Photo credit: Mark Fisher at www.fishercreative.com, Instagram: @fishercreative; via Juniper.
Juniper Systems’ Archer Field PC has beenused to record the elevation of a never-before-climbed peak in the remote Myanmar Himalaya. The peak, Mount Gamlang Razi, has historically been known as the second highest peak in Southeast Asia, but a joint American-Myanmar-led expedition set out on a mission last September to hopefully prove that it is in fact the tallest. Read the whole story on Juniper Systems’ blog.
Standing at a reported 5,881 meters tall, Mount Hkakabo Razi has long been known as Southeast Asia’s highest peak. In recent years, however, the legitimacy of the elevation of Hkakabo Razi has come into question. Current digital analysis suggests that initial surveys of Mount Hkakabo Razi were overstated and its actual elevation is as much as 100 meters lower than originally believed. At the same time, digital analysis suggests that virgin-peak Gamlang Razi may in fact be the taller peak. This controversy prompted Idaho resident and experienced climber Andy Tyson to lead an American-Myanmar expedition team on a three-week approach through 150 miles of cobra-riddled, mosquito-infested jungle, and from there up to the peak of Gamlang Razi to measure its elevation in person.
Tyson needed a device that could accurately record the elevation at the summit, while being able to withstand the extreme conditions of the hot, wet jungle and the frozen mountaintop. With this in mind, Tyson requested from Juniper Systems a top-of-the-line rugged handheld. In response, Juniper Systems provided the team with an Archer Field PC with Hemisphere GPS XF101 receiver, along with training to record the GPS data they needed.
Setting up the Archer Field PC to collect GPS data. Photo credit: Mark Fisher at http://www.fishercreative.com/Instagram: @fishercreative/via Juniper.
After a 35-day journey, Tyson and the team successfully summited Gamlang Razi, with the Archer Field PC in hand. After collecting GPS data at the top, the data was sent via satellite phone to Juniper Systems for analysis. After post-processing the data against terrestrial base stations in Lhasa, Tibet, and confirming the results with Effigis in Montreal, Canada, Juniper Systems concluded that the elevation of Gamlang Razi was 5,870 meters, ±2 meters. This suggests that Gamlang Razi is taller than nearby Hkakabo Razi by approximately 112 meters and should be considered Southeast Asia’s new highest peak.
However, there are many — particularly natives to Myanmar — who are not ready to accept changes to Hkakabo Razi’s original elevation measurement. This was made apparent in a letter Myanmar’s president, Thein Sein, wrote to Tyson and the team after their successful summit, congratulating them for summiting Southeast Asia’s second-tallest peak.
Tyson remains firm in his assertion that Gamlang Razi is the country’s highest peak, but some have suggested that the debate may not be over until someone actually climbs Hkakabo Razi and measures it in person. Juniper Systems said they have a handheld for the job, should that time come.
The expedition team. Photo credit: Mark Fisher at http://www.fishercreative.com. Instagram: @fishercreative/via Juniper.
The Sochi 2014 Olympic Winter Games mobile app, Wireless Olympic Works (WOW), turns the world’s Android devices into mobile sports stations that fans can use to personalize their own Olympic Winter Games experience, according to maker Samsung Electronics.
The XXII Olympic Winter Games, held in Sochi, Russia, run February 7-21.
Fans attending the Olympic Winter Games in Sochi will have access to a location-based Olympic Winter Games venue guide through the Samsung WOW technology. The guide offers Olympic venue information and navigation services so visitors can feel truly integrated into the Olympic Winter Games experience on the ground, Samsung said.
Samsung’s Public WOW app also provides sports fans with real-time access to event schedules, latest reports on results, medal standings and Olympic records. Public WOW is an extension of Samsung’s custom WOW for the Olympic Family, which is a wireless communications platform developed to ensure smarter communications and smoother, wireless operations of the Olympic Winter Games by offering news and information about the games to officials and staffs.
“Samsung is offering fans around the world the most direct access to Sochi 2014 Olympic Winter Games and allowing them to design and personalize their experience in ways that are most relevant to their interests and passions,” said WS Lee, senior vice president of New Business Development, Mobile Communications Division at Samsung Electronics. “Our dedicated teams are hard at work year-round to ensure that the WOW technology is ready for use throughout the Games, both for consumers looking for the ultimate Olympic Winter Games experience, and for the Olympic Family utilizing our technology to support Games-time operations.”
All Android users worldwide can download Samsung’s Public WOW app via the Samsung App store and Google Play.
Components of the Samsung WOW app allow fans to design their own Olympic Winter Games experience in the following ways:
Personalize an Olympic Winter Games updates plan. highly personalized, live Games-time updates ranging from medal counts to big moments that can be pushed to users’ phones in real time. A new cheering service will allow fans to send cheers to support their favorite athletes and countries.
Share celebrations with social network features. Users can upload text and images instantly to share with other WOW app users and with their social networks, creating a global community around shared interests in the Olympic Winter Games and winter sports. Languages supported for the Public WOW app include Chinese, English, French, German, Korean, Russian and Spanish.
Learn about Olympic sports with an interactive, visual guide. The app offers information on all 15 winter sports at Sochi 2014 through a highly visual and engaging graphic user interface. A Visual Sports Guide will provide tutorials on each sport, including rules, equipment details and many other points of interest bring people closer to the excitement of the Olympic Winter Games.
“With its advanced technology in wireless communications, Samsung has played an essential role in the successful operation of the Olympic Winter Games. We believe the WOW app for Sochi 2014 will once again benefit the Games with more efficient and faster communications for the Olympic Family as well as fans around the world” said Timo Lumme, managing director, IOC TMS.
As part of the “Samsung Smart Olympic Games Initiative,” Samsung will provide around 18,000 mobile devices to the Olympic Family, including executives, staff, and officials from the IOC, National Olympic Committees and organizing committees in Sochi. They will be connected to Samsung’s WOW service which will provide essential, up-to-date Games Time data and connectivity that is crucial to the Olympic Winter Games operation.
The Samsung WOW service was first launched during the Athens 2004 Olympic Games for the Olympic Family and has since evolved into a must-have resource for officials, attendees and fans worldwide.
Samsung began its Olympic Games involvement as a local sponsor of the Seoul 1988 Olympic Games. Beginning with the Nagano 1998 Olympic Winter Games, the company extended its commitment to the Olympic Movement as the Worldwide Olympic Partner in the Wireless Communications Equipment category, providing its proprietary wireless communications platform, called Wireless Olympic Works (WOW), and mobile phones. These mobile phone technologies provide the Olympic Family with real-time, user location-based information service and interactive communications. Samsung’s commitment as a Worldwide Olympic Partner continues through to Rio 2016.
Connected vehicles can help to mitigate crashes on busy urban streets.
The U.S. Department of Transportation’s (DOT) National Highway Traffic Safety Administration (NHTSA) announced today that it will begin taking steps to enable vehicle-to-vehicle (V2V) communication technology for light vehicles. This technology would improve safety by allowing vehicles to “talk” to each other and ultimately avoid many crashes altogether by exchanging basic safety data, such as speed and position, ten times per second, the agency said.
“Vehicle-to-vehicle technology represents the next generation of auto safety improvements, building on the life-saving achievements we’ve already seen with safety belts and air bags,” said U.S. Transportation Secretary Anthony Foxx. “By helping drivers avoid crashes, this technology will play a key role in improving the way people get where they need to go while ensuring that the U.S. remains the leader in the global automotive industry.”
DOT research indicates that safety applications using V2V technology can address a large majority of crashes involving two or more motor vehicles. With safety data such as speed and location flowing from nearby vehicles, vehicles can identify risks and provide drivers with warnings to avoid other vehicles in common crash types such as rear-end, lane change, and intersection crashes. These safety applications have been demonstrated with everyday drivers under both real-world and controlled test conditions.
The safety applications being developed provide warnings to drivers so that they can prevent imminent collisions, but do not automatically operate any vehicle systems, such as braking or steering. NHTSA is also considering future actions on active safety technologies that rely on on-board sensors. Those technologies are eventually expected to blend with the V2V technology. NHTSA issued an Interim Statement of Policy in 2013 explaining its approach to these various streams of innovation. In addition to enhancing safety, these future applications and technologies could help drivers to conserve fuel and save time.
V2V technology does not involve exchanging or recording personal information or tracking vehicle movements. The information sent between vehicles does not identify those vehicles, but merely contains basic safety data. In fact, the system as contemplated contains several layers of security and privacy protection to ensure that vehicles can rely on messages sent from other vehicles and that a vehicle or group of vehicles would be identifiable through defined procedures only if there is a need to fix a safety problem.
In August 2012, DOT launched the Safety Pilot “model deployment” in Ann Arbor, Michigan, where nearly 3,000 vehicles were deployed in the largest-ever road test of V2V technology. DOT testing is indicating interoperability of V2V technology among products from different vehicle manufacturers and suppliers and has demonstrated that they work in real-world environments.
In driver clinics conducted by the Department prior to the model deployment, the technology showed high favorability ratings and levels of customer acceptance. Participants indicated they would like to have V2V safety features on their personal vehicle.
“V2V crash avoidance technology has game-changing potential to significantly reduce the number of crashes, injuries and deaths on our nation’s roads,” said NHTSA Acting Administrator David Friedman. “Decades from now, it’s likely we’ll look back at this time period as one in which the historical arc of transportation safety considerably changed for the better, similar to the introduction of standards for seat belts, airbags, and electronic stability control technology.”
NHTSA is now finalizing its analysis of the data gathered as part of its year-long pilot program and will publish a research report on V2V communication technology for public comment in the coming weeks. The report will include analysis of the Department’s research findings in several key areas including technical feasibility, privacy and security, and preliminary estimates on costs and safety benefits. NHTSA will then begin working on a regulatory proposal that would require V2V devices in new vehicles in a future year, consistent with applicable legal requirements, Executive Orders, and guidance. DOT believes that the signal this announcement sends to the market will significantly enhance development of this technology and pave the way for market penetration of V2V safety applications.
“We are pleased with the direction NHTSA is taking in terms of V2V technology,” said Greg Winfree, Assistant Secretary for Research and Technology. “The decision to move forward comes after years of dedicated research into the overwhelming safety benefits provided by a connected vehicle environment.”
V2V communications can provide the vehicle and driver with 360-degree situational awareness to address additional crash situations — including those, for example, in which a driver needs to decide if it is safe to pass on a two-lane road (potential head-on collision), make a left turn across the path of oncoming traffic, or in which a vehicle approaching at an intersection appears to be on a collision course. In those situations, V2V communications can detect threats hundreds of yards from other vehicles that cannot be seen, often in situations in which on-board sensors alone cannot detect the threat.
NHTSA has worked in close partnership in this research both with other DOT agencies, including the Office of the Assistant Secretary for Research and Technology and the Federal Highway Administration, and with several leading auto manufacturers and academic research institutions, who have invested significant resources into developing and testing V2V technology. The collaboration of government, industry and academia is critical to ensure V2V technology’s interoperability across vehicles.
The European GNSS Agency (GSA) is inviting European industries and Member State Competent Public Regulated Service (PRS) Authorities to share their views and ideas on which technologies at user segment level are important to support the adoption of the PRS. In particular, industries with potential interests and capabilities to support the development of Galileo PRS user segment technologies such as receivers, security modules, and dedicated infrastructure are encouraged to join the discussion.
PRS signals will be restricted to authorized users by governments for sensitive applications that require a high level of continuity. The PRS uses robust signals that are encrypted and resistant to jamming.
The GSA’s objective is to ensure that PRS service is affordable and secure for all interested users while also ensuring that European industry maintains its competitive edge in the global satellite navigation marketplace.
The GSA has already conducted several studies and projects aimed at identifying, developing and sustaining the necessary technology to support PRS market uptake. Additional initiatives are expected to be launched within the Horizon 2020 Framework Programme and in other programme initiatives in late 2014 and 2015.
Based on openly available information, the GSA has drafted a roadmap for developing and identifying the necessary secure technologies. This roadmap will be augmented by information gathered during the current consultations. It is expected that industry will provide additional inputs and ideas that may be
explored in the frame of Horizon 2020 and other initiatives. The GSA will use this information in planning long-term activities in support of PRS adoption, with a focus on technology preparation for a more effective market uptake.
Consultations will focus on the following topics:
Necessary steps for transforming the identified technologies into products competitive enough in terms of cost, power, dimension etc. to support the market uptake of PRS within the 2018-2020 timeframe.
Collection of information on the current European capability and capacity with the manufacturing sectors, with particular attention to nanotechnology manufacturing capabilities, and ideas of how to better use it for PRS market uptake.
Ideas of how to build, starting from the most promising technologies, the manufacturing lines capable of serving the PRS user segment need.
Main domains, elements and interfaces that will benefit from standardization, allowing for a stronger market adoption of PRS.
The deadline to receive requests is February 28. All consultations will be organized between February and April 2014. For more information and to arrange a one-on-one meeting, send an email to: [email protected].
Galileo PRS is restricted to governmental authorized users. It is intended for use with sensitive applications that require a high-level of service continuity. Authorized users include Member States, European Council, European Commission, EEAS, EU agencies and, subject to security agreements with the EU, third countries and international organizations.
Despite major GPS fitness device OEMs announcing new fitness products at January’s International Consumer Electronics Show in Las Vegas, it looks like an increasingly difficult battle between smart devices and wearables, according to analysts at ABI Research.
Garmin launched its Vivofit fitness band and Vivoki/Vivahub corporate wellness solution. Magallen is one of the few companies in the GPS device OEM space that continues to show flashes of innovation, opening up its Echo watch platform to a range of third-party smartphone application developers.
At the high-end of the GPS fitness watch market, Polar has launched a new multi-sport watch, which features a barometric pressure sensor, support for new features such as a cycling power pedal. TomTom has launched an iOS application that links its current GPS watch range to an iPhone via Bluetooth.
In ABI Research’s quarterly GPS/GNSS Device tracker, the impact of these new device categories on dedicated GPS fitness device growth can be fully seen. Senior analyst Patrick Connolly comments, “Our forecasts for the overall GPS-enabled fitness area remain strong, hitting $2.6 Billion in 2018, but as was the case with turn-by-turn navigation, converged devices and wearables will take an increasing part of the available market. The adage of keeping what we have is important here, retaining a firm eye on growth in professional users, with hardware and in particular eyewear, a major distinguisher.”
Practice director Dominique Bonte adds, “Of the announcements, Garmin’s move into corporate wellness was the most striking. We are about to see a huge technological shift in the corporate/business sector, around BYOD, BYOW, wellness, security, and efficiency. What is interesting is that Garmin does not include a location element, which will be a core enabler in this sea change.”
BeiDou Releases Public Service Performance Document
In late December, director Ran Chengqi of China’s Satellite Navigation System Management Office announced the BeiDou Navigation Satellite System (BDS) Public Service Performance Standard. The document details the public service performance parameters of the BeiDou system, including service area, accuracy, integrity, continuity, and availability. It is a basic commitment to customers from BDS providers, but also an important basis for customers to choose, use, and evaluate the system performance.
Also released is Version 2 of the BDS Interface Control Document (ICD) for the Open Service Signal. Among other changes, it includes a description of the B2I signal on 1207.140 MHz.
The publishing of the Public Service Performance Standard, a common practice among GNSS operators, is also a prerequisite for BeiDou system involvement in international civil aviation, international maritime, 3rd Generation Mobile [phone] System, and other international standard-setting organization activities.
The document has Chinese and English versions. Because document download from the BDS government website can be difficult, Richard Langley has made them available at the University of New Brunswick website:
Analysis. John Lavrakas of Advanced Research Corporation posted the following comment to the online version of this news story:
“I took a quick look at comparing the BeiDou Open Service Performance Standard with the GPS Standard Positioning Service Performance Standard and obtained mixed results.
“In some cases, the commitments from BeiDou were stronger (URE accuracy, the table to show green for the GNSS service committing to a more stringent standard over the other vertical position), and in other cases the commitments from GPS were stronger (continuity of service, advance notice of outages).
Table 1. Coded to show green for the GNSS service committing to a more stringent standard over the other. Courtesy of Advanced Research Corporation.
Galileo to Sail, Penalty-Free
Schedule Overruns Not a Problem, Avers Space Agency Director-General
Athough the European Commission (EC) sternly put in place financial penalties for late delivery and arrival on orbit of Galileo satellites, the European Space Agency (ESA) that manages the process will not suffer the consequences of a one-year delay in their launch. The EC did not sign an industrial contract with the ESA for the Galileo work, according to an announcement by ESA Director-General Jean-Jacques Dordain made the announcement in mid-January 17.
Dordain said under the agreement, the EC pays for ESA’s staff costs, while ESA acts as technical manager for the program. But the industrial contract itself to build the satellites — and specifying the penalities — was not encompassed by this agreement.
Galileo’s schedule is now firmly back on track, according to ESA,since the first OHB satellite passed thermal-vacuum testing in November, and the second satellite is in the test chamber. Signals are apparently “go” for their launch in June aboard Soyuz rocket from Guiana Space Center in South America. A second pair should launch in October, and a third in December.
Meeting an Aggressive Date. The EC committed some time ago to start initial Galileo services in 2014. Delivery on this promise has become increasingly unclear after recent testing delays. Getting new Soyuz launch dates withing this year is not a sure-fire thing, either.
The Galileo Supervisory Authority earlier announced that it had validated the four initial operating-capability (IOV) Galileo spacecraft in orbit as perform twice as well as expected in terms of signal accuracy. However, the satellites provide very limited use, about one hour per day when all are visible to the same user.
Once six satellites become visible inthe sky, sometime after the planned June launch, testing qualification of early services can begin. With eight, actual service qualification is possible but not certain. Finally, with 10 satellites — December? — early services may be able to start.
Earlier last year, EC Vice President Antonio Tajani had warned that financial penalties to those building Galileo would cover the cost overruns due to the delay in launching the system. His finger appeared to point at ESA as much as OHB AG of Germany and Surrey Satellite Technology Ltd. of Britain, who lead the industrial consortium building the satellites.
The main antenna of the second Galileo Full Operational Capability (FOC) satellite being inspected with a flashlight in advance of mass property testing at the European Space Agency’s ESTEC Test Centre in the Netherlands. Thermal-vacuum testing on the second model began in early 2014. The two FOC satellites will be launched on a Soyuz rocket from Europe’s French Guiana Spaceport in mid-2014. Whether four more can rise and begin providing initial Galileo services by the end of the year is the question of the hour.
U.S.Transport DepSec Takes Potshot at CNAV
The departing Deputy Secretary of Transportation, John Porcari, wrote a letter in the closing days of 2013 opposing the U.S. Air Force’s announced plans to begin broadcasting Civil Navigation (CNAV) message-populated L2C and L5 signals as early as April 2014. Military personnel are incensed over what they see as Porcari’s impugning, when not ignoring, the Air Force 35-year track record of broadcasting the gold standard of global navigation satellite signals — something in which Transportation has zero experience.
Porcari alludes in his December 27 letter to “non-standard engineering tools” and “non-standard operations” that he believes would come into play for early CNAV broadcast. “These have the potential to inject human error, which may result in unacceptable GPS constellation operation.”
What Porcari means by “non-standard” he does not specify, although he confesses to unease as “the ability to monitor these signals, [without which] the system will not know if the L2C and LS signals are within specification. Given these risks, DOT is concerned that the CNAV messages could provide hazardously misleading information, impacting GPS safety-of-life, protection of property, and economic security applications.” The full text of the Porcari letter is available here.
OCX Delay the Cause? Because the current GPS ground control system cannot generate CNAV, and the next-generation OCX —which can — will not be ready by April, anothercomputer will apparently develop the civil signal navigation data. However, neither the data or message is intended for actual use, nor will the FAA or any transport agency employ it. The advance project is designed to aid reciever manufaturers and developers in adpting to the new signal.
In addition to questioning Air Force 2 SOPS ability to broadcast an accurate, compliant signal containing CNAV, the letter appears to ignore — or be ignorant of — the 17 official U.S. government/military monitoring sites for GPS distributed around the world, not to mention thousands of other monitoring sites run by government agencies such as the Jet Propulsion Laboratory, the National Aeronautics and Space Administration, and the National Geospatial-Intelligence Agency, and by many universities such as Stanford, Ohio State, Cal Tech, and many other international institutions around the world. Many of these sites collaborate under the rubric of the International GNSS Service.
Finally, John Deere and Trimble Navigation both operate automated GPS signal monitoring systems that that report any anomaly in the navigation message for all GPS signals with an average two-second notification time.
“This letter is so much BS,” fumed one source who wished to remain anonymous, “coming from an agency that is in arrears in its GPS payments to the tune of more than $70 million and has no clue how to represent the global GPS user. GPS is a ubiquitous system, not just a tool for the DOT and the Federal Aviation Administration. GPS needs to implement these signals for all users and as a modernization program that was promised to be in place years ago.”
Porcari left for the private sector.
OCX Change Order to Ensure Proper M-Code Function
Raytheon Intelligence and Information Systems has been awarded a change order for work that costs up to $8.5 million on its existing contract to ensure that the new military signal, M-code, works with the GPS Operational Control System, according to an announcement from the Pentagon as reported by Space News.
Raytheon is building the ground station (OCX) for a new generation of satellites that will bring more safety and precision to GPS. The contract modification is to assure implementation of M-code capabilities across OCX Block 1 and 2. M-code is the new highly secure, anti-jam signal designed for the GPS III constellation. The current GPS ground control system lacks M-code capability.
The OCX is designed to work with the advanced GPS III positioning, navigation and timing satellites, slated to start launching in 2015, and also will be backwardly compatible with existing GPS satellites.
Raytheon won the $886.4 million prime contract to develop the OCX in February 2010. Work will be performed at Raytheon’s facility in Aurora, Colorado, and is expected to be completed by August 31, 2016.
The Air Force Space and Missile Systems Contracting Directorate, Los Angeles Air Force Base, California, is the contracting agency.
Details. Raytheon Intelligence and Information Systems, Aurora, Colorado, was awarded the unpriced change order (P00112) with a not-to-exceed of $8,595,748 on an existing contract (FA8807-10-C-0001) for M-Code Implementation on the Operational Control System. The contract modification is to assure implementation of M-Code Capabilities across OCX Block 1 and 2. Work will be performed at Aurora and is expected to be completed by August 31, 2016. Fiscal 2014 research and development funds will be obligated at definitization.
GAGAN Certified for Aviation over India
The Director General of Civil Aviation of India has certified the GPS-Aided Geo Augmented Navigation (GAGAN) system to Required Navigation Performance 0.1 Nautical Mile (RNP0.1) service level.
Aircraft equipped with satellite-based augmentation system (SBAS) receivers can now use GAGAN signals in Indian airspace for en route navigation and non-precision approaches without vertical guidance.
Mission control centers and uplink stations now operate on Indian soil. Messages carrying corrections to GPS signals are sent to satellites in geostationary orbit carrying the GAGAN payload.
The availability of the GAGAN signal over Indian airspace bridges the gap between European Union’s European Geostationary Navigation Overlay Service (EGNOS) and Japan’s Multi-functional Satellite Augmentation System (MSAS) coverage areas.
The SBAS consists of 15 Indian reference stations, three uplink stations, three mission control centers, and three GAGAN payloads broadcasting in C and L bands and with all the associated software and communication links.
GAGAN will provide augmentation service for GPS over India, the Bay of Bengal, South East Asia and the Middle East expanding up to Africa.
Car, Nav Makers Emulate NSA: Track, Store Consumer Data
U.S. Big Three automakers and some Japanese car companies track and store data from customers’ on-board navigation systems, according to a report from the U.S. Government Accountability Office. The document describes, in general fashion, practices at General Motors, Ford, Chrysler, Toyota, Honda, and Nissan, and further delves into data storage by GPS manufacturers Garmin and TomTom and nav app designers Google Maps and Telenav.
The GAO said the automakers collect data at times to assist customers with traffic updates, emergency roadside assistance, and to track stolen vehicles.None of the companies currently sell the data, according to the report, but most drivers do not know what information is being tracked and cannot opt out of the data collection programs.
The companies can “track where consumers are, which can in turn be used to steal their identity, stalk them or monitor them without their knowledge. In addition, location data can be used to infer other sensitive information about individuals such as their religious affiliation or political activities.”
The report claims the companies’ privacy policies are sometimes unclear, making it difficult for consumers to understand the potential risks of using their GPS navigation devices.
No federal law regulates GPS privacy; it is not illegal for private companies to collect, use, or sell personal information. Several proposals have been floated in Congress to protect the privacy of GPS data, but none enacted.
The Business section from the January 2014 issue (Download the PDF). Includes: 2014 Receiver Survey Addendum (for the full survey, click here); FAA Selects Six Sites for UAV Research; NovAtel Supplies Reference Receivers for IRNSS Ground Segment; SkyTraq Seeks Crowdfunding for GPS/BeiDou Development Board; Hemisphere GNSS Names Chuck Joseph President and CEO; Honda Joins Google Alliance to Develop GPS Solutions; Garmin Launches New Outdoor Series; Saelig Introduces Low-Cost SMD Antennas; Events
By Wei Zhang, Attila Komjathy, Simon Banville, and Richard B. Langley
INNOVATION INSIGHTS by Richard Langley
MAY YOU LIVE IN INTERESTING TIMES. So goes the purported Chinese proverb and curse. When it comes to the ionosphere, an interesting time might indeed be a curse for most users of GPS. The ionosphere – that region of the upper atmosphere where free electrons exist in sufficient numbers to affect the propagation of radio waves – owes its existence primarily to the extreme ultraviolet (EUV) and x-ray photons emitted by the sun. They ionize atoms and molecules in the upper atmosphere, freeing the outer electrons. Mostly the ionosphere is well behaved but it can get quite interesting when it is disturbed by space weather events such as solar flares or coronal mass ejections.
The signals from the GPS satellites are perturbed as they transit the ionosphere. Pseudorange measurements are increased in value (an additional delay) and carrier-phase measurements are decreased (a phase advance). If not fully modeled or otherwise accounted for, the perturbations can decrease the accuracy of GPS positioning, navigation, and timing (PNT). For highest PNT accuracies, observations are made at the two frequencies transmitted by all GPS satellites and because the ionosphere’s effect on radio signals is dispersive, a linear combination of the measurements removes almost all of the ionospheric perturbations. On the other hand, the ionosphere’s effect on single frequency observations must be corrected using a model. Most commonly, the model assumes that all of the electrons in the ionosphere can be compressed into a thin shell at a certain height above the receiver. This permits the computation of an estimate of the vertical ionospheric delay. Then, a mapping function is used to predict the slant delay, the delay contributing to a GPS measurement. The approach works reasonably well, particularly if near-real-time values of vertical delay can be provided to users as is done by the Wide Area Augmentation System and other satellite-based augmentation systems. However, this two-dimensional approach ignores the fact that the electron content of the ionosphere is actually spread out in the vertical direction and so has certain inaccuracies, which can increase when the ionosphere is disturbed.
In an effort to improve ionosphere modeling with potential application to single-frequency GNSS users, a couple of my current graduate students together with a former student, have investigated a three-dimensional approach to ionospheric modeling using empirical orthogonal functions or EOFs to describe the vertical structure of the ionosphere. EOFs reduce the dimensionality of a data set or an empirical model consisting of a large number of interrelated variables, while retaining as much of the variance present in the data set as possible. This is achieved by transforming to a new set of variables, the orthogonal functions, which are uncorrelated (orthogonal), and which are ordered so that the first few retain most of the variation present in all of the original variables. Only three functions are required to account for more than 99 percent of the variability in the International Reference Ionosphere – 2007, for example.
In this month’s column we look at the performance of this 3D approach to modeling the ionosphere including times when the ionosphere is particularly interesting.
“Innovation” is a regular feature that discusses advances in GPS technology and its applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas.
Ionospheric modeling plays an important role in improving the accuracies of positioning and navigation, especially for current civil aircraft navigation and mass-market single-frequency users. Measurement-driven models are considered to be among the best candidates for real-time single-frequency positioning owing to their real-time applicability and relatively higher accuracy compared to empirical models, such as the GPS broadcast (also known as Klobuchar) and NeQuick models. A good example of a real-time positioning application is satellite-based augmentation systems (SBAS), including the Wide Area Augmentation System (WAAS), the European Geostationary Navigation Overlay Service (EGNOS), the Japanese MSTAT Satellite-based Augmentation System (MSAS), and the Indian GPS Aided Geo Augmented Navigation system (GAGAN). Because the ionosphere can be the largest error source in single-frequency positioning, the accuracy of ionospheric modeling is critical for single-frequency applications.
Several organizations have been routinely providing ionospheric products to correct errors caused by the ionosphere in the form of ionospheric maps — that is, vertical total electron content (vTEC) at grid points (including regional and global products), such as those from WAAS and the International GNSS Service (IGS), with various processing time delays ranging from near real time to a couple of weeks. Among the earliest works of ionosphere modeling, the University of New Brunswick-Ionospheric Modeling Technique (UNB-IMT) was developed in the mid-1990s. This technique was demonstrated to effectively derive both regional and global total electron content (TEC) maps. However, most of the models, including the current version of UNB-IMT, approximate the ionosphere using a single thin-shell approach with an altitude set at, for example 350 km, which may introduce additional modeling errors up to several TEC units (1 TECU = 1016 electrons/m2), corresponding to meter-level errors of measurement delay or advance at the GPS L1 frequency.
To overcome any downside of such models, three-dimensional (3D) ionospheric tomographic modeling methods have been proposed and implemented by several groups since the late 1990s. Different from the two-dimensional (2D) single thin-shell ionospheric models, where the parameters to be estimated are associated with TEC, the modeled variables in the tomographic model are related to electron density functions. Therefore, we may expect more complex structures of electron densities (such as those observed during ionospheric storms or in the highly variable equatorial anomaly) to be revealed by the models. A commonly accepted modeling approach is to describe the ionospheric horizontal (longitudinal and latitudinal) variability by a spherical harmonic (SH) expansion up to a specific degree and its vertical dimension modeled by empirical orthogonal functions (EOFs).
However, SH models are not ideal for capturing local variability in the ionosphere because each basis function of spherical harmonics exists over the entire geographic region of interest, such as the entire globe in the case of global modeling. In other words, localized measurements will have influence on the estimated state across the whole globe. As alternative approaches, wavelet, finite element (meshes/pixels), and local-basis-function models have been proposed and implemented to capture the localized information content in the measurements and pass this information on to the end user. On the other hand, the inversion process can occasionally become singular as many of the parameters to be estimated tend to be ineffective and less meaningful. This is especially the case when our goal is to obtain better accuracies with higher order wavelet bases or smaller meshes/pixels. Due to the potential computing and transmitting burden, the two modeling techniques may have more difficulties associated with real-time applications, such as real-time single-frequency positioning, although they have advantages for capturing localized structures in the ionosphere.
Aiming for potential real-time applications of 3D tomographic models, we have extended the UNB-IMT from 2D to 3D by modeling the vertical dimension of the ionosphere using EOFs. In this article, we discuss our approach and report on some initial tests including comparing its performance with the 3D SH approach.
The 2D UNB-IMT was demonstrated to work with various network sizes: regional, baseline-by-baseline, and even single standalone stations. Therefore, it is expected that this technique will help in capturing localized ionospheric structures above small regional networks or above a single standalone station. Additional benefits may be expected for disturbed ionospheric conditions. For assessing the two modeling techniques, a small regional network was chosen to perform station-by-station and batch processes. The performance of both methods with the two processing scenarios has been compared by analyzing the post-fit residuals and vTECs of the state estimation process, as well as the repeatability of estimates of differential code biases (DCBs) for both quiet and disturbed ionospheric conditions.
3D UNB-IMT
Because of the limited number of ionospheric parameters to be estimated, the 2D UNB-IMT was considered suitable for real-time applications, such as real-time single-frequency precise point positioning (PPP) and SBASs. In fact, it can be proven that the modeling method of the current 2D UNB-IMT is identical to the original planar fit of WAAS in nature if the locations of reference stations tend to collocate with WAAS ionospheric grid points (IGPs). Although additional parameters are involved, we believe the 3D UNB-IMT approach with its potential for improved modeling accuracy is still suitable for real-time applications. In this section, we will introduce the 3D UNB-IMT modeling strategy and demonstrate its applicability with a regional network and single standalone stations.
Model Description. In order to clearly present the technique demonstrated in our recent work, we first briefly review the 2D UNB-IMT. Linear polynomial functions were initially proposed for describing the spatial variability of the ionosphere. We model the observed slant TEC (sTEC) between a satellite and a receiver from carrier-phase and pseudorange (code) observations at some epoch as the product of a bilinear polynomial representing the vTEC at the thin-shell ionospheric pierce point (IPP) of the signal raypath and a mapping function that projects the vTEC to sTEC plus receiver and satellite instrumental biases (DCBs). The input variables are the geographic longitude of the IPP referenced to the solar-geomagnetic coordinate system (in other words, the difference between the longitude of the IPP and the longitude of the mean sun) and the difference between the geomagnetic latitude of the IPP and the geomagnetic latitude of the station. We consequently have three polynomial coefficients to estimate for each station: a constant term, one to describe the longitude variations, and one for the latitude variations.
The mapping function used in the model is the standard geometric mapping function, which computes the secant of the zenith angle of the signal geometric ray path at the IPP at a specified shell height. Because of the dependence of the ionosphere on solar radiation and the geomagnetic field, the solar-geomagnetic reference frame is used to compute the TEC over each station in this technique. Since the ionosphere changes more slowly in the sun-fixed reference frame than in the Earth-fixed one, such a reference frame is ideal for producing more accurate TEC estimates.
The initial version of UNB-IMT ignored the non-linear spatial variation of the ionosphere. Non-linear terms are expected to be able to absorb more complex variability of the ionosphere and thus more properly describe the ionosphere in disturbed conditions. Regarding this issue, the drawbacks of some modeling methods based on linear models have been reported: for example, the highly variable ionosphere might be absorbed by the estimated DCBs, making the repeatability of the estimated DCBs (day-to-day variability) correlated with the variability of the ionosphere. To enhance the performance of UNB-IMT, especially under disturbed ionospheric conditions, UNB researchers extended the linear version of UNB-IMT to a quadratic one and assessed it by using a wide-area regional network in North America. This modified approach reduced the post-fit residuals significantly by better modeling the ionospheric variations with the help of the additional second order (non-linear) terms.
To better use a priori information in the development of 3D UNB-IMT, we separate the TEC into a background reference or “known” part and a perturbation or to-be-modeled part. The background reference part of TEC could be calculated from an a priori source of electron density, such as any kind of ionospheric model, including empirical and theoretical ionospheric models. The density, as a function of latitude, longitude, height, and time, is integrated along the raypath between the receiver and a satellite.
Then, the perturbation part of the electron density is modeled by the inner product of EOFs and polynomial functions with associated estimated coefficients to depict the variability of the ionosphere in the vertical and horizontal directions respectively. And this part is similarly integrated along the raypath and added to the reference part along with the DCBs.
Empirical Orthogonal Functions. The EOF method is a method of choice for analyzing the variability of a single field (with only one scalar variable). Variability of the ionosphere with respect to height is needed for the 3D models. The method finds the spatial patterns of variability based on historical data sets (as reflected in empirical or theoretical models). In other words, the modes of variability decomposed by the method are primarily “data modes,” and not necessarily physical or actual real-time models. Due to its noted ability in describing the background ionosphere, the data sets output from the empirical Ionospheric Reference Ionosphere 2007, were utilized to form the EOFs in our technique.
Thus, the data sets of electron densities are realized by uniform sampling at the following variant time scale intervals and specific geographic locations:
Solar cycle: [1998:1:2008] (year)
Season of year: [Dec., Mar., Jun., Sep.] (month)
Time of day: [1:1:24] (hour)
Day of month: [1:9:28] (day of month)
Geographic latitude: [30:5:60] (degree)
Geographic longitude: [280:5:300] (degree),
where the numbers separated by colons correspond to minimum:increment:maximum. The data sets cover the whole spatial area of interest. The data sets of a whole solar cycle in typical equinox and solstice months are used to ensure that the EOFs span the range of profile variations that include the variation in solar EUV and x-ray output. Each electron density profile with respect to height at these locations and time points is sampled in the vertical dimension at [100:2:2000] (km). Figure 1 shows the first three third-order normalized EOFs based on the data sets. The first three eigenvalues account for 92.22, 6.69, and 0.78 percent of the total respectively. Provided the solution is nonsingular, the choice of the highest order of EOFs is a trade off between processing time and modeling accuracy as to the specific network and capability of computer(s). In our current work, the highest order of three was chosen. In this case, the neglected vertical variation of the ionosphere corresponding to higher order EOFs is 0.31 percent.
FIGURE 1. The normalized first three dominant EOFs extracted from the IRI-2007 empirical model.
Once the modeling approach has been constructed, the following task is to estimate the coefficients. Considering the potential real-time applications, a Kalman filter is employed to solve the TEC observation equation. To be specific, the following settings are used. The correlation time is set to five minutes, which correspond to the WAAS update interval for ionospheric grid points. The uncertainty of the dynamic model, 0.008 TECU2/second, is chosen to characterize the potential rapid change of the ionosphere.
Finally, the estimated coefficients provided by the Kalman filter are then used to reconstruct the electron density field.
Testing the Approach
In this section, we report on tests of the 3D UNB-IMT and compare its performance with that of the 3D SH approach. Because of the advantages of sensitivity of 2D UNB-IMT, especially with the single-station processing strategy, it is expected that this technique will help in better capturing localized ionospheric structures above small regional networks or above a single standalone station compared to the 3D SH approach. Additional benefits may be expected for disturbed ionospheric conditions.
For assessing the two modeling techniques, a small regional network of four IGS reference stations located from geographic latitude 39.0° N to 48.1° N and longitude 66.7° W to 77.6° W was chosen to perform single-station and multi-station (network) processing. The stations are GODZ in Greenbelt, Maryland; UNBJ and FRDN in Fredericton, New Brunswick; and VALD in Val d’Or, Quebec. Figure 2 shows the locations of the reference stations chosen for the modeling. The dual-frequency GPS data used for the tests was obtained from October 13–25 (day of year (doy) 286–298) in 2011 with the sampling time interval of 30 seconds. The corresponding values of the interplanetary magnetic field Bz component; the planetary geomagnetic index, Kp; the auroral electrojet index, AE; and the disturbance storm-time index, Dst on these days are shown in FIGURE 3. It is seen that a severe ionospheric storm triggered by a coronal mass ejection from the sun occurred late on October 24 (doy 297), 2011, and continued through the entire day of October 25 (doy 298), 2011. The other days seem relatively quiet. Thus, we chose October 16, 2011, as a typical day with quiet ionospheric conditions and October 25, 2011, as a typical day with disturbed ionospheric conditions in the following tests. The performance of both methods (3D UNB-IMT and SH model) with the two processing scenarios will be compared by analyzing the post-fit residuals and TEC of the state estimation process for both quiet and disturbed ionospheric conditions.
FIGURE 2. The network of the four stations used in the evaluation procedures.
All four reference stations in the small network have the ability to provide both C/A- and P-code pseudorange measurements. In our tests, the P-code observable is used to extract TEC through leveling the corresponding carrier-phase measurements. We used a 15°-elevation-angle cut-off in our study.
Single Station Experiment. The estimated parameters of 2D and 3D UNB-IMT have different physical meanings due to the different modeling strategies. In theory, the 3D UNB-IMT can reproduce the electron densities for any location (horizontal and vertical) at any epoch. Figure 4 shows an example of the electron density profile produced by the linear 3D UNB-IMT in the zenith direction of station FRDN at 12:00 UT on October 16 (doy 289), 2011. Therefore, we will have to integrate electron densities into TEC for the 3D UNB-IMT modeling results if we want to compare how the two approaches have modeled the ionosphere side by side. For the purpose of sensitivity comparison, the results from 2D and 3D UNB-IMT are compared in terms of post-fit residuals as well as time series of estimated vTEC in the single-station processing scenario. As discussed above, we use the GPS data from station FRDN only for October 16 and 25, 2011, in this subsection. The post-fit residuals are calculated as the difference between the measured and estimated biased sTEC.
FIGURE 4. The electron density profile produced by linear 3D UNB-IMT overhead FRDN at 12:00 (UT) on October 16 (doy 289) in 2011.
From the top to bottom panels, Figure 5 shows the estimated vTEC in the zenith direction over the station, post-fit residuals, estimated satellite and receiver DCBs, and unbiased sTEC with respect to local mean solar time series obtained with linear 2D (left-hand panels) and 3D (right-hand panels) UNB-IMT approaches respectively. We use a different color for each satellite to see individual improvement of satellites in terms of post-fit residuals, estimated DCB, and unbiased sTEC. As for the potential improvement of 3D UNB-IMT, we supposed, if the 2D model with single-shell assumption does not depict the variability of the ionosphere quite well (especially the vertical variability of the ionosphere), we should expect to see an improvement from the 3D model in terms of post-fit residuals. As seen in this figure, the 3D UNB-IMT improves the results in terms of post-fit residuals. The means and standard deviations of the residuals with the 2D and 3D UNB-IMT are shown in Table 1.
FIGURE 5. Sensitivity test (the panels from the top to the bottom correspond to: estimated vertical TEC, post-fit residuals, satellite and receiver DCB, slant TEC with respect to local time) between linear 2D (the left-hand panels) and 3D (the right-hand panels) models at FRDN on October 16 (doy 289) in 2011.TABLE 1. The means and standard deviations of the residuals under the quiet (Q, October 16, 2011) and disturbed or storm (S, October 25, 2011) ionospheric conditions with linear (L) and quadratic (Q) modeling approaches. Units = TECU.
The 3D UNB-IMT with three times as many parameters is allowed to “accommodate” more (vertical) variations of the ionosphere. The benefits are also manifest in the improvement of the estimated vTEC and estimated satellite and receiver DCBs. In terms of estimated vTEC, the smooth variation of TEC may be expected at mid-latitudes during quiet ionospheric conditions without any ionospheric anomaly. The unmodeled variation of TEC in 2D UNB-IMT seen in the post-fit residuals is also manifest as “artificial small jumps” in the vTEC panel. In other words, the 3D UNB-IMT is able to better represent the measurements from low-elevation-angle satellites owing to the EOFs replacing the mapping function. It is the typical case when a satellite comes into or goes out of view of the receiver. The estimated DCBs are relatively constant over the entire day. But it is also found from the estimated DCBs that the results from 2D UNB-IMT have slightly more variability. Both effects seem to be related to the unmodeled errors. The post-fit residuals in the 3D UNB-IMT are closer to the zero mean Gaussian distribution.
Then, we further evaluated the performance of 2D and 3D UNB-IMT under significantly disturbed conditions. Figure 6 shows the results with the same modeling strategies as demonstrated in Figure 5 but on October 25, 2011. Similar conclusions can be drawn from Figure 6, where better results in terms of post-fit residuals are obtained with 3D UNB-IMT (Table 1). In terms of estimated vTEC, the results from both strategies under the disturbed conditions look more irregular than those under the quiet conditions and deviate a little from the sine-wave-like daily variation. Some actual variation of the ionosphere during disturbed conditions may be captured and correctly illustrated as the bumps for both approaches. Furthermore, the unmodeled errors may also be explained as artificial small jumps/bumps in vTEC curves (revealed by the magnitude of post-fit residuals). It is seen that 3D linear UNB-IMT explains more variation of the ionosphere than 2D linear UNB-IMT. However, some residual unmodeled errors may still exist with the 3D model.
FIGURE 6. Sensitivity test (the panels from the top to the bottom correspond to: estimated vertical TEC, residuals, satellite and receiver DCB, slant TEC with respect to local time) between linear 2D (the left-hand panels) and 3D (the right-hand panels) models at FRDN on October 25 (doy 298) in 2011.
As concluded by other investigators, a higher order model could explain more spatial (non-linear) variations of the ionosphere, especially for geomagnetic storm conditions. The results with 2D and 3D quadratic UNB-IMT approaches are shown in Figure 7. In the post-fit residual panels, it can be seen that the residuals with 3D quadratic UNB-IMT are mostly within ±2 TECU except for several small spikes that happened between 0:00 and 4:00 local mean solar time and reflect that not all the electron density variations had been correctly represented by the model used. But it is clear that the 3D quadratic UNB-IMT can significantly improve the modeling precision compared to the 2D quadratic/linear UNB-IMT and 3D linear UNB-IMT. The magnitude of the post-fit residuals shown in this panel is even comparable with the results for the quiet condition shown in Figure 5. In terms of vTEC, a few spurious spikes are occasionally found when processing the data from the four stations with the 3D quadratic model and single-station processing strategy. Other data sources, such as data from incoherent backscatter measurements, may be needed to confirm if the spikes are caused by the instability of the model or actual ionospheric structures. Still, the vTEC curves with 3D quadratic UNB-IMT look smoother than 2D UNB-IMT. In terms of estimated DCBs, it is found that the results with 3D quadratic UNB-IMT approach exhibit relatively fewer perturbations than the other three approaches tested.
FIGURE 7. Sensitivity test (the panels from the top to the bottom correspond to: estimated vertical TEC, residuals, satellite and receiver DCB, slant TEC with respect to local time) between quadratic 2D (the left-hand panels) and 3D (the right-hand panels) models at FRDN on October 25 (doy 298) in 2011.
As we found for the 2D modeling approaches, the single thin-shell assumption with a fixed ionospheric shell height may introduce additional modeling errors. That is mainly because the layer with highest electron density (F2 layer) is not always located at a fixed height. Especially in disturbed ionospheric conditions, such as the case shown in Figures 6 and 7, the layer height would change significantly. Some methods have been proposed and tested with the help of more reliable “true” heights from other resources, such as ionosondes. However, due to the limited number of the instruments deployed and limited information provided (only information from overhead), the applications with these methods would have to be limited to the specific area covered by stations or networks equipped with the instruments. In addition, as to real-time application, the data processing time delay of ionosondes might be another technical issue these methods have to face. Compared with these methods, one benefit of the 3D UNB-IMT is its potential for real-time application for any size of network. Another benefit is its vertical modeling capability to depict vertical variation of electron density so the improved results would also be expected for disturbed ionospheric conditions. It is clearly seen from Figures 6 and 7 that the lowest vTECs around 4:00 LT reach down to 0 TECU with the 2D linear/quatratic UNB-IMT, which are considered as unphysical results. It is confirmed that small biases still exist in the results with the 2D model likely due to the improper shell height chosen (fixed at 350 km for the results shown in this article).
Multi-Station Experiment. When using the modeling scheme for a network solution, we will generally have two possible processing scenarios. One is processing the data of all the stations as a batch, and the other is processing station by station (or baseline by baseline).
The advantages and disadvantages of the batch process can be summarized as follows. It has more redundancies in the Kalman filter to estimate a more stable and reliable set of satellite and receiver DCBs. Due to more measurements as an input (state) of the Kalman filter, the convergence time would be shorter in terms of the estimated DCBs. It would be of benefit for real-time applications if we have limited a priori information about the estimated ionospheric parameters and/or DCBs. However, the batch solution seems to be less sensitive to localized information content than the station-by-station solution. The overall effect of the batch solution is smoothing over the network, reducing the size of some small perturbations. Theoretically, localized measurements should not have significant influence on the estimated state across an extended area or even the entire globe. In other words, the batch solution may be beneficial for relatively small local-area networks, but may not be ideally suited for networks as large as wide-area ones. Another straightforward disadvantage of the batch process is its relatively longer processing time, which might be a downside if it is used for real-time applications.
In the multi-station experiment, we tested the 3D UNB- IMT with a small regional network of four IGS reference stations (Figure 2) to investigate its performance with localized ionospheric variations. We performed tests with two scenarios: batch and station-by-station. Due to space restrictions, we cannot thoroughly report the results we obtained here. Please see the conference paper listed in Further Reading for the full details. Overall, the results we obtained in terms of post-processing residuals were similar to those in the single station experiment. We also found that the 3D UNB-IMT with EOFs seems to be able to better model the measurements with low elevation angles than the 2D UNB-IMT with a mapping function.
Comparing 3D UNB-IMT with SH Model. We have compared the results using the batch processing strategy with those from the SH model. The reason for this approach is that we intended to compare the results of the two processing strategies (UNB-IMT and SH) with identical conditions. That is, both methods processed the data using a batch scheme and estimated both ionospheric parameters and DCBs simultaneously, instead of using some other source or processed results. Therefore, in this case, we can compare the results side by side and evaluate the effectiveness of the estimated ionospheric parameters.
Based on the data from the network of the four stations, the sensitivity of the SH models is lower than that of 3D UNB-IMT, although the number of ionospheric parameters of the SH models is comparable or even larger than that of 3D UNB-IMT. In other words, the ionospheric parameters in 3D UNB-IMT to describe the variability of the ionosphere are more effective and meaningful to such a network scale than those in the 3D SH model.
Given the nature of its basis functions, the SH model is an excellent tool for global modeling, but it has some shortcomings for localized variability modeling. As to larger regional networks with longer baselines, such as those used for WAAS, which covers North America, the difference of the sensitivities between the batch and the station-by-station solutions should be larger than the results we have obtained. However, we cannot conclude that the sensitivity of 3D UNB-IMT is better than that of the 3D SH model with the batch processing strategy for such large regional networks before more tests are conducted. Still, it is clearly seen in our tests that the 3D SH model is not always ideal for regional networks in terms of sensitivity.
We reached similar conclusions for October 25, 2011, where the residuals spread more widely compared with quiet-condition residuals. In the storm conditions, the residuals of the quadratic 3D UNB-IMT spread relatively less than those of other modeling strategies. This is especially the case for the several hours at the beginning of the day, which corresponds to the peak of the Dst and Kp indices shown in Figure 3. The quadratic 3D UNB-IMT seems to have the capacity to handle the ionospheric spatial and temporal variation even during severe storm conditions.
FIGURE 3. Interplanetary magnetic field Bz component, Kp index, AE index, and Dst index during October 13–25 (doy 286–298) in 2011; nT = nanoteslas (Data from World Data Center for Geomagnetism, Kyoto and Goddard Space Flight Center Space Physics Data Facility).
Repeatability of Estimated DCBs. The DCBs not only have influence on the quality (accuracy) of the vTEC estimation, but their repeatability can also provide information to evaluate ionospheric models. This implies that the ionospheric models that have the capability to estimate/eliminate more accurate DCBs, independent of ionospheric variability, are preferable. We carried out a number of tests to evaluate the repeatability of estimated DCB values using the 2D and 3D UNB-IMT approaches as well as the 3D SH technique under both quiet and disturbed ionospheric conditions. For quiet ionospheric conditions, the performance of all the tested models looks comparable, although the quadratic 3D UNB-IMT performs slightly better than the others. As to the disturbed conditions, the quadratic 2D/3D UNB-IMT seems be able to provide more stable DCBs than the other models. However, the improvement of the extension from 2D to 3D is slight for the quadratic models, although it is significant for the linear models. The performance of the 3D SH model looks fairly poor compared to 3D UNB-IMT for regional modeling. Consult the conference paper for further details.
Conclusions and Future Research
In the work described in this article, we extended the UNB-IMT from 2D to 3D and compared the performance between them in station-by-station and batch processing scenarios for both quiet and storm ionospheric conditions. We used the data from a small regional network of dual-frequency GPS receivers. The DCBs and ionospheric delays were estimated at the same time by a Kalman filter. The newly developed approach was evaluated by analyzing the post-fit residuals, TEC of the state estimation process, and the repeatability of estimates of DCBs.
In the single-station processing, the improvement of 3D UNB-IMT has been demonstrated in both quiet and disturbed ionospheric conditions in terms of post-fit residuals. The 3D UNB-IMT with more parameters allows the depiction of more complex (vertical) variability of the ionosphere. The 3D UNB-IMT is able to better deal with the measurements from low-elevation-angle satellites owing to EOFs replacing the mapping function. The artificial jumps with 2D UNB-IMT when satellites come into or go out of view of the receiver have been properly handled by the 3D UNB-IMT. In addition, the time series of estimated DCBs with 3D UNB-IMT exhibit less perturbation than the results with 2D UNB-IMT.
As to the multi-station (network) processing, it is confirmed that the station-by-station solution is more sensitive to localized information than the batch solution. Based on the results from our research, station-by-station processing with 3D UNB-IMT is suggested to increase chances to catch localized ionospheric structures.
The repeatability of estimated DCBs was investigated as another indicator to evaluate the viability ofionospheric models.
Before the 3D UNB-IMT is tested in the positioning domain for single-frequency positioning, it is worth validating the model with other data sources. In addition, the potential benefits of 3D UNB-IMT during extremely disturbed ionospheric conditions is worth investigating further.
Acknowledgments
We would like to thank the IGS and the Crustal Dynamics Data Information System for providing the GPS data, and we acknowledge the financial contribution of the Natural Sciences and Engineering Research Council of Canada for supporting the first and last authors. This article is based on the paper “Eliminating Potential Errors Caused by the Thin Shell Assumption: An Extended 3D UNB Ionospheric Modelling Technique” presented at the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 16–20, 2013.
WEI ZHANG received his M.Sc. degree in space science in 2009 from the School of Earth and Space Science of Peking University, China. He is currently an M.Sc.E. student in the Department of Geodesy and Geomatics Engineering at University of New Brunswick (UNB) under the supervision of Dr. Richard B. Langley.
ATTILA KOMJATHY is a principal investigator at the California Institute of Technology Jet Propulsion Laboratory and an adjunct professor at UNB, specializing in remote sensing techniques using GPS. He received his Ph.D. from the Department of Geodesy and Geomatics Engineering of UNB in 1997.
SIMON BANVILLE works for the Geodetic Survey Division of Natural Resources Canada on real-time precise point positioning (PPP) using global navigation satellite systems. He is also in the process of completing his Ph.D. degree at UNB under the supervision of Dr. Langley.
FURTHER READING
• Authors’ Conference Paper
“Eliminating Potential Errors Caused by the Thin Shell Approximation: An Extended 3D UNB Ionospheric Modelling Technique” by W. Zhang, R.B. Langley, A. Komjathy, and S. Banville in Proceedings of ION GNSS+ 2013, the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 16–20, 2013, pp. 2447–2462.
• 2D Ionosphere Modeling
“SBAS Ionospheric Modeling with the Quadratic Approach: Reducing the Risks” by H. Rho, R. Langley, and A. Komjathy in Proceedings of ION GNSS 2005, the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, Long Beach, California, September 13–16, 2005, pp. 723–734.
“Improvement of a Global Ionospheric Model to Provide Ionospheric Range Error Corrections for Single-frequency GPS Users” by A. Komjathy and R. Langley in Proceedings of the 52nd Annual Meeting of The Institute of Navigation, Cambridge, Massachusetts, January 22–24, 1996, pp. 557–566.
• 3D (4D) Ionosphere Modeling
“Comparison of 4D Tomographic Mapping Versus Thin-shell Approximation for Ionospheric Delay Corrections for Single-frequency GPS Receivers over North America” by D.J. Allain and C.N. Mitchell in GPS Solutions, Vol. 14, No. 3, 2009, pp. 279–291, doi: 10.1007/s10291-009-0153-0.
“Regional 4-D modeling of the Ionospheric Electron Density” by M. Schmidt, D. Bilitza, C. Shum, and C. Zeilhofer in Advances in Space Research, Vol. 42, No. 4, 2008, pp. 782–790, doi: 10.1016/j.asr.2007.02.050.
“History, Current State, and Future Directions of Ionospheric Imaging” by G.S. Bust and C.N. Mitchell in Reviews of Geophysics, Vol. 46, No. 1, RG1003, March 2008, doi: 10.1029/2006RG000212.
“Development of the Global Assimilative Ionospheric Model” by C. Wang, G. Hajj, X. Pi, I.G. Rosen, and B. Wilson in Radio Science, Vol. 39, No. 1, RS1S06, February 2004, doi: 10.1029/2002RS002854.
Contributions to the 3D Ionospheric Sounding with GPS Data by M. García-Fernández, Ph.D. dissertation, Research Group of Astronomy and Geomatics, Universitat Politècnica de Catalunya, Barcelona, Spain, 2004. Available online in three parts:
“The NeQuick Model Genesis, Uses and Evolution” by S.M. Radicella in Annals of Geophysics, Vol. 52, No. 3/4, June/August 2009, pp. 417–422, doi: 10.4401/ag-4597.
“International Reference Ionosphere 2007: Improvements and New Parameters” by D. Bilitza and B. Reinisch in Advances in Space Research, Vol. 42, No. 4, 2008, pp. 599–609, doi: 10.1016/j.asr.2007.07.048.
“Empirical Orthogonal Functions and Related Techniques in Atmospheric Science: A Review” by A. Hannachi, I.T. Jolliffe, and D.B. Stephenson in International Journal of Climatology, Vol. 27, No. 9, July 2007, pp. 1119–1152, doi: 10.1002/joc.1499.
“Empirical Orthogonal Functions: The Medium is the Message” by A.H. Monahan, J.C. Fyfe, M.H.P. Ambaum, D.B. Stephenson, and G.R. North in Journal of Climate, Vol. 22, No. 24, December 2009, pp. 6501–6514, doi: 10.1175/2009JCLI3062.1.
A Manual for EOF and SVD Analyses of Climatic Data by H. Bjornsson and S. Venegas, Report No. 97-1, Department of Atmospheric and Oceanic Sciences and Centre for Climate and Global Change Research, McGill University, Montreal, February 1997.
In the wake of last month’s Expert Advice column on eLoran — “The Low Cost of Protecting America” by Dana Goward of the Resilient Navigation and Timing Foundation — come several positive comments and encouraging developments. Rather than rehearse all the arguments why we should care about this, I’ll repeat the one word that I heard most often in GNSS circles in 2013: jamming. Followed closely by: spoofing.
“I have been advocating strongly for reconsideration of the government’s domestic Loran decision for the last year or so,” writes one reader positioned on Washington’s Beltway, “and specifically working within the Department of Defense (DoD) to ensure it is aware of international developments for eLoran in the UK and South Korea, and the possibilities inherent in other former Loran chains.
“The DoD is beginning to recognize the value of eLoran as a complement to GPS, not only for international missions, but in cooperation with the departments of Transportation and Homeland Security for domestic critical infrastructure.”
Last fall, Don Jewell’s Defense PNT newsletter on the same subject drew this reply from another well-known expert:
“One of the key short-term actions is to prevent the decommissioned [Loran] sites from being sold off for subdivisions. These sites are a national treasure with unique properties: soil conductivity, water content, metal content, and more that are hugely important in siting low-frequency positioning systems. Those long-gone engineers of the 1940s and ’50s knew this and chose accordingly.”
Before last month’s issue appeared but after it had gone to press, President Obama signed the National Defense Authorization Act (NDAA) for 2014. It contained several favorable New Year’s auguries for positioners, navigators, and timers.The act evinced an acute awareness of the vulnerability of space systems to disruption. The act is also a law governing the land. Through it Congress requires the administration to, among other things, explain biennially in its “Space Protection Strategy” report exactly how, in the event space systems are disrupted, DOD and the intelligence community “plan to provide necessary national security capabilities through alternative space, airborne, or ground systems.”
Since said administration acted early in its first term to decommission Loran-C, the congressional directive is pointed.
The next big thing coming up on the GNSS international horizon takes place in Rotterdam, the Netherlands, April 15–17: the European Navigation Conference, ENC-GNSS 2014. It includes a track session on “eLoran and other Low-Frequency Systems,” and I’ll be there with pencil sharpened.
Brad Parkinson will give the ENC keynote, and he is on record as one of an august group of Institute for Defense Analyses experts who unanimously recommended that the existing Loran-C be greatly updated and modernized to eLoran. We should hear more from him on this subject amid the wharves, waterways, and docks of Europe’s largest port (world’s third busiest).
There’s barely room left to report the successful tests of Enhanced Differential Loran (eDLoran) by Dutch specialists Reelektronika: absolute accuracy of 5 meters in the North Sea and in the Rotterdam Europort harbor area.
Figure 1. Overall system architecture for MUSTER: Multi-platform signal and trajectory estimation receiver.
More Receiver Nodes Bring Ubiquitous Navigation Closer
Encouraging results from new indoor tests and advances in collaborative phased arrays come from MUSTER: multiple independently operating GPS receivers that exchange their signal and measurement data to enhance GNSS navigation in degraded signal environments, such as urban canyons and indoors.
By Andrey Soloviev and Jeffrey Dickman
Bringing GNSS navigation further indoors by adding new users to a collaborative network can help realize the concept of ubiquitous navigation. Increasing the number of receiver nodes to improve signal-to-noise ratios and positioning accuracy lies at the heart of the MUlti-platform Signal and Trajectory Estimation Receiver (MUSTER). This article focuses on benefits of integrating multi-node receiver data at the level of signal processing, considering two case studies:
Collaborative GNSS signal processing for recovery of attenuated signals, and
Use of multi-node antenna arrays for interference mitigation.
MUSTER organizes individual receiver nodes into a collaborative network to enable:
Integration at the signal processing level, including:
Multi-platform signal tracking for processing of attenuated satellite signals;
Multi-platform phased arrays for interference suppression;
Integration at the measurement level, including:
Joint estimation of the receiver trajectory states (position, velocity and time); and,
Multi-platform integrity monitoring via identification and exclusion of measurement failures.
To exclude a single point of failure, the receiver network is implemented in a decentralized fashion. Each receiver obtains GNSS signals and signal measurements (code phase, Doppler shift and carrier phase) from other receivers via a communication link and uses these data to operate in a MUSTER mode (that is, to implement a multi-platform signal fusion and navigation solution). At the same time, each receiver supplies other receivers in the network with its signal and measurement data. Figure 1 illustrates the overall system architecture.
Open-loop tracking is the key technological enabler for multi-node signal processing. Particularly, MUSTER extends an open-loop tracking concept that has been previously researched for single receivers to networked GNSS receivers. Signals from multiple platforms are combined to construct a joint 3D signal image (signal energy versus code phase and Doppler shift). Signal parameters (code phase, Doppler shift, carrier phase) are then estimated directly from this image and without employing tracking loops.
Open-loop tracking is directly applied to accommodate limitations of military and civilian data links. To support the functionality of the receiver network at the signal processing level (that is, to enable multi-platform signal tracking and multi-platform phased arrays) while satisfying bandwidth limitations of existing data link standards, individual receivers exchange pre-correlated signal functions rather than exchanging raw signal samples.
Before sending its data to others, each receiver processes the incoming satellite signal with a pre-processing engine. This engine accumulates a complex amplitude of the GNSS signal as a function of code phase and Doppler frequency shift. Receivers then broadcast portions of their pre-correlated signal images that are represented as a complex signal amplitude over the code/Doppler correlation space for 1-ms or 20-ms signal accumulation. For broadcasting, portions of signal images are selected around expected energy peaks whose locations are derived from some initial navigation and clock knowledge.
This approach is scalable for the increased number of networked receivers and/or increased sampling rate of the ranging code (such as P(Y)-code vs. CA-code). The link bandwidth is accommodated by tightening the uncertainty in the location of the energy peak. As a result, the choice of the data link becomes a trade-off between the number of collaborative receivers and MUSTER cold-start capabilities (that is, maximum initial uncertainties in the navigation and clock solution).
Multi-Node Signal Accumulation
An earlier paper that we presented at the ION International Technical Meeting, January 2013, describes the approach of multi-platform signal accumulation for those cases where relative multi-node navigation and clock states are partially known. This section reviews that approach and then extends it to cases of completely unknown relative navigation and clock states. The following assumptions were previously used:
Relative position between networked receivers is known only within 100 meters;
Relative receivers’ velocity is known within 2 meters/second;
Relative clock states are calibrated with the accuracy of 100 nanoseconds (ns) or, equivalently, 30 meters.
These assumptions are generally suitable for a pedestrian type of receiver network (such as a group of cellular phone users in a shopping mall area) where individual nodes stay within 100 meters from each other; their relative velocities do not differ by more than 2 meters/second; and, the clocks can be pre-calibrated using communication signals. In this case, zero relative states are used for the multi-node signal accumulation and subsequent tracking. Figure 2 summarizes the corresponding MUSTER tracking architecture.
Figure 2. Multi-platform tracking architecture for approximately known relative navigation states.
Relative navigation states are initialized based on clock calibration results only: zero relative position and velocity are assumed. These initial states are then propagated over time, based on MUSTER/supplemental tracking results (Doppler frequency estimates and higher-order Doppler terms). Code and frequency tracking states are computed by combining biased and unbiased measurements. Biased measurements are obtained by adjusting supplemental signal images for approximately known relative states only. Unbiased measurements are enabled by relative range/Doppler correction algorithms that estimates range and frequency adjustments for each supplemental receiver.
The Kalman filter that supports the optimal combination of biased and unbiased tracking measurements also includes code-carrier smoothing to mitigate noise in measured code phase. For those cases where multi-platform signals are combined coherently, a standard carrier-smoothing approach is used. When non-coherent signal combinations are applied, a so-called pseudo-carrier phase is first derived by integrating Doppler estimates over time and then applied to smooth the code phase.
Multi-platform signal accumulation and tracking can be extended to include cases where the relative navigation parameters are completely unknown. For such cases, MUSTER implements an adjustment search to find the values of code phase and Doppler shift for each supplemental receiver that maximize the overall signal energy.
Adjustment search must be implemented if MUSTER/supplemental relative states are completely unknown, or if their accuracy is insufficient to enable direct accumulation of multi-platform energy, for example, when the relative range accuracy is worse than 150 meters and an energy loss of at least 3 dB is introduced to the signal accumulation process. For each code phase, Doppler and carrier phase (if coherent integration is performed) from the adjustment search space, a supplemental 1-ms function is adjusted accordingly and then added to the MUSTER function. Multiple 3D GPS signal images are constructed, and the image with the maximum accumulated energy is applied to initialize relative navigation parameters: code phase and Doppler shift adjustments values from the adjustment search space that correspond to the energy peak serve as approximate estimates of relative range and Doppler.
The accuracy of these estimates is defined by the resolution of the adjustment search, which would be generally kept quite coarse in order to minimize the search space. For instance, a 300-meter search grid is currently implemented for the code phase, which enables the resolution of relative ranges within 150 meters only. Hence, to mitigate the influence of relative state uncertainties on the tracking quality, a correction algorithm is applied as described in our earlier paper. Figure 3 shows the overall system architecture.
Figure 3. MUSTER signal-tracking approach for cases of unknown relative states.
The architecture keeps all the previously developed system components and adds the adjustment search capability (red block in Figure 3) to incorporate cases of unknown MUSTER/supplemental receivers’ relative navigation states. To minimize the computational load, adjustment search is performed only for the first tracking epoch. Search results are applied to initialize the estimates of MUSTER/supplemental range and Doppler, which are then refined at each subsequent measurement epoch using a combined biased/noisy tracking scheme.
The updated architecture can support cases of completely unknown relative states, as well as those cases where relative states are coarsely known, but this knowledge is insufficient to directly combine multi-platform signals.
The complete adjustment search is possible. However, it is extremely challenging for actual implementations due to both large computational load and a data exchange rate associated with it. To exemplify, NcodexNDoppler versions of the multi-platform 3D function have to be computed for the case where Ncode code phase and NDoppler Doppler shift adjustment search bins are used and outputs from two receivers are combined non-coherently. A complete search (1023 code bins and 11 frequency bins) requires computation of 11,253 3D functions. This number increases to (11,253)2 or 126,630,009 if the third receiver is added.
In addition, receivers must exchange their complete pre-correlated signal functions, which puts a considerable burden on the computational data link. For instance, the exchange of complete 1-ms functions with the 4-bit resolution of samples (required to track the carrier phase) results in the 45 Mbit/s data rate for only a 2-receiver network. Hence, it is anticipated that for practical scenarios, a reduced adjustment search will be utilized for cases where the accuracy of relative states does not support the direct accumulation of multi-platform signals: for example, when the distance between users in the network exceeds 150 meters. In this case, only segments of 1-ms functions around expected energy peaks (estimated based on approximate navigation knowledge) are exchanged.
Phased Arrays
Multi-platform phased arrays have been developed to enable interference and jamming protection for GNSS network users who cannot afford a controlled reception pattern antenna (CRPA) due to size, weight, and power (SWAP), as well as cost constraints. The multi-node phased array approach presented here cannot match the performance of CRPA, with its careful design, antenna calibration, and precise knowledge of relative location of phase centers of individual elements. However, it can still offer a significant interference protection to networked GNSS users.
The multi-platform phased array implements a cascaded space-time adaptive processing (STAP) as illustrated in Figure 4.
Figure 4. Implementation of multi-platform phased array with cascaded space-time adaptive processing.
Cascaded STAP implements temporal filtering at a pre-correlation stage, while spatial filtering (in a form of the digital beam forming or DBF) is carried out at post-correlation. Cascaded STAP is implemented instead of joint STAP formulation to
remove the need to exchange raw signal samples (which is necessary when DBF is applied at pre-correlation); and,
support a novel DBF approach that does not require precise (that is, sub-centimeter to centimeter-level) knowledge of relative position and clock states between network nodes (described later).
Signal samples are still exchanged for the estimation of signal covariance matrices that are required for the computation of temporal and spatial weights. However, the sample exchange rate is reduced significantly as compared to the joint STAP: for example, only 100 samples are currently being exchanged out of the total of 5000 samples over a 1-ms signal accumulation interval.
The DBF uses the Minimum Variance Distortion-less Response (MVDR) formulation for the computation of spatial weight vector. MVDR constrains power minimization by the undisturbed signal reception in the satellite’s direction: (1)
where Φ is the multi-node signal covariance matrix that is computed based on temporal filter outputs; superscript H denotes the transpose and complex conjugate operation; and, η is the steering vector that compensates for phase differences between array elements for the signal coming from the satellite’s direction: (2)
In (2), u is the receiver-to-satellite line-of-sight (LOS) unit vector; rm is the relative position vector between phase centers of the mth node and MUSTER; (,) is the vector dot product; and, λ is the carrier wavelength.
Following computation of DBF weight, multi-node 1-ms GPS signal functions are combined: (4)
where is the complex 1-ms accumulated signal amplitude of the mth node for the (l,p) bin of the code/carrier open-loop tracking search space. The result is further accumulated (for example, over 20 ms) and then applied for the open-loop estimation of signal parameters.
One of the most challenging requirements of the classical MVDR-based DBF is the necessity to estimate relative multi-node position and clock states at a centimeter level of accuracy. To eliminate this requirement and extend potential applications of multi-node phased arrays, the DBF was modified as illustrated in Figure 5.
Figure 5. Modified DBF for a multi-node phased array with unknown relative navigation states.
The modified approach searches through phase adjustments to supplemental receivers and chooses the adjustment combination that maximizes the output carrier-to-noise ratio (C/N0). As a result, no knowledge of the relative navigation states is needed. For each phase combination, , from the adjustment search space, the satellite lookup constraint is computed as:
(5)
Due to the cyclic nature of the phase, the search space is limited to the [0,2π] region. The search grid resolution of π/2 is currently being used.
The obvious drawback of the exhaustive search-based DBF is that the approach is not scalable for the increased number of network users. However, it can still be efficiently applied to a relatively limited network size such as, for example, five collaborative receivers. In addition, the method does not generally support interference suppression with carrier-phase fidelity. However, code and Doppler frequency tracking statuses are still maintained as it is demonstrated in the next section using experimental results.
Experimental Results
We used two types of experimental setups as shown in Figures 6 and 7, respectively.
The first setup (Figure 6) was used to demonstrate multi-platform signal accumulation with unknown relative states and multi-node phased arrays. Raw GPS signals received by three antennas were acquired by a multi-channel radio-frequency (RF) front-end and recorded by the data collection server. The first antenna served as the MUSTER platform, the second and third antennas were used as supplemental platforms. Relative antenna locations were measured as [-0.00; 0.99; 0.05] m (East, North, Up components) for the MUSTER/supplemental receiver 1; and, [0.16; 0.76; 0.27] m for the MUSTER/supplemental receiver 2.
Figure 6. Test setup 1 applied for multi-platform signal accumulation with unknown relative states and multi-platform phased arrays.
A stationary test scenario was considered. Clock biases were artificially induced to emulate a case of asynchronous network. Clock biases were introduced by converting raw GPS signal samples into the frequency domain (applying a fast Fourier transform (FFT) to 1-ms batches of signal samples); implementing a frequency-domain timing shift; and, converting shifted signals back into the time domain (via inverse FFTs). Multi-platform signal processing algorithms were then applied to raw GPS signals with asynchronous multi-platform clocks.
The second setup (Figure 7) was applied for the demonstration of indoor signal tracking. Two receiver nodes (roof and cart) with independent front-ends were used. The roof node remained stationary, while the cart was moved indoors. Each node in the data collection setup includes a pinwheel GPS antenna, an RF front-end, an external clock for the front-end stabilization, and a data collection computer. Figure 7 illustrates corresponding test equipment for the cart node.
Figure 7. Test setup 2 used for indoor signal tracking.
Multi-Platform Signal Tracking with Unknown Relative States. Two platforms were used to demonstrate the case of completely unknown states (antennas 1 and 3 in Figure 6). The third platform was not used due to the extreme computational burden of the complete adjustment search (about 106 grid points for the case of three platforms). A 0.2-ms (60 km) clock bias was added to GPS signal samples recorded by antenna 3. Complete adjustment search was implemented for the code phase. No adjustment search was needed for the Doppler shift. The use of adjustment search provides approximate estimates of relative shifts in multi-platform code phases. These approximate estimates are then refined using a relative range estimation algorithm. Figures 8 and 9 exemplify experimental results for cases of coherent (C/N0 is 31 dB-Hz) and non-coherent (C/N0 is 29 dB-Hz) multi-platform signal accumulation.
Consistent code- and carrier-phase tracking is maintained for the coherent accumulation case.
Carrier-phase and code-phase error sigmas were estimated as 8.2 mm and 28.8 meters, accordingly. The carrier-smoothed code tracking error varies in the range from –4 to –2 meters for the steady-state region. For the non-coherent tracking case, errors in the carrier smoothed code measurements stay at a level of –5 meters. These example test results validate MUSTER tracking capabilities for the case of completely unknown relative navigation states.
Indoor Signal Processing
The indoor test was performed to demonstrate the ability of MUSTER to maintain signal tracking status under extreme signal attenuation conditions. The test was carried out at the Northrop Grumman campus in Woodland Hills, California, with no window view for the entire indoor segment; all the received GPS signals were attenuated by the building structure. Raw GPS signal data was collected from the test setup shown in Figure 6 and then post-processed with multi-platform signal accumulation algorithm with partially known relative navigation states. A combined 20-ms coherent/0.2-s non-coherent signal accumulation scheme was applied. A complete position solution was derived from five highest-elevation satellites.
As the results for the indoor test show in Figure 10, MUSTER supports indoor positioning capabilities for the entire test trajectory. The GPS-only indoor solution reconstructs the right trajectory shape and size. Solution discontinuities are still present. However, the level of positioning errors (20 meters is the maximum estimated error) is lowered significantly as compared to traditional single-node high-sensitivity GPS implementations where errors at a level of hundreds of meters are commonly observed. This accuracy of the multi-node solution can be improved further when it is integrated with other sensors such as MEMS inertial and vision-aided navigation.
Figure 10. Indoor test results.
Multi-Platform Phased Arrays
For the functionality demonstration of multi-platform phased arrays, live GPS signal samples were collected with the test setup shown in Figure 6. Interference sources were then injected in software including continuous wave (CW) and matched spectrum interfering signals. The resultant data were post-processed with the multi-platform phased array approach described above. Relative navigation and clock states were unknown; the DBF formulation was augmented with the phase adjustment search.
Figures 11 and 12 exemplify experimental results.
Figure 11. Example performance of the multi-platform phased array: PRN 31 tracking results; jamming-to-signal Ratio of 50 dB was implemented for all interference sources.Figure 12. PRN 14 tracking results; jamming-to-signal ratio of 55 dB implemented for all interference sources.
Test results presented demonstrate consistent GPS signal tracking for jamming-to-signal (J/S) ratios from 50 to 55 dB. The steady-state error in the carrier-smoothed code is limited to 5 meters.
Acknowledgment
This work was funded, in part, by the Air Force Small Business Innovation Research (SBIR) grant, Phase 1 and Phase 2, topic number AF103-185, program manager Dr. Eric Vinande.
Andrey Soloviev is a principal at Qunav. Previously he served as a Research Faculty at the University of Florida and as a Senior Research Engineer at the Ohio University Avionics Engineering Center. He holds B.S. and M.S. degrees in applied mathematics and physics from Moscow Institute of Physics and Technology and a Ph.D. in electrical engineering from Ohio University.
Jeff Dickman is a research scientist with Northrop Grumman Advanced Concepts and Technologies Division. His area of expertise includes GPS baseband processing, integrated navigation systems, and sensor stabilization. He holds a Ph.D. in electrical engineering from Ohio University. He has developed high-accuracy sensor stabilization technology and is experienced with GPS interferometry for position and velocity aiding as well as high-sensitivity GPS processing techniques for challenging GPS signal conditions.
The Institute of Navigation (ION) presented its Annual Awards during the ION International Technical Meeting (ITM) 2014 in San Diego, California, January 27-29.
ION also announced the recipients of the 2014 fellow memberships.
Awards
The ION Annual Awards Program is sponsored by The Institute of Navigation to recognize individuals making significant contributions or demonstrating outstanding performance relating to the art and science of navigation.
Dr. Jacques Georgy received the Early Achievement Award for contributions to portable and indoor navigation using MEMS inertial sensors on consumer devices. The Early Achievement Award is presented in recognition of outstanding contributions made early in one’s career.
Captain Alexander Dufault received the Superior Achievement Award for his dedication as MC-130P Navigator in developing and executing new techniques, increasing the full range employment and navigation prevision of the MC-130P Combat Shadow. The Superior Achievement Award is presented to an individual demonstrating outstanding accomplishments as a practicing navigator.
Dr. Young Chang Lee received the Dr. Samuel M. Burka Award for his paper “New Advanced RAIM with Improved Availability for Detecting Constellation Wide Faults, Using Two Independent Constellations” published in the Spring 2013 issue of NAVIGATION, Journal of The Institute of Navigation, Vol. 60, No. 1, pp. 71-83. The Dr. Samuel M. Burka Award recognizes outstanding achievement in the preparation of a paper contributing to the advancement of the art and science of positioning, navigation and timing.
Dr. Mikel Miller received the Captain P. V. H. Weems Award for his contributions to the management and encouragement of advanced navigation research and for his service to The Institute of Navigation. The Captain P. V. H. Weems Award is presented to individuals for continuing contributions to the art and science of navigation.
Dr. Mark Psiaki received the Tycho Brahe Award For exceptional contributions to the theory and practice of spacecraft attitude and orbit determination and to the advancement of GNSS algorithms for satellite navigation. The Tycho Brahe Award is given in memory of Mary Tornich Janislawski, developer of the Mark II Plotter, a charter member of The Institute of Navigation, the first woman to have received an ION Annual Award, a civilian aviation instructor, a teacher at the University of California at Berkeley and Stanford and a respected author. This award has been generously endowed by Col. Leonard Sugerman (USAF, Ret.), a past president of The Institute of Navigation (1970–1971).
Dr. Yu (Jande) Morton received the Thomas L. Thurlow Award for significant contributions to the understanding of ionospheric effects on navigation satellite signals, development of several innovative signal processing algorithms and dedication to navigation education. The Thomas L. Thurlow Award recognizes outstanding contributions to the science of navigation.
Mr. Ronald Braff received the Distinguished Service Award in recognition of more than 24 years of service to NAVIGATION, The Journal of The Institute of Navigation. The Distinguished Service Award is presented for extraordinary service to The Institute of Navigation.
A special recognition was given to the GPS III SLR Implementation Team in grateful recognition for the multi-year effort to make the implementation of laser retro-reflector on GPS III a reality and enhance its performance and interoperability for generations to come. GPS SLR Implementation Team Members included Adde, Barbara, Ballenger, Allan, Col (Ret.), Bar-Sever, Yoaz, Dr., Beard, Ronald L., Bolden, Charles Jr., Honorable, Buckman, David, Col (Ret.), Carter, David, Davis, Mark, Dobson, Craig, Freilich, Michael, Dr., Garver, Lori, Honorable, Gruber, Bernard, Col (Ret.), Hothem, Larry, Hudnut, Kenneth, Dr., Johnson, Thomas, Dr., Kaye, Jack, Kehler, Robert, Gen, Koch, Janelle, Maj, LaBrecque, John L., Dr., Lewis, Kirk, Long, Letitia, Madden, David, Col (Ret.), Malys, Stephen, Merkowitz, Stephen, Dr. Miller, James J., Moreau, Michael, Dr., Oria, A.J., Dr., Pace, Scott, Dr., Pavlis, Erricos, Dr., Pearlman, Michael, Dr., Puhek, James, Col, Rosenberg, Robert, Maj Gen (Ret.), Scolese, Christopher Shelton, William, Gen, Skalski, Hank, Slater, James, Standley, Vaughn, Dr., Thomas, Linda, Dr. Weinberg, Norm, Wetzel, Scott, Whelan, Martin, Maj Gen, Yelle, Ray, Younes, Badri, National Space-Based PNT Advisory Board co-chaired by: Dr. James Schlesinger and Dr. Bradford Parkinson.
Fellow Membership
Election to fellow membership recognizes the distinguished contributions of The Institute of Navigation members to the advancement of the technology, management, practice and teaching the arts and science of navigation; and/or for lifetime contributions to the Institute.
Dr. Mark Psiaki has been elected for contributions to GNSS signal processing, software receivers, ionospheric scintillation modeling, and for satellite orbit and attitude determination.
Mr. Logan Scott has been elected for contributions to GNSS signal processing, anti-jam antennas, anti-spoofing measures, and crowd sourcing to locate jammers.
Prof. Peter Teunissen has been elected for invention of the LAMBDA method, the current standard for integer ambiguity resolution in GNSS carrier phase measurements, and for reliability theory of integer estimation.
Sokkia Corporation is offering enhanced abilities and versatility to its DX series of total stations with the introduction of the DX-200 in the North American market.
When configured for hybrid positioning, the DX-200 has the ability to use both GNSS positioning and optical positioning data simultaneously. The standard Sokkia Hybrid Robotic System includes the DX, GRX2 GNSS receiver and MESA large-screen tablet controller.
“The DX-200 is ideal for the professional looking for a mid-range, auto-pointing total station that can become a full-robotic instrument with a simple firmware upgrade,” said Ray Kerwin, director of global surveying products. “Advanced functionality such as hybrid positioning can be added to the robotic unit, making the DX-200 a versatile system for multiple applications.”
The DX-200 can be used with the RC-PR5 remote controller for increased Bluetooth wireless operating range. “The remote allows for rapid prism search and lock up to 2,000 feet (600 meters) away,” Kerwin said.
“Hybrid positioning adds a new dimension of versatility,” Kerwin said. “When line-of-sight is blocked, for example, shots can be measured with the GNSS receiver, and the receiver can also be used for quick lock functionality.”
Standard additional features of the DX series include Direct Aiming auto-collimation technology, TSshield security and maintenance technology, MAGNET integrated software onboard and Sokkia’s patented RED-tech reflectorless measurement system.
The DX-200 is available in 1, 3 and 5 arc second accuracy models.
