Lockheed Martin has received a $172 million contract from the U.S. Navy and Air Force for Long Range Anti-Ship Missile (LRASM) production. The LRASM is designed to reduce dependence on GPS.
The contract continues the production for the air-launched variant of LRASM, including a full production run of missiles and engineering support. This is the second of several expected annual production lots that will deliver next-generation anti-ship missiles to the U.S. Navy and U.S. Air Force.
LRASM is designed to detect and destroy specific targets within groups of ships by employing advanced technologies that reduce dependence on intelligence, surveillance and reconnaissance platforms, network links and GPS navigation in electronic warfare environments.
LRASM will play a significant role in ensuring military access to operate in open ocean/blue waters, owing to its enhanced ability to discriminate and conduct tactical engagements from extended ranges.
LRASM is a precision-guided, anti-ship standoff missile based on the successful Joint Air-to-Surface Standoff Missile – Extended Range (JASSM-ER). It is designed to meet the needs of U.S. Navy and U.S. Air Force Warfighters in contested environments.
The air-launched variant provides an early operational capability for the U.S. Navy’s offensive anti-surface warfare Increment I requirement. With the recent EOC declaration by the U.S. Air Force for the B-1B, the focus is now on the U.S. Navy’s F/A-18E/F Super Hornet in 2019.
“LRASM brings a game-changing capability to both the U.S. Air Force and the Navy,” said David Helsel, LRASM director at Lockheed Martin Missiles and Fire Control. “This second production lot will provide anti-ship missiles for both the B-1B and F/A-18E/F, bringing sea control back to our warfighters.”
Features include enhanced ADS-B, SBAS and georeferenced charts.
Collins Aerospace’s Pro Line Fusion avionics upgrade for Pro Line 4-equipped Bombardier Challenger 604 series aircraft has been certified by the U.S. Federal Aviation Administration (FAA).
Working closely with Bombardier as the original aircraft manufacturer and Nextant Aerospace as the installation design certification lead, this sole all-in-one solution complies with pending mandates while modernizing the flight experience for pilots.
The Pro Line Fusion upgrade enhances the operational capabilities of the Challenger 604 aircraft to a similar level as that of the Challenger 605 and Challenger 650 jets equipped with Collins Pro Line 21 Advanced, while providing Challenger 604 operators with a solution to meet future regulatory requirements.
Among these enhancements, the upgrade replaces the factory-installed CRT displays with three 14.1-inch widescreen LCD displays with configurable windows. Features designed to improve situational awareness and reduce pilot workload for Bombardier Challenger 604 aircraft owners include:
A fully loaded package of baseline equipment for operation in modernizing global airspace — beyond ADS-B mandate compliance, offering SBAS-capable GNSS, localizer performance with vertical guidance (LPV) approaches, radius-to-fix (RF) legs and more
Geo-referenced electronic navigation charts that display own-ship aircraft position
The Challenger 604 Pro Line Fusion retrofit solution, which is already available for several Beechcraft King Air and Cessna Citation CJ aircraft, is part of our ongoing effort to provide owners with modern technology, enhanced situational awareness and compliance with airspace mandates,” said Christophe Blanc, vice president and general manager, business and regional systems for Collins Aerospace. “The Challenger 604 business jet is a highly-valued, long-haul aircraft that will be able to continue flying well into the future with this upgrade.”
The upgrade is available exclusively throughout Bombardier’s extensive network of service centers and Nextant Aerospace.
Allystar Technology Co. Ltd. has launched a multi-band, multi-GNSS system on chip, the HD8040 series, to help portable devices save size and weight. The HD8040 offered in wafer-level chip-scale packaging (WLCSP).
The HD8040 series of chipsets fully supports all civil signals on the L5 band, said Shi Xian Yang, Allystar high-precision product manager at Allystar. Besides GPS, other constellations with L1/L5 signals include Galileo, BeiDou, the Indian NavIC system and Japanese QZSS.
Besides L1 band, HD8040D supports L5/B2a/E5a signals, which are expected to have lower noise and be better in multipath mitigation mainly due to the higher chipping rate of L5 signals relative to L1 C/A code.
HD8041D supports IRNSS (NavIC), which makes it suitable for navigation in urban areas in India and the Middle East, where seven NavIC satellites have a higher elevation than both GPS and Galileo satellites. This means IRNSS (NavIC) would provide greater accuracy, precision and available measurements.
With the features of small size (3 x 3 millimeters) and low power consumption, the HD8040 series is suitable for smartphones, tablets and other portable devices.
The architecture integrates floating-point arithmetic units based on ARM CortexM4, 160 KB RAM, 32 KB backup RAM with VBAT, and 384 KB embedded Flash memory. Besides basic peripheral interfaces UART, I2C, SPI and GPIO, it supports the CAN interface for automotive applications, too.
Customer samples of the HD8040D and HD8041D are available now.
Tersus GNSS Inc. has released the Tersus GeoCaster, a Networked Transport of RTCM via Internet Protocol (NTRIP) caster software. The software expands the company’s product line and provides users with better and more comprehensive services.
The Tersus NTRIP caster software is designed to allow GNSS correction data such as RTCM corrections to be repeated and sent to different end users via the internet.
Screenshot: Tersus GNSS
“GeoCaster has a user-friendly interface, and it not only supports multiple bases online simultaneously but also supports multiple rovers for one base,” said Xiaohua Wen, founder and CEO of Tersus GNSS Inc. “Our users can have a real-time review of detailed statistics and can modify user-defined permissions manually.”
Tersus GeoCaster supports configurable bases online simultaneously and configurable rovers for one base. GeoCaster supports NTRIP protocol and operates continuously.
The software is designed for end users involved in applications such as surveying, construction engineering, deformation monitoring, automated vehicle, precision agriculture, unmanned aerial vehicle, machine control and robotics.
This is the first release of GeoCaster. Version 2.0, targeted at the first quarter of 2019, is expected to offer higher accuracy and longer baseline applications.
Bell Helicopter unveiled a full-scale vertical-takeoff-and-landing (VTOL) air taxi vehicle during CES 2019, held in Las Vegas.
The air taxi, named Bell Nexus, is powered by a hybrid-electric propulsion system and features Bell’s signature powered lift concept incorporating six tilting ducted fans designed to safely and efficiently carry passengers.
Bell Nexus means the nexus of transport and technology and of comfort and convenience. Nexus captures the long-sought-after vision of quick air travel with a unique in-flight experience, keeping passengers connected to their lives and saving valuable time.
The Nexus team consists of Bell, Safran, EPS, Thales, Moog and Garmin, who are collaborating on Bell’s VTOL aircraft and on-demand mobility solutions. Bell is leading the design, development and production of the VTOL systems; Safran is providing the hybrid propulsion and drive systems; EPS is providing the energy storage systems; Thales is providing the Flight Control Computer (FCC) hardware and software; Moog is developing the flight control actuation systems; and Garmin is integrating the avionics and the vehicle management computer (VMC).
Autonomous Pod Transport (APT). Alongside the debut of Bell Nexus, Bell will feature the Autonomous Pod Transport (APT). The APT family varies in payload capability that can serve many mission sets such as medical, law enforcement, offshore missions and on-demand delivery services. Bell is expanding into a new industry to show the full spectrum of our capabilities and the real-world challenges APT will address, Bell said in a press release.
Future Flight Controls. Bell’s Future Flight Controls simulator was a new experience for CES participants this year. Bell is actively collecting data to help shape the future flight controls of aviation. Data from the simulators will be used to determine what actions and interfaces are intuitive to the average potential operator and what prior experiences and abilities contribute to these opinions.
Urban air travel is coming closer to the masses through recent advancements in technology and software. The critical last step is designing a flight-control ecosystem that allows individuals to safely and efficiently operate urban air vehicles.
In 2018, Bell provided the world a glimpse into the air-taxi passenger experience, and this year, attendees could see the full vision.
Mountainous areas present special problems for surveyors, overcome by the expanded availability of multi-GNSS. (Photo: Trimble)
Today’s GNSS satellites transmit on three or more carrier frequencies. The quality of the data in these signals from GPS, BeiDou, Galileo, GLONASS and QZSS reveals the expected measurement precisions. This article explores the noise of the range residual and ionospheric residual to indicate the oncoming capabilities.
Today, four GNSSs transmit various codes on various carrier frequencies: the USA’s GPS, Russia’s GLONASS, Europe’s Galileo and China’s BeiDou. Most of the carrier phase and pseudorange data are available using civilian GNSS receivers. Improvements in signal quality as well as reliability of the satellites are foreseen through the generations, as well as the introduction of new signals, such as L1C, L2C, L5 carrier and codes, and M-codes, on top of the existing L1-C/A code and the P(Y) code on both L1 and L2. Improvements are also seen in boosting the transmitting power.
This article investigates the use of two approaches to analyze the relative noise in the various carrier phase and pseudorange observable for GPS, BeiDou, Galileo, GLONASS and Japan’s Quasi-Zenith Satellite System (QZSS) augmentation. Two approaches analyze the relative noise in the observables: the range residual and the ionospheric residual. Both techniques can also be used to detect cycle slips.
Range Residual
UAV survey operations benefit from multi-GNSS receivers. (Photo: Septentrio)
The range residual is simply the change from one epoch to the next in the difference in the range calculated using the pseudorange and the range calculated by the carrier phase on a specific frequency. The pseudorange values are scaled using the wavelength to an equivalent range in units of the carrier’s cycles rather than meters. Equation 1 illustrates the range residual between the pseudorange ρ on a specific carrier frequency and the carrier phase observable φ, using the wavelength λ of the carrier to scale the pseudorange. The values of these observables are compared between adjacent epochs.
RR = (p/λ) – φ (1)
Two adjacent epochs are used, as then the integer ambiguity value, as well as the ionospheric and tropospheric errors, and satellite and receiver clock errors are the same, or negligibly different at such small (<1 s) epoch intervals. Therefore, these are all canceled out, and the resulting value is the measurement receiver and observable noise. The pseudorange observable will be significantly noisier than the carrier phase observable, therefore this method is a good way to calculate the measurement noise for the pseudoranges.
Ionospheric Residual
Surveyors work the Berezitovy mine in the North Amur region of Russia. (Photo: Javad GNSS)
If the carrier waves traveled only through a vacuum, then a phase observation from a specific satellite to a specific GNSS receiver could be scaled and converted to an equivalent phase measurement on another frequency using the frequencies of the carrier waves. However, as the signal passes through the ionosphere, systematic errors that are frequency dependent are introduced, so it is not possible to directly convert from one carrier phase value to another for a specific range measurement. The error is known as the ionospheric residual, and this will change slowly over time as the satellite passes overhead and the ionosphere being passed through changes, and also as the ionosphere slowly changes its characteristics over time, mainly due to the sun’s activities.
Equation 2 shows the calculation, using L1 and L2 carrier phase readings and corresponding frequencies, used to calculate the ionospheric residual. Again, the difference in the ionospheric residual values between adjacent epochs is used, as in the same way as the range residual values, external noise sources are eliminated.
(2)
Results
The results presented here are a subset of a much larger set. Figure 1 illustrates the range residuals for L1 and L2 as well as the L1L2 ionospheric residual for PRN32 (Block IIA satellite).
Figure 1. L1 range residual (left) L2 range residual (center) and L1L2 ionospheric residual (right) for GPS PRN32 (Block IIA) satellite. (Charts: Authors)
Figure 2 illustrates the L1 and L5 range residuals and the L2 (C-code) L5 ionospheric residual for PRN01 (Block IIF satellite).Both figures’ data are for the complete passing of the satellites from horizon over and back down again.The data for PRN32 is all that exists in the datafile, as this satellite only transmits L1 CA code and P(Y) code, as well as L2 P(Y) code, and corresponding carrier values.
Figure 2. L1 range residual (left) L5 range residual (center) and L2 (C code) L5 ionospheric residual (right) for GPS PRN01 (Block IIF) satellite. (Charts: Authors)
PRN01 is a block IIF satellite, and data for L1 CA code, L2 P(Y) code as well as L2 C-code, L5 code, and corresponding carrier phase values are recorded in the datafile.The block IIF satellites can result in four range residual values and five ionospheric residual combinations.Figure 2 only illustrates three of these combinations.The data were obtained from the Curtin University GNSS repository on Sept. 1, 2015, gathered at a 1-Hz epoch interval; 29,908 epoch of data were gathered for PRN32, and 26,073 epochs for PRN01.
It can be seen from these figures that the L1 range residuals are similar in characteristics for both PRN01 and PRN32.The values are noisy at the start and the end of the time series, indicating that the CA code is more prone to noise at low elevations.Comparing these to the L2 (PRN32) and L5 (PRN01) range residuals, we can see that both the L2 and L5 range residuals are not as prone to low elevation noise. Also, the two L2 and L5 range residuals are visually similar in characteristcs.By comparing the L1L2 and L2L5 ionospheric residuals (Figure 1, right, and Figure 2, right), we can see that the L1L2 combination is slightly noisier than the L2L5, in particular at low elevation angles.
If we compare BeiDou ionospheric residual results, we can see the comparison of noise on the three ionospheric residual combinations, B1B2, B1B3 and B2B3, as well as the results from the three types of satellite orbits, ie MEO, IGSO and GEO. Figure 3 illustrates the ionospheric residual results for PRN07 (IGSO) for the three frequency combinations, from data gathered on a static pillar located on top of the University of Nottingham Ningbo China’s Science and Engineering Building.
Figure 3. Ionospheric residual results for BeiDou PRN07 (IGSO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Chart: Authors)
Figure 4 illustrates the ionospheric residual results for PRN01 (GEO) for the three frequency combinations.
Figure 4. Ionospheric residual results for BeiDou PRN01 (GEO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Chart: Authors)
Figure 5 illustrates the ionospheric residual results for PRN12 (MEO) for the three frequency combinations. Here it can be seen that the B2B3 combination is generally less noisy than the B1B2 and B1B3. In addition to this, it can be seen that when the MEO and IGSO satellites are at lower elevation angles, the observables also become noisier. The GEO satellites have a constant elevation angle, and do not experience this phenomenon.
Figure 5. Ionospheric residual results for BeiDou PRN12 (MEO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Charts: Authors)
Detailed Results
The data, gathered on a single GNSS receiver located at the University of Curtin’s GNSS research center, was downloaded in BINEX format and converted into RINEX 3.02 format using RTKLIB software. Software was developed by the authors in Matlab in order to interrogate the data files and implement the range residual and ionospheric residual algorithms. RINEX 3.02 format was chosen due to its compatibility with multi-GNSS and multi-frequencies.
Industrial UAV applications such as construction draw benefits from multi-GNSS receivers’ capabilities. (Photo: Skycatch, Swift Navigation)
Results are presented for both ionospheric residual and range residual results for various GNSS. These results have been calculated with varying elevation mask angles, ranging from 0° to 55° at 5° intervals. The RMS values of the resulting ionospheric residuals and range residuals were calculated and plotted against the respective elevation mask angle for each satellite and frequency combinations. This illustrates the influence of the elevation mask angle used on the results.
Typically, tens of thousands of epochs of data were used for every plotted point in the following figures. Further to this, not only are the results for the various frequencies and frequency combinations for the various GNSS illustrated, but also the various satellite types, MEO, GEO and IGSO, and various satellite Blocks for GNSS. GPS Block IIA (PRN04 and PRN32), Block IIR (PRN14), Block IIR-M (PRN31) and Block IIF (PRN01, PRN26, PRN25) data were all analyzed. Thus, the comparison of the various frequencies within each satellite system are illustrated, as well as the variations by comparing the various satellite constellation types and the various generations of GPS satellites.
Surveying accuracy is critical to roadway construction. (Photo: Leica Geosystems)
The BeiDou data illustrated are MEO (C12, C14, C11), IGSO (C09, C10, C07) and GEO (C01, C02). The data used were gathered on Sept. 1, 2015, in order to include GPS Block IIA satellites (PRN04 and PRN32). PRN32 was retired in June 2016, and PRN04 was taken out of active service in November 2015, but the satellite was reactivated in March 2018, this time broadcasting PRN18.
Figure 6 illustrates RMS of the range residual results for GPS (a), BeiDou (b), Galileo (c), GLONASS (d) and QZSS (e) respectively. These figures have been drawn so that the y-axis ranges are the same for each, hence illustrating the relative values.
Figure 6A illustrates the range residual results for GPS. It can be seen that the L1 CA code results are the noisiest, with PRN14 being the noisiest, followed by PRN31, PRN26, PRN01, PRN04, PRN25 and PRN32. It can also be seen with these results that lower elevation angle mask increases the noise level. Both the L2 and L5 code results are less noisy.
Figure 6A. RMS range residual results for GPS. (Chart: Authors)
Looking at the detail, the L5 code results is less noisy than the L2 and affected less than the L1 results by the changes in elevation mask angles used. Interestingly enough, the data file includes both the L2 P(Y) code and L2C code results. L2C only exists on the Block IIR-M and Block IIF satellites. The L2C code results are generally noisier than the L2 P(Y) code.
Figure 6B illustrates the results for the range residuals for the BeiDou satellites. Here it can be seen that the B1 code is affected more by low elevation mask angles than B2 and B3. It can also be seen that both the geostationary satellites’ B1 results stand out, with satellite C02 being noisier than C01. The B2 and B3 values for both these GEO satellites are bunched up with the majority of the other results towards the middle of the figure. The pairs of B2 and B3 results for the GEO satellites are close to each other in values, and the pairs of B2 and B3 results for the other satellites are also close to each other.
Figure 6B. RMS range residual results for BeiDou. (Chart: Authors)
It can also be seen that the range residual results for BeiDou are generally less noisy than than GPS, in units of cycles.
Similarly, for Galileo, Figure 6C, the E1 results are worst, and affected more by low elevation masks. Again, generally the Galileo results are seen to be improved over GPS. The GLONASS results, Figure 6D, illustrate that the L1C results are generally noisier, and then the L1P, followed by L2C and L2P. PRN09 is also consistently generally noisier than PRN10. Finally, Figure 6E illustrates the results for QZSS. Again, L1C is the noisiest and affected most by low elevation mask angles.
Figure 6C. RMS range residual results for Galileo. (Chart: Authors)Figure 6D. RMS range residual results for GLONASS. (Chart: Authors)Figure 6E. RMS range residual results for QZSS. (Chart: Authors)
Figure 7 illustrates the ionspheric residual results for the same satellites as Figure 6. This time, however, the resulting ionospheric residual values are calculated using pairs of data from the same satellite on different carrier frequencies. The range residual results compare the code and carrier from specific satellites and frequencies.
Figure 7(a) shows that the ionospheric residual results are affected by low elevation masks, and that the L1L2CW (L1 CA code and L2 P(Y) code available on all the satellites) combinations are the noisiest, followed by L2L5WX (L2 P(Y) code and L5 code available on Block IIF satellites, PRN 26, PRN01, PRN25), followed by L1L2CX (L1 CA code and L2 C code available on Block IIF and Block IIR-M satellites, PRN31, PRN26, PRN01 and PRN25), followed by L1L5CX (L1 CA code and L5 code, Block IIF satellites, PRN01, PRN25, PRN26) and finally the least noisy were the L2L5XX results (L2 C code and L5 code available on Block IIF satellites, PRN26, PRN25 and PRN01).
Figure 7A. Ionospheric residual results for GPS. (Chart: Authors)
Figure 7(b) illustrates the BeiDou ionospheric residual plots, illustrating that satellite C14 is much noisier for all three combinations of B1B3, BB1B2 and B2B3 in that order. The B1B2 combinations for the satellites are generally the noisiest, and then the B1B3 and B2B3 combinations are intertwined. The Galileo results again illustrate that the E1 combinations are generally noisier, and again we see the effect of low elevation angle masks, Figure 7(c). Generally, however, the Galileo results are less noisy than GPS, as are the BeiDou results.
Figure 7B. Ionospheric residual results for BeiDou. (Chart: Authors)Figure 7C. Ionospheric residual results for Galileo. (Chart: Authors)
The GLONASS results are again generally the noisiest, and again PRN09 is noisier than PRN10, with the L1P combinations being noisier, Figure 7(d). Figure 7(e) for QZSS shows that there are generally two groups of results. The upper set consists of L1L2ZX, L1L5ZX, L1L2XX, L1L5XX, L1L6ZX and L1L6XX from highest to lowest noise respectively. The lower, less noisy, group consists of L1L2CX, L1L5CX, L2L5XX, L2L6XX, L1L6CX and L5L6XX from highest to lowest noise respectively. Further details about the various codes and carrier values can be found in the RINEX 3.02 manual produced by the IGS.
Figure 7D. Ionospheric residual results for GLONASS. (Chart: Authors)Figure 7E. Ionospheric residual results for QZSS.(Chart: Authors)
Conclusions
A surveyor checks an urban construction project. (Photo: Topcon)
These preliminary results illustrate that there are differences in the noise values for various GNSS, frequencies as well as satellite generations and orbit types. It can be seen that generally L1, B1 and E1 have noisier results, and are affected moreso by low elevation mask data, and hence multipath. It can also be seen that newer generations of satellites do indeed produce better quality data.
Some specific satellites produce lower quality data such as GLONASS PRN09 and BeiDou C14. This could be due to multipath produced at the satellite.
Today roughly 100 GNSS transmit data, and typically users can gather data from 30 to 50 at any time. Positioning requires nowhere near this number of satellites, therefore decisions are needed as to which satellites and which data to use in a positioning solution. Our findings imply that our approach could be used in such decision-making in GNSS processing software, helping the software to choose the optimum satellites to draw from in a positioning solution.
Acknowledgments
This work described in this article was first presented at the FIG 2018 conference held in Istanbul, Turkey. The authors acknowledge the use of data supplied from the Curtin University GNSS Centre.
Manufacturers
The GNSS receiver used is a Trimble NET R9, and the antenna is a Trimble TRM 59800.00 SCIS choke ring antenna. A ComNav K508 GNSS receiver supplied some of the BeiDou results.
GETHIN WYN ROBERTS is an associate professor at Fróðskaparsetur, the University of the Faroe Islands. He is past Chairman of the FIG’s Commission 6, Engineering Surveys, and previously held posts at the University of Nottingham both in the UK and in China. He holds a Ph.D. in engineering surveying and geodesy from the University of Nottingham.
CRAIG M. HANCOCK is an associate professor in Geodesy and Surveying Engineering and the head of the Department of Civil Engineering at the University of Nottingham, Ningbo, China as well as the head of the Geospatial and Geohazards Research Group. He holds a PhD from the University of Newcastle Upon Tyne.
XU TANG is a research fellow at the University of Nottingham, Ningbo, China. He holds a PhD from Nanjing University.
A new interactive app by Esri models the cumulative number of climate hazards likely to occur under different emissions scenarios for any place on Earth through 2100. The app visualizes the index of 11 hazards, including warming, drought, heatwaves, fires, precipitation, floods, storms, water scarcity, sea-level rise, and changes in natural land cover and ocean chemistry. Users can see how severely locations around the world will be affected by these cumulative hazards under different global mitigation scenarios.
Esri created the app in partnership with the University of Hawaii’s Camilo Mora, lead author of a study in Nature Climate Change, which provides a comprehensive assessment of the simultaneous occurrence of multiple climate hazards strengthened by increasing greenhouse gas emissions and their effect on humanity. Mora’s analysis of thousands of peer reviewed scientific papers reveals 467 ways in which human health, food, water, economy, infrastructure and security have been impacted by multiple climatic changes.
By clearly visualizing the threats that our world’s ecosystem faces at every level, the maps and data hammer home how location intelligence can help with understanding what is at stake in making decisions, even at a global scale. Visualize the data here.
Advanced AI, robotics and autonomous vehicle services on Sprint’s dedicated IoT network will adapt to the real world using highly accurate, detailed and constantly refreshed maps.
Sprint and Mapbox are launching precision mapping technology with Curiosity IoT, allowing automated services that run on Sprint’s dedicated internet of things (IoT) network to move around the ever-changing world with pinpoint accuracy.
Smart machines, from drones to autonomous delivery carts, will be able to make fast location and routing decisions using highly detailed, accurate maps that are updated as the environment changes.
Sprint made the announcement this week at the Consumer Electronics Show being held in Las Vegas.
High Accuracy and Precise Detail with Live Maps. Mapbox offers what it calls a “live map”, a map built not from traditional data surveys months or years before, but from data collected from hundreds of millions of location-enabled sensors that feed back information about the world in real time.
Mapbox uses artificial intelligence (AI) to turn those massive data flows into a picture of real time transit paths that can be used for precise, up-to-date routing.
Image: Mapbox
Through its relationship with Sprint, Mapbox will leverage the inherent advantages of Curiosity IoT with 5G to take mapping to the next level. The network’s extreme bandwidth and low latency will allow Mapbox to collect higher volumes of richer data from the sensors, including high resolution video.
That data can be processed to identify and detect changes in the physical environment. Those changes are then incorporated into updated maps which can be distributed at scale to a wide variety of smart machines. The result is more accurate, more up-to-date maps that reflect the world in real time.
“Smart machine-based services need to be able to make immediate mobility decisions similar to the way a driver might react to construction, traffic or other obstacles on a street,” said Ivo Rook, senior vice president, IoT and product development at Sprint. “The launch of Mapbox’s precision mapping technology allows all intelligent machines to move at a level of precision never seen before. Our fully dedicated Curiosity IoT network and operating system — soon to be powered by Sprint’s mobile 5G connectivity makes this possible. From autonomous vehicles to advanced AI-based machines, precision mapping is a big step forward in making smart service models a reality for the immediate economy.”
“As maps guide new smart machines on IoT networks, you remove the human in the middle that used to compensate for differences between the map and the real world. Precision mapping services need to reflect the world as it is, at that precise moment so that those smart machines can travel safely and efficiently,” said Eric Gundersen, CEO of Mapbox. “Sprint’s Curiosity IoT network with mobile 5G provides platform services that make that real with high bandwidth, edge computing for object detection and data processing and super low latency.”
Curiosity IoT with 5G. Sprint 5G and Curiosity will create the new standard in IoT which features device data intelligence, over-the-air device management and chip-to-cloud security, the companies said.
When coupled with Sprint mobile 5G technology, Curiosity IoT’s dedicated, distributed and virtualized IoT core network is capable of supporting artificial intelligence, robotics, edge computing, autonomous vehicles and other IoT systems requiring extreme low-latency and high-bandwidth.
Researchers at the Massachusetts Institute of Technology (MIT) presented a project at the International Symposium on Experimental Robotics involving an autonomous drone fleet system that collaboratively mapped an environment under dense forest canopy.
Designed with search and rescue in mind, the drones used lidar, onboard computation and wireless communication, with no requirement for GPS positioning.
Each drone carries laser-range finders for position estimation, localization and path planning. As it flies, each drone creates its own 3-D map of the terrain. A ground station uses simultaneous localization and mapping (SLAM) technology to combine individual maps from multiple drones into a global 3-D map that can be monitored by operators.
The MIT team tested its concept via simulations of randomly generated forests, and world-tested two drones in a forested area at NASA’s Langley Research Center. In both experiments, each drone mapped a roughly 20-square-meter area in about two to five minutes, while the control system integrated their maps together in real-time.
The drones were programmed to identify multiple trees’ orientations, as recognizing individual trees in impossible for the technology, and individual trees’ orientation very difficult. When the lidar signal returns a cluster of trees, an algorithm calculates the angles and distances between trees to identify the cluster and determine if it has already been identified and mapped, or is a new mini-environment.
The technique also aids in merging maps from the separate drones. When two drones scan the same cluster of trees, the ground station merges the maps by calculating the relative transformation between the drones, and then fusing the individual maps to maintain consistent orientations.
Taoglas, a provider of internet of things (IoT) and automotive antenna and RF solutions, completed its acquisition of ThinkWireless Inc., an antenna provider that specializes in the design, development and production of combination antenna systems for the commercial vehicle market.
The ThinkWireless brand will become ThinkWireless, a Taoglas company. ThinkWireless Founder and Chief Executive Officer Argy Petros and Director of RF Technology Pierre Wassom will remain.
“Think Wireless has made a name for itself as a designer and developer of high-quality combination antenna systems with deep roots in the commercial trucking industry, where infotainment services, including good quality of service from satellite and AM/FM radio, weather band and GNSS are crucial,” said Ronan Quinlan, Co-CEO, Taoglas.
“As we continue to explore potential acquisitions to strengthen the Taoglas brand, we were struck by how similar Think Wireless’ approach to antenna design and manufacturing is to our own commitment to excellence,” Quinlan said. “This is a great acquisition for the Taoglas Group as we look to further expand into new, synergistic markets such as the commercial vehicle industry.”
ThinkWireless, headquartered in Coconut Creek, Florida, specializes in the design, development and production of combination antenna systems that incorporate two or more frequency bands, including those for SiriusXM satellite radio, GPS, AM/FM, weather band, DAB, HDTV, Wi-Fi, Bluetooth and LTE.
The ThinkWireless facilities will become Taoglas’ ninth design and development center globally, and the third in the U.S., alongside centers in San Diego and Minneapolis.
“Taoglas is well-known as a global brand that delivers the highest-quality antennas and RF solutions to the automotive, IoT and other markets,” Petros said. “Taoglas’ global scale and sales channels are unparalleled and will help grow the reach of ThinkWireless’ solutions in the trucking and commercial vehicle industry around the world.”
The ThinkWireless antennas will be available for purchase on the Taoglas website, through key distribution partners and through Taoglas’ Antenna Builder e-commerce marketplace for custom antennas and cable assemblies.
Calendar pages allows seem to fly by quickly, and 2018 was no different. While many of the items discussed in last year’s review continued to be topics of advancement, there are several new sources of technology, data collection and potential issues for surveyors going into the new year.
Let’s look back at the stories that affected the surveyor and their use of GNSS technology in 2018.
FCC broadband accuracy
The race across America to provide better broadband coverage hit a snag late in 2018 when critics of the Federal Communications Commission (FCC) voiced their displeasure with the accuracy of maps produced to depict the coverage of broadband access.
These critics are pressuring the FCC to verify internet coverage and speed of data availability in rural areas as reported by the broadband companies.
The FCC unveiled a new broadband map in February 2018. (Image: FCC)
These broadband companies are only required to report on the advertised availability and data speeds and not the actual coverage/speed of the installed networks. Critics of the FCC have found that information used from the broadband providers overstates the available speeds and number of internet service providers, thus allowing the FCC to produce mapping of broadband that is not correct.
Because of this incorrect reporting, it is estimated that almost 40 percent of rural America doesn’t have access to broadband data with no formal plan of rectifying this situation. The FCC has stated that they will investigate these coverage maps in order to determine if monies distributed to broadband providers were not used in accordance with the promised delivery of coverage and data speed.
Why does this matter to surveyors? As previously discussed in past columns, the reliance on the real-time network capability of GNSS is one of the biggest time and production savers for the surveyor and for those working in rural America is no exception.
Not just in small towns but out in the open where large parcels are being surveyed for many different reasons, including pipelines, wind and solar installations and title conveyances. By having broadband available use by surveyors, these tasks can be accomplished with shorter timeframes and less steps to keep critical data in compliance with established coordinate systems.
While this bill received lots of attention because of the FAA implications, the portion of the bill concentrating on geospatial oversight will have a lasting effect on the governance and development of the national mapping industry.
For many years, the ever-developing amount and sources of geospatial data has been growing within several different agencies of the United States government. This bill was established to help streamline the efforts and availability of geospatial data by assigning specific agencies to oversee the development and introduction of new technologies.
The biggest takeaway from this bill will be the reduction of agencies working on concurrent data sets for public and private use and therefore streamlining the opportunities to introduce newly acquired information into critical programs, (such as FEMA floodplain mapping, GAO asset management, etc.).
Part of the reason I wish to highlight this bill was the efforts of the National Society of Professional Surveyors (NSPS) to keep the state professional licensing laws intact, the use of private sector businesses for providing surveying services, and to keep quality-based selection (QBS) as the primary tool for awarding contracts for procurement services.
Because of the actions and reasoning by NSPS, the authors of the bill withdrew the language that would allow “low bid” opportunities within these contract awards. This influence by NSPS is a prime example of how a profession can influence legislation through our democratic process.
Galileo implementation, Beidou installation, GPS Block III launches
SpaceX’s Falcon 9 rocket orbited the first GPS III satellite on Dec. 23, 2018. (Photo: SpaceX)
In November 2018, the FCC opened a new chapter in GNSS observation by approving a waiver to allow GNSS receivers to utilize Galileo transmissions for location determination without a specific FCC license. Traditionally, the FCC would require licensing of public, receive-only GNSS equipment used with any foreign-based systems but worked with several US agencies to create a waiver to allow faster implementation to use the Galileo signals.
It should also be noted that the Chinese government has been rapidly building the latest stage of their own GNSS constellation, the BeiDou system. The United States and China have been promoting cooperation to allow each side to better understand the current workings of GPS and BeiDou, (GPS-BeiDou Statement). China is currently completing its third phase of the navigation system that potentially will surpass the United States GPS constellation in data availability and accuracy, (See GPS World“Directions 2019: BeiDou accelerates global deployment,” December 2018).
Not to be outdone, the U.S. has begun its implementation of their next wave of satellites, the GPS III containing the latest technology, the L1C civil signal, with improved accuracy and anti-jamming programming. On Dec. 23, the SpaceX Falcon 9 rocket delivered the GPS III SV01 into its intended orbit (SpaceX Launch) with more launches scheduled for additional satellite vehicles in 2019.
These efforts to increase satellite coverage and accuracy will only improve the use of GNSS receivers by surveyors. While I look forward to software and receiver upgrades to take advantage of the newer birds, we still need a backup plan in case of international conflicts and a reduction/discontinuation of GNSS service.
GPS and terrestrial backup
The Frank LoBiondo U.S. Coast Guard Authorization Act of 2018, which also included the National Timing Security and Resilience Act, was signed into law on Dec. 4 and directs the Secretary of Transportation to establish a terrestrial back system for the U.S. satellite navigation system within a two-year period (see “GPS to get terrestrial backup system”).
The bill lays out specific conditions for the backup plan:
terrestrial
wireless
synchronized to UTC
difficult to disrupt
able to penetrate underground and inside buildings
capable of deployment to remote locations
expandable to provide position, navigation and timing (PNT), and
able to work in concert with similar systems such as eLoran.
However, this bill did not provide any funding for the creation of this system but now allows the introduction of appropriations in future bills and acts. As I have written in past columns (see “The day GPS went away,” September 2017), it won’t be a matter of if but when something happens to our current GNSS capabilities and we need to develop this backup plan yesterday.
Dual-band GNSS cellphones as the new norm
My last submission featured the latest in chipset for cellphones and utilizing dual-frequency GNSS signal reception. Xiaomi, based in Beijing, China, introduced the Mi 8 phone with a dual-frequency GNSS chip in the Spring of 2018 to rave reviews.
This chip frequency reception (E1/L1+E5/L5) is targeted to embrace the Galileo and GPS constellations for increased accuracies (within a decimeter) well beyond the current norm for smartphones (typically 1-3 meters +/-).
Since then, Xiaomi has released the Mi Mix 3 and Huawei has released the Mate 20, Mate 20 Pro and Mate 20 X, all with dual-frequency chipsets. However, all of these phones are not available in the U.S., and the security issues with Huawei has been well documented (CNBC Report, February 2018).
The reason I still bring these up for the surveyor is because soon we will have dual-frequency capability on the phone in our pockets here in the U.S. Such phones can greatly increase efficiencies, especially when used during reconnaissance efforts. I believe many more phone manufacturers will begin to incorporate dual-frequency chips in their future models to increase location accuracies for the users and take advantage of upcoming network enhancements (see GPS World“Dual-frequency GNSS smartphone hits the market,” June 2018.)
Surveyors vs. technology disruptors
The Mi 8 smartphone offers dual-frequency capability. (Image: Xiaomi)
One of the biggest stories in the surveying world made national headlines after a start-up “GEO-spatial” consultant created by retired bankers was sued by the Mississippi Board of Licensure for Professional Engineer and Surveyors for having “engaged, and continues to engage in the practice of surveying while not licensed by the Board.” (Madison County, Mississippi, Chancery Court.) While the initial suit remained under the national radar, the countersuit by the consultant and subsequent articles in national websites brought the situation to the front page.
The issue at hand is the creation of “plats” combining a legal description for a parcel with a high-resolution photo (captured by various means, including UAV) and depicting said legal description on the photo for use by banks and other financial institutions for risk evaluation. Their argument is that they have “First Amendment rights” to provide public information (the legal description) on a recent aerial photograph in order to provide an exhibit for lenders to review and make loan decisions. Banks are now paying much less in fees to this company for an exhibit instead of a Plat of Survey provided by a licensed surveyor, yet the exhibit provides no assurance (or certification) to its validity and/or any metadata for the represented information.
The subsequent articles by both Bloomberg and Ars Technica writers liken the situation to Airbnb versus hotels and Uber/Lyft versus taxi drivers as a new “disruption in technology” brings forth change to previously licensed professions. In fact, the author of the Bloomberg article stated, “the clients are sophisticated, and they’re not complaining.”
Using this mentality, we could apply it to any licensed profession and allow services normally regulated by laws to be administered by non-professionals, as long as the client “is sophisticated and not complaining.” This means anyone can provide accounting, medical, dental or even law services if the client is satisfied. As previously published here, (see GPS World“Accuracy, precision and boundary retracement in surveying” July 2017), a boundary survey is not simply a mathematical figure from a legal description. It takes a trained person to know how to properly relate a legal description to a physical parcel and professional licensing provides that assurance (and protection) to the public.
This situation falls squarely in the GNSS wheelhouse for surveyors, especially as technology advances and accuracies become smaller with progress, (i.e. GPS Block III, BeiDuo, Galileo, etc.) and the ability to measure with higher positional accuracy, (i.e. Xiaomi Mi 8 and other to follow).
The surveying profession has joked for years that when these technologies do come forward, many unlicensed “professionals” will come forward with their measuring devices (phones) and locate property lines as part of their service.
But for now, it isn’t just the physical location by GNSS measurement we should worry about; it is the high-resolution photo software, GIS data sources and those folks enterprising enough to put all this information together. The surveying profession will need to ramp up its message to public to help better define what the licensed surveyor provides versus the “we can do it much cheaper and faster” stories. More often than not, you get what you pay for.
Data collection advancements
Emlid Reach RS with iPad. (Photo: Tim Burch)
While 2018 didn’t see any revolutionary changes to GNSS data collection, several small advances are noteworthy. Besides the previously mentioned dual-frequency cellphones, we are also seeing more integration with the cellphones themselves as data collectors in conjunction with stand-alone GNSS receivers (see GPS World“University research uses smartphones for precision GNSS,” September 2018).
Several of the major survey equipment manufacturers are joining a group of small GNSS start-ups by introducing single- and dual-frequency receivers to work with both Android- and iOS-based phones and tablets for more cost-effective positional solutions.
Another trend that is becoming very popular is the use of post-processing kinematic (PPK) solutions with many of the newest models of multi-rotor and fixed wing UAVs. The early (and expensive) trend of aerial vehicles produced by the major surveying equipment manufacturers insisted on installation of a dual-frequency RTK receiver in order to provide a more robust control system for the orthometric photo process. Because there is still a need to combine the still photos from the UAV flight via various “stitching” software, the need (and expense) of RTK within the receiver, while a nice feature, has become overkill for most aerial needs. However, there are times and applications when a fixed-RTK location could be useful, especially during emergency situations when needing to utilize the UAV for live streaming purposes.
The last big trend to gain popularity comes from Propeller, a young tech company from Australia that provides both a control point product and data reduction/reporting service. Their revolutionary ground control point (GCP) target, the Aeropoint, is becoming a very popular item for UAV pilots worldwide. These 24-inch (61-CM) square foam targets contain a single-frequency GNSS receiver that collects RINEX data while performing your UAV flight. Spread these targets around your site, setup and perform your survey, then download the target data to the Propeller app on your phone/tablet. The app automatically uploads the data to the company’s site and processes the geographical location for each target into your chosen coordinate system. It truly is that simple and the Propeller folks have made it easy to use. Their online software, Propeller Platform, is also available for photo/data processing and site analysis/visualization/volume computations. They, too, are now teaming with DJI to offer PPK solutions combining Aeropoint data along with Phantom 4 RTK photo data in a convenient, streamlined process.
For 2018, our firm (SPACECO Inc) expanded our UAV program in several ways to take advantage of these trends. First, we been using the Emlid Reach RS single-frequency GNSS receiver utilizing a Bluetooth connection to an iOS-based tablet to GCP’s for our UAV program. The receiver’s low cost and ease of use with an RTN network has been a pleasant change from typical surveying equipment. We also use Propeller’s Aeropoints in locations where the RTN coverage is not readily available. For sites that are substantial (typically 300 acres+), we often send our data to the Propeller Platform for photo stitching and data reduction to take advantage of their computing power.
WingtraOne. (Photo: Brian Kravets, SPACECO Inc.)
Lastly, we wanted to expand our fleet of quad-rotor UAV’s to include a fixed wing model for larger sites. A visit with the Wingtra crew at InterGeo 2017 in Berlin convinced me that a vertical take-off and land (VTOL) model would be a great addition, so we took delivery of our WingtraOne this past summer. The ease of use and amount of project space the Wingtra can cover was already great but we’ve added the PPK module to reduce the amount of GCP’s necessary, especially in inaccessible areas. All these additions to our survey department (carefully vetted and purchased; no freebies from any of the manufacturers!) have provided new ways to expand our services to our clients and allows us the opportunity to enjoy what we do along the way. It is my pleasure to report from personal experience that these trends are solid and will continue to increase our abilities and productivity for days to come.
What’s next for 2019?
Some of the items I see gaining traction in 2019 will include additional sensors for UAV’s (LiDAR, hyperspectral, infrared), continued improvement in cost effectiveness of laser scanners and LiDAR, increased interest in SLAM (simultaneous localization and mapping) technology and, of course, more geolocation services tied into autonomous vehicles/delivery. Will 2019 be the year Amazon drops my packages by UAV at my front door? As fast as these technologies are developing, I wouldn’t bet against it.
The Faro Focus scanner attached to a Stormbee UAV. (Photo: Stormbee)
3D measurement and imaging company Faro has joined with UAV provider Stormbee to offer an integrated airborne 3D scanning solution designed to quickly gather large area data for crash scene documentation, security pre-planning and military applications.
The integrated solution includes the Faro Focus laser scanner, the Stormbee S series UAV and the Beeflex software suite.
The airborne solution enables wide-area scanning missions, such as highways, train infrastructure, and buildings. While these would take days when scanned from the ground, they can now be completed in just hours without interrupting traffic or setting foot in a zone of interest.
The Faro Focus laser scanner. (Photo: Faro)
The solution further enhances productivity by allowing users to capture complex environments where traditionally would be inaccessible to ground based scanning and levels of accuracy and detail from the air with exceptional.
The data can then download to FARO Zone for crash reconstruction, security pre-planning, military reconnaissance.
The Faro–Stormbee airborne solution has no need for control points, meaning is quicker to start scanning an area compared to other lidar drones. Drone pilots can fly with ease as it goes up to 100 meters (328 feet) in the air. With the drone’s integrated redundancy, even if a propeller or battery fails the UAV still flies.
“Stormbee has developed and validated its UAV credibility from real-life testing in the most rigorous environments,” said Liesbeth Buyck, CEO of Stormbee. “As a result, we are confident that this turnkey solution, that includes the Stormbee UAV and the FARO Focus laser scanner, creates a new reliability and quality benchmark for airborne 3D data capture solutions.”
Users can create centimeter-level accurate point clouds directly from the in-flight data. The user-friendly Beeflex software takes little training to use and can be exported directly into Faro Scene or Faro Zone 3D software for further analysis or to combine aerial scans with the detail-rich data from terrestrial scanners.
The Faro scanner can detach from the drone and be used as a terrestrial scanner or even a mobile mapper. This flexibility allows users to use one scanner in the air, on land or affixed to a vehicle.
Combined with Faro’s Focus laser scanner compact design, IP54 rating and laser technology users can scan a vast variety of scenarios, from large areas (railways, cities), areas with no light (tunnels, burned buildings), and hard-to-document areas (cluttered crime scenes, inside dumpsters).
