The Spectratime Force 2020 Rubidium clock is designed for the defense market.
Spectratime, a provider of high precision atomic clocks and a business of the Orolia Group, has launched the Force 2020.
The Force 2020 is a rugged, anti-vibration, GPS/GNSS-lockable, ultra-low-noise Rubidium atomic clock for highly dynamic defense platform applications.
According to Pascal Rochat, managing director of Spectratime, “Next-generation defense airborne radars, drones, helicopters, secure shipboard and radio communications systems use high K-band frequencies which require ultralow noise performance. In tactical missions, ultra-low-noise performance can only be minimally degraded during exposure to dynamic vibration and high-g environments to maintain the integrity of the battlefield systems. Spectratime’s Force-2020 rubidium atomic oscillator is perfect for such critical applications, and thus we are currently working with large defense contractors to integrate our new product into their highly dynamic defense platform systems.”
Product features
Output frequency up to 500 MHz
Can use the patented SmarTiming+ technology, disciplining an external SAASM or a non-SAAMS GPS or GNSS 1PPS reference up to 100,000 seconds with an auto-adaptive loop time operating at 1-ns resolution
State-of-the-art frequency and timing signal stability performance
Integration of an ultra-low-noise OCXO oscillator with optional low g-sensitivity and a single or dual vibration-isolated tray for the OCXO and/or the Rb oscillator to meet various dynamic application requirements.
U-blox has launched the LARA-R3121, a new module comprising a single-mode LTE Category 1 modem and a GNSS positioning engine specifically designed for Internet of Things (IoT) and machine-to-machine (M2M) devices.
The LARA-R3121 is designed for IoT applications including smart utility metering, connected health and patient monitoring, smart buildings, security and video surveillance, smart payment and point-of-sale (POS) systems, as well as wearable devices, such as action cameras.
“Most IoT modules on the market use LTE modem technology, developed by handset-focused silicon vendors. They may not provide the best fit for IoT applications, because they focus on features targeted at Tier 1 handset makers, limited by short life cycles. The LARA-R3121 is different with features and qualifications crafted for the industrial markets,” said Andreas Thiel, u-blox co-founder and executive VP, Cellular Products and IC Design. “This is the only cellular module comprising a LTE Cat 1 modem and a GNSS engine, with complete module hardware and software all developed by a single supplier. With our focus on the IoT market, we bring an ‘IoT first’ approach to silicon design.”
The LARA-R3121 is supplied in the small 24 x 26 mm LARA LGA form factor for compact IoT devices. This standardized package enables straightforward automated manufacturing and is pin-compatible with the u-blox LARA-R2 series, which supports multimode LTE Cat 1 with 2G/3G fallback.
LARA-R3121 module by u-blox.
According to the company, it is a landmark in u-blox’s long-term strategy to create modules based on the UBX-R3 LTE modem technology platform, an internally developed, flexible, software-defined modem architecture specifically designed for IoT and M2M.
The essential modem, positioning and module components of the LARA-R3121 are developed in-house, allowing for freedom for innovative feature development, for enabling end-to-end security and giving full control of product quality, while ensuring the long term product availability required by many IoT applications. Because modem and GNSS technologies were all developed in-house, u-blox is also able to provide unparalleled technical support for developers.
The LARA-R3121 features FOTA, providing customers with a solution to issue firmware over the air updates. It also benefits from end-to-end security features, such as secure boot, secure transport layer, secure authentication, secure interfaces and APIs. Like other cellular modules from u-blox, it complies with a nested architecture, which allows for easy migration, and future-proof, seamless mechanical scalability across cellular technologies.
As a single mode, LTE-only device, LARA-R3121 takes advantage of the fact that LTE networks are becoming universally available. Increasingly, products do not require fallback to 3G or 2G, which means that non-essential components can be removed, reducing cost and power consumption.
The 10 Mbits downstream and 5 Mbits upstream maximum throughput of LTE Cat 1 provides data rates sufficient for good quality video streaming.
Rockwell Collins has awarded a contract to Systron Donner Inertial (SDI) for an inertial measurement unit (IMU) needed for the new Boeing 777X Integrated Flight Control Electronics (IFCE) fly-by-wire system.
The SDI300 aviation-grade inertial measurement unit by Systron Donner Inertial.
The core of SDI’s solution is its SDI300 aviation-grade IMU, which delivers reliable high performance and stability over full temperature and vibration environments, the company said.
The compact, low-power, high-quality SDI300 IMU enables efficient and smooth aircraft maneuvers through the most complex flight scenarios and challenging environments, while improving total system cost-effectiveness, reduced obsolescence and increased sustainability.
“SDI is honored to be selected and partnered with Rockwell Collins, BAE Systems, and Boeing for the 777X IFCE Program. The collaboration, teamwork and support provided by Rockwell Collins and the IFCE program team has been outstanding,” said David Hoyh, director of sales and marketing for SDI. “Systron Donner Inertial has a strong execution and service record on today’s B777.
“The new, smaller, lighter SDI300 aviation IMU will leverage SDI’s next generation quartz gyros and system architecture and be certified to DO-160/DO-254 Level A requirements, creating an innovative MEMS solution for the 777X’s advanced fly-by-wire system,” Hoyh said.
For more information and specifications on the COTS SDI300 or for information on the complete SDI product line, call +1 925-979-4500, e-mail: [email protected]; or go to www.systron.com.
In this month’s column, we take a look at some initial efforts to independently process smartphone measurements. How good are the results? Read on.
INNOVATION INSIGHTS with Richard Langley
IT WAS 1999. That was the year when the first mobile or cell phones equipped with GPS became available. Garmin introduced the NavTalk Pilot aimed at aviators and Benefon, a former Finnish cellphone manufacturer, offered the Benefon Esc! These devices benefited from the continuing reduction in the size (and power needs) of GPS receivers, which had been shrunk to just a few integrated circuits or chips.
I documented that progress in GPS technology in an article for this column in April 2000 titled “Smaller and Smaller: The Evolution of the GPS Receiver.” In that article, I also mentioned that receiver modules had been made small enough to be put in a wristwatch. This was something that I and other researchers at the University of New Brunswick had predicted in a paper presented at a meeting in 1983. Talk about prescient.
In our paper, we said “With the miniaturization and cost reduction being experienced continually, it is surely safe to postulate the limit of this evolution: a cheap ‘wrist locator’ giving instantaneous positions to an accuracy of 1 [millimeter].” Elsewhere in the paper, we suggested a price for this technological wonder of $10, and that it would be available sometime in the twenty-first century.
Costing about $400 and giving GPS Standard Positioning Service accuracies, the first “wrist locator” also came on the market in 1999 — before the 21st century began. While we may have been a bit overly optimistic in the capabilities and cost of the “wrist locator,” the basic prediction came true earlier than expected. And I said in that April 2000 column that there’s room for further development. No kidding. It wasn’t many years after that GPS World article appeared that we had announcements of single-chip receivers that could be more easily integrated into cell phones and other devices.
And today we have “system on chip” integrated circuits that combine many of the major functions of a cell phone into a single chip including a multi-core microprocessor, modems for two-way radio communications and most of the functioning of a GNSS receiver. And I say GNSS receiver as the latest chips support not just GPS but GLONASS, BeiDou, Galileo and the Quasi-Zenith Satellite System as well as satellite-based augmentation systems.
The widespread addition of GPS receivers to cell phones was initially stimulated by E-911 requirements in North America and similar initiatives elsewhere. In the United States, the Federal Communications Commission requires cell-phone carriers to report phone location to within 50 meters for 67 percent of emergency calls, and within 150 meters for 90 percent of calls. Such accuracies are readily achieved in most outdoor locations even with some multipath signal degradation. In fact, positioning accuracies for cell phones in benign environments are often better than 10 meters, even approaching the meter level at times. This allows us to use applications on our GNSS-equipped smartphones for navigation, for example. As a result, some smartphone users are abandoning their vehicle “satnavs” in a move not unlike the abandonment of landline telephones.
While positioning accuracy at the meter or few-meter level may be adequate for pedestrian and vehicle navigation, sub-meter-level accuracy might be desirable for certain tracking applications and other uses–including some we haven’t even dreamed of yet. So, are such cell-phone positioning accuracies achievable with current technology? How close are we to having personal navigation devices with the one-millimeter accuracy of our futuristic “wrist locator?” Thanks to Google’s recent release of code to permit access to the raw GNSS measurements from smartphones and tablets running a version of the Android operating system, researchers and developers are able to answer that question.
In this month’s column, we take a look at some initial efforts to independently process smartphone measurements. How good are the results? Read on.
By Simon Banville and Frank van Diggelen
The development of low-cost GNSS chips spurred a revolution in positioning, navigation and timing (PNT) devices. Once reserved for military operations and high-end geodetic applications, GNSS positioning eventually found its way into the lives of millions (if not billions) of users with the development of GNSS-enabled car navigation devices and smartphones.
The meter-level accuracies provided by GNSS receivers in smartphones enabled a wide range of location-based services including social networking, vehicle tracking, weather services and so on. At the other end of the spectrum, more expensive GNSS equipment can provide centimeter- and even millimeter-level accuracies by tracking signals on multiple frequencies and by using high-quality antenna and receiver components. Such GNSS receivers are utilized in a variety of applications such as tectonic motion monitoring, land surveying, precision farming, oil and gas exploration, and machine control.
During its “I/O 2016” conference held in May 2016, Google announced that raw GNSS measurements from smartphones and tablets running the Android N (“Nougat” = version 7) operating system would be made available to developers. The implications of this initiative are significant for the community since it allows us to move away from the black-box concept of the GNSS receiver providing meter-level accuracies and opens up the possibilities of using pseudorange, Doppler and carrier-phase measurements to derive more accurate positions. Even if the low-cost GNSS antennas and chips contained in smartphones will never outperform high-end geodetic instruments, it is an interesting research avenue to investigate how far these devices can take us. This opportunity could in turn spark the emergence of new applications that would not have been envisioned before.
Even though the opportunities for high-precision positioning with smartphones were limited prior to this announcement, scientists and engineers have already tried to tackle this issue. For instance, researchers at the University of Texas at Austin used a smartphone antenna to feed GNSS signals into a software-defined receiver built at their facility.
While carrier phases were affected by significant time-correlated errors such as multipath, centimeter-level differential positioning could still be achieved. Direct access to GNSS measurements from modified smartphone firmware was also reported. In one such experiment, a survey-grade antenna was used to feed GNSS signals to a modified Samsung Galaxy S5 smartphone running a Broadcom GNSS chip. The analysis revealed a nonzero and drifting bias in the carrier-phase measurements that prevented both floating-point-valued-ambiguity and integer-ambiguity-fixed solutions to be computed.
Microsoft Mobile also produced custom firmware for the Nokia Lumia 1520 “phablet” smartphone, allowing access to raw GNSS measurements from the phone’s internal Qualcomm integrated receiver. This data, analyzed by members of the Finnish Geospatial Research Institute, identified pseudorange measurement noise on the order of tens of meters and carrier-phase observations contaminated by several outliers. As a result, only meter-level positioning could be achieved.
In the following sections, we first explain how raw GNSS measurements can be accessed from the Android N operating system (os). After performing a preliminary assessment of the data quality, we use state-of-the-art positioning software developed at Natural Resources Canada to assess whether precise positioning can currently be achieved using raw GPS observations collected by a smartphone.
ACCESSING RAW GNSS MEASUREMENTS
The Android operating system defines application programming interfaces (APIs), which are a collection of protocols allowing users to access the system’s functionalities. The GNSS raw measurements are contained in the GnssClock and GnssMeasurement software classes, which are described in the android.location APIs. Google has released the GnssLogger application or app along with its source code (see FIGURE 1). You can find the app here (download the file GnssLogger.apk).
FIGURE 1. GnssLogger screenshot, showing raw measurements from a GPS satellite and a GLONASS satellite.
You can use the app as-is to log the GNSS measurements to a text file, or you can use the source code to build the GNSS measurements into your own app. At the same GitHub repository, you will also find the measurement data used in this article, and Matlab files for reading, processing and plotting the data.
The GnssLogger app logs the measurement data in comma-separated-value (csv) text format, and sends the file by Internet to your e-mail, Google Drive or some other file-sharing facility. The data fields are described in the GnssClock and GnssMeasurement classes in the online android.location API documentation.
The app logs the decoded ephemeris data in decimal representations of the bytes defined by the respective constellation interface control documents (ICDs). The android.location format is more aligned with typical mobile devices than existing formats, and includes concepts such as hardware clock discontinuity (to support power-save duty cycling), and received satellite time modulo 1, 2, 4, 10 or 20 milliseconds; 0.6, 1, 2 or 6 seconds; 1 day; or 1 week; depending on the satellite system, and the highest sync state achieved per satellite (such as code lock, bit sync, subframe sync and so on).
This was done because smartphone fixes are often achieved before bit sync, frame sync or time of day/week have been decoded. Thus one can derive Radio Technical Commission for Maritime Services (RTCM) or Receiver-Independent Exchange (RINEX) formats from the Android raw measurements, but not vice-versa without losing information. Developers are encouraged to create RTCM and RINEX logging apps and publish them on the Google Play Store.
The first available Android products with GNSS raw measurements are the following devices running the Android N OS: Nexus 9 tablet, Nexus 5x phone, Nexus 6p phone, Pixel phone and the Pixel XL phone. The raw measurements from Nexus 9 include accumulated delta range (that is, carrier-phase measurements) for GPS and GLONASS. The Nexus 5x, Nexus 6p and Pixel phones track GPS and GLONASS, but the raw measurements from these phones are from GPS only, and do not include carrier phase.
Future Android phones with the Android N (or newer) OS, when paired with GPS chips manufactured in 2016 or later, will support the GNSS raw measurements API.
The Nexus 9 tablet has duty cycling disabled in the forthcoming Android N 7.1 release, so it is suitable for collecting continuous carrier-phase measurements over periods of many minutes. A more detailed explanation of duty cycling is given in a subsequent section of this article.
RAW GNSS MEASUREMENTS
To get a first glance into the quality of the GNSS data provided by a smartphone, a 3-minute data set was collected on August 22, 2016, at the Googleplex, located in Mountain View, California. An engineering build of the Android N OS was used with the Samsung Galaxy S7 smartphone running the Broadcom 4774 GNSS chip. This device enabled logging of carrier-phase, Doppler and pseudorange measurements on the L1 signal for GPS, GLONASS, BeiDou, Galileo and QZSS. However, in the data processing described below, only GPS observations were used.
The GNSS antenna contained within the smartphone uses linear polarization, making it especially susceptible to multipath effects resulting from GNSS signals bouncing off the ground or nearby surfaces before reaching the antenna. In the process of computing the observations, the GNSS receiver must discriminate between the direct signal and the reflected ones, resulting in noisier and possibly biased measurements.
FIGURE 2 shows the carrier-to-noise-density ratio (C/N0) for the signal at the antenna input. Differences in the elevation angle of satellites above the horizon typically explains the differences of C/N0 values among satellites. The sudden sharp variations on all satellites simultaneously can be attributed to the operator touching the phone. The C/N0 values measured in this example are approximately 10 dB-Hz lower than typical values obtained from a geodetic-quality antenna and receiver, which, as we expect, impacts the quality of the smartphone measurements.
FIGURE 2. Carrier-to-noise-density ratio for II tracked GPS satellites.
FIGURE 3. Pseudorange rate and Doppler errors of GPS satellite G29 with respect to carrier-phase measurements.
FIGURE 4. Position estimates using pseudorange data only. The plotted estimates are differences with respect to the mean values in each component.
FIGURE 5 Position estimates using pseudorange and Doppler data. The plotted estimates are differences with respect to the mean values in each component.
For instance, consider GPS satellite G29 that had, on average, the highest C/N0 values in our data set. FIGURE 3 displays, in red, the error in the time variation of the pseudorange with respect to the carrier-phase measurements, computed by differencing both observables between adjacent 1-second epochs. It is clear that, even for the satellite with the strongest signal, the noise level is at the meter level and is about one order of magnitude larger than geodetic-quality measurements. The noise in the Doppler measurements can also be evaluated in a similar fashion, by comparing the mean Doppler value of two epochs with respect to the epoch-difference of carrier phases. Doppler measurements, useful in deriving the velocity of the user (speed and direction), show a much better performance with a precision at the level of a few centimeters per second.
To obtain a better insight into how noisy measurements propagate into position estimates, we show the position errors in the north (latitude), east (longitude) and up (vertical) components in FIGURE 4. To mitigate satellite-related errors, we used precise satellite orbit and clock corrections computed at Natural Resources Canada (NRCan) instead of the broadcast values transmitted in the navigation message of the GPS satellites. Atmospheric delays affecting the propagation of the signals were also accounted for.
The tropospheric delay was computed based on temperature and pressure values provided by the Global Pressure and Temperature (GPT) model, while the ionospheric delay was mitigated by using a global ionospheric map, also computed at NRCan. Additional error sources affecting GNSS observations were also accounted for, such as relativistic effects caused by the Earth’s rotation during signal propagation (a dekameter-level effect often referred to as the Sagnac effect) and the satellite orbit eccentricity (a meter-level effect). Earth tides resulting from the gravitational pull of the sun and the moon (a decimeter-level effect) were also considered, although this error source is not quite perceptible at this point. Measurement weighting was performed using the C/N0 values provided by the smartphone.
Since the exact location of the smartphone is unknown, Figure 4 displays the position estimates with respect to the mean values for each component. With position dilution of precision (PDOP) values between 1.3 and 1.5, an indication of good satellite geometry, the meter-level precisions obtained reflect the quality of the pseudorange measurements. While a meter-level accuracy is sufficient for most applications such as car navigation or finding your friends, the purpose of our study is to determine if it is possible to improve on such results.
As we have seen from Figure 3, Doppler measurements can provide a better estimate of the smartphone velocity. They can be incorporated into a positioning solution by adding velocity states (in the north, east and up directions) and by defining a maximum acceleration for the phone (in this case, it was set to a conservative value of 4.9 ms-2).
FIGURE 5 shows the resulting solution, where the position has a much smoother variation due to the velocity information provided by the Doppler measurements. During the first few epochs, larger residuals for some satellites (at the meter level) were observed for the Doppler observations, which resulted in a poor velocity determination. The original csv format generated by the GnssLogger app also contained the precision of the Doppler observables, which could have allowed for the identification of these outliers, although this information was lost when translating this file to the RINEX format used by the positioning software.
To turn the smartphone into a high-precision positioning tool, it is imperative to make use of carrier-phase measurements, which are at least 100 times more precise than pseudorange measurements. Since a GNSS receiver can only track the change in carrier phases, these measurements contain an unknown offset with respect to a true range measurement, referred to as a carrier-phase ambiguity. This offset is a constant value as long as the receiver continuously tracks the satellite.
When obstructions such as trees, buildings, overpasses, and so on are present between the satellite and the GNSS receiver’s antenna, signal tracking interruptions are likely to occur. In this case, the initial offset value is changed and the carrier-phase ambiguity needs to be reset in the position filter. During poor signal tracking conditions, such as in urban canyons or under a tree canopy, carrier-phase measurements often suffer from many discontinuities and provide little to no benefit to the solution. However, with continuous signal tracking, a much more precise solution can be obtained.
FIGURE 6 shows that the number of ambiguity resets in the data set collected were typically low, except for a few epochs where three or four satellites experienced simultaneous discontinuities. In such instances, it is likely that the solution will not be quite as stable as during continuous tracking on all satellites.
FIGURE 6. Number of carrier-phase ambiguity resets and number of satellites used in the solution.
FIGURE 7. Position estimates using pseudorange, Doppler and carrier-phase data. The plotted estimates are differences with respect to the mean values in each component.
FIGURE 8. Position estimates as in Figure 7 but with precise external ionospheric information.
To exploit the full potential of carrier-phase measurements, a careful modeling of all error sources must be achieved. In addition to the error sources discussed earlier, the so-called carrier-phase wind-up effect caused by the rotation of the satellite antennas as the satellites revolve around Earth was accounted for. High-precision GNSS processing strategies also typically include modeling of the user antenna phase-center variations, although this information is not yet available for smartphone antennas.
As illustrated in FIGURE 7, including carrier-phase measurements in the positioning filter dramatically improved the precision of the position estimates. Notice that the scale of the y-axis has been reduced from ±15 meters in Figure 5 to ± 1 meter in Figure 7. At this point, it should be stressed that the solution is becoming precise, but is by no means accurate. With noisy pseudorange measurements and only three minutes of data, we are still expecting an accuracy of only a few meters. Nevertheless, the displacement measured by the GPS data is now closer to its expected value.
Now, it is still not clear if some of the position fluctuations observed in Figure 7 are caused by the poor quality of carrier-phase measurements or by residual ionospheric effects. To answer this question, we extracted precise slant ionospheric delays from a nearby permanent GPS station operated by UNAVCO (formerly known as the University Navstar Consortium).
This station, labeled SLAC, is located approximately 10 kilometers to the west of the Googleplex. The slightly more stable position estimates obtained, and shown in FIGURE 8, confirm that residual ionospheric errors contaminated the solution shown in Figure 7.
These results demonstrate that, by using carrier-phase measurements and by carefully modeling the error sources affecting GPS observations, it is possible to derive a centimeter-level displacement of the smartphone. Noisier position estimates in Figure 8 correlate well with fluctuations in C/N0 presented in Figure 2 or the ambiguity resets identified in Figure 6, and highlights that careful handling of the phone is required for obtaining such results.
One of the major challenges for smartphone manufacturers is to increase battery life. Since continuous use of the smartphone’s GNSS receiver would quickly drain the battery, the receiver employs a process known as duty cycling; for example, tracking GNSS signals for 200 milliseconds before shutting down for 800 milliseconds, then repeating.
As you can imagine, it is not possible for the GNSS receiver to provide continuous carrier-phase measurements with duty cycling enabled. There is, however, an exception to this process: the receiver remains continually active while decoding the navigation message. From a cold start, it takes several minutes to decode the necessary parts of the message for the satellites in view, providing us with a few minutes of continuous carrier-phase tracking. This workaround was exploited to obtain the data set analyzed in this study, but is definitely not a viable option for real-life applications.
The results presented so far demonstrate that, at this point, precise displacements can be estimated using raw GPS measurements from a smartphone. While this feature can be useful in some applications, it could also be desirable to obtain centimeter-level accuracies with a smartphone.
So, what are the current limitations to performing real-time kinematic (RTK) positioning with smartphones? To answer this question, we need to invoke the concept of ambiguity resolution, the well-known technique in differential positioning allowing precise identification of the integer carrier-phase ambiguities. Ambiguity resolution is the key to centimeter-level accurate positioning since it effectively transforms carrier-phase measurements into very precise range measurements.
However, single-epoch ambiguity resolution requires a very good (decimeter-level or better) initial position. It should be obvious when examining Figure 4 that this condition cannot be satisfied with the current quality of pseudorange measurements. The smartphone antenna is definitely the main culprit for this issue, and the use of an external antenna could be a viable, although cumbersome and expensive, solution. Another option for obtaining centimeter-level accuracies would be to average measurement noise for several minutes while benefiting from the continuity of carrier phases.
In this case, duty cycling is certainly a barrier that needs to be addressed. Smartphone or tablet manufacturers could solve this issue by adding an option to disable duty cycling of the GNSS receiver, such as has been done on the Nexus 9 tablet.
CONCLUSIONS
The Android N operating system now allows us to access raw GNSS measurements from smartphones or tablets through various APIs. Making this data available opens up a world of possibilities to developers for the creation of new applications.
In the study reported in this article, we examined the quality of the data with the purpose of deriving precise positioning information from a smartphone. Our preliminary results confirmed that noisy pseudorange observations can, at the moment, only provide meter-level accuracies. Nevertheless, the current quality of carrier-phase measurements can potentially allow for a precise (centimeter-level) displacement of a smartphone to be computed.
There are still some obstacles preventing smartphones from competing with low-cost RTK units, namely the quality of the antenna and the duty cycling of the GNSS receiver. We hope that, by exposing these shortcomings, the scientific community will find solutions and improve on the results presented herein.
Precise positioning with smartphones will also reveal a plethora of new issues associated with using these devices as high-precision instruments. For example, centimeter-level accuracies can only really be achieved after antenna phase centers have been characterized. Centering of the devices over the point of interest also needs further investigation. The handling of the phone to avoid signal blockages or measurement degradation certainly requires special attention. These areas offer lots of room for improvements and could very well mark the beginning of a new research era in high-precision GNSS positioning.
ACKNOWLEDGMENTS
We would like to thank Mohammed Khider and Daniel Estrada Alva of Google for creating and publishing the GnssLogger app. We also thank them and Lifu Tang, Marc Stogaitis, Steve Malkos and Wyatt Riley of Google for creating the GNSS raw measurement API. This article is published under the auspices of the NRCan Earth Sciences Sector as contribution number 20160169.
SIMON BANVILLE has been working for the Canadian Geodetic Survey of Natural Resources Canada (NRCan) in Ottawa since 2010 as a senior geodetic engineer where he is involved in precise point positioning using global navigation satellite systems. He received his Ph.D. in 2014 from the Department of Geodesy and Geomatics Engineering at the University of New Brunswick, Canada, under the guidance of Richard B. Langley.
FRANK VAN DIGGELEN leads the Android Location Team at Google in Mountain View, California. He is also a consulting professor at Stanford University, Stanford, California, where he created an online GPS course, offered free through Stanford University and Coursera. Van Diggelen is the inventor of coarse-time GNSS navigation, and co-inventor of the extended ephemeris concept for assisted-GNSS (A-GNSS). He holds over 80 issued U.S. patents on A-GNSS. He is the author of A-GPS, the first textbook on A-GNSS. He received his Ph.D. in electrical engineering from Cambridge University, England.
“Precise Positioning for the Mass Market” by T. Humphreys, K. Pesyna, D. Shepard, M. Murrian, C. Gonzalez and T. Novlan, keynote presentation at the International GNSS Service Workshop, GNSS Futures, Sydney, Australia, February 8–12, 2016. Available on line: (video), (slides)
“Low-Cost Precise Positioning Using a National GNSS Network” by M. Kirkko-Jaakkola, S. Söderholm, S. Honkala, H. Koivula, S. Nyberg and H. Kuusniemi in the Proceedings of ION GNSS+ 2015, the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation, Tampa, Florida, Sept. 14–18, 2015, pp. 2570–2577.
Improved Convergence for GNSS Precise Point Positioning by S. Banville, Ph.D. dissertation, Department of Geodesy and Geomatics Engineering, Technical Report No. 294, University of New Brunswick, Fredericton, New Brunswick, Canada, July 2014. Recipient of The Institute of Navigation Bradford W. Parkinson Award for 2014.
“Coarse-Time Navigation: Instant GPS,” Chapter 4 in A-GPS: Assisted GPS, GNSS, and SBAS by F. van Diggelen, published by Artech House, Boston, Massachusetts, 2009.
The Piksi Multi is a multi-band, multi-constellation receiver for the mass market. Autonomous devices require precision navigation, especially those that perform critical functions. The receiver uses real-time kinematics (RTK) technology, providing location solutions 100 times more accurate than traditional GPS. Piksi Multi supports GPS L1/L2 and is hardware-ready for GLONASS G1/G2, BeiDou B1/B2, Galileo E1/E5b, QZSS L1/L2 and SBAS. The Piksi Multi Evaluation Kit also has been upgraded with all-new components. The new kit contains two Piksi Multi GNSS modules, two integrator-friendly evaluation boards, two GNSS survey-grade antennas and two high-performance radios, so that it can deliver reliability and range — well over 10 kilometers — and all of the accessories required for rapid prototyping and integration.
For dedicated time and frequency transfer applications
The Septentrio PolaRX5TR.
The PolaRx5TR has 544 hardware channels and supports all major satellite constellations including GPS, GLONASS, Galileo, BeiDou, QZSS and IRNSS. A calibration circuit is incorporated to measure and compensate for internal delay, removing the need for calibration using external equipment and ensuring measurement latching is always accurately synchronized with the PPS input. The PolaRx5TR is compliant with the new-format CGGTTS version V2E of Consultative Committee for Time and Frequency (CCTF) recommendations. Also included as standard is Septentrio’s Advanced Interference Mitigation (AIM+) technology, giving outstanding interference robustness in difficult radio environments. Up to eight independent logging sessions can be configured logging to either the 16-GB internal memory or to an externally connected device.
The NCS Titan GNSS simulator has up to 256 channels (and 1024 multipath channels) and up to 4 RF outputs per chassis, providing flexibility and outstanding performance . The extra complexity and cost of using multiple signal generators is avoided, improving reliability without compromising on functionality. Its innovative design allows users configure channels for any GNSS signals and allocate those channels to any of the RF outputs fitted. This flexibility enables the same simulator hardware to be used for an extensive range of tests, for all types of GNSS applications. The NCS TITAN GNSS Simulator was developed in cooperation with WORK Microwave GmbH, Germany.
The GSS200D Interference Detection and Analysis solution, developed with Nottingham Scientific Limited, comprises field-based hardware and a secure data server for automatic capture and analysis of GNSS radio-frequency interference. Deployments of GSS200D probes provide users with a thorough understanding of the RF interference environment at sites of interest. Spirent has already detected thousands of disruptive GPS L1 interference events with its global network of GSS100D detectors. By adding support of additional frequencies and constellations, as well as improving the analysis and reporting, the GSS200D responds to the demand of critical infrastructure and civil aviation customers.
For surveyors, contractors, builders and engineers
The Carlson BRx6 is a multi-GNSS, multi-frequency receiver. It has a multi-band 372-channel GNSS receiver, Athena RTK technology and an integrated Atlas L-band receiver. The BRx6 also contains electronic sensors that measure tilt, direction (electronic compass) and acceleration, supporting Carlson SurvCE’s advanced features such as LDL (live digital level or e-bubble), leveling tolerance, auto by level, tilted-pole correction and advanced stakeout features. SurvCE contains sophisticated checks for compass and acceleration anomalies to ensure accuracy. The BRx6 delivers affordable, high-positional accuracy. Manufactured to Carlson’s exacting specifications by Hemisphere GNSS, the BRx6 can be used as a precise base station or lightweight rover. RTK corrections can be received over UHF radio, cell modem, Wi-Fi, Bluetooth or serial connection.
RTK Assist is a subscription-based service that provides users with satellite-delivered correction data to seamlessly continue centimeter-level accuracy during real-time kinematic (RTK) correction outages caused by communication disruptions. Users are able to maintain RTK-level performance for up to 20 minutes, reducing any associated downtime and optimizing solution productivity. The RTK positioning with correction data is delivered directly to the receiver via satellite, allowing for a continuous centimeter-level solution that is globally available 24/7.RTK Assist is best suited for applications where there are potential obstructions, dead spots or baseline limitations that would cause RTK network correction losses for short periods of time.
The POSPac MMS 8 is GNSS-aided inertial post-processing software for georeferencing data collected from cameras, lidars, multi-beam sonars and other sensors on mobile platforms. POSPac MMS 8 uses the Trimble CenterPoint RTX subscription service to deliver these benefits for mobile mapping from land, air, marine and UAV platforms. With an internet connection, users can achieve centimeter-level accuracy within one hour after data collection — there is no need to wait for delivery of public-domain ephemeris data. Users can map inaccessible regions that have no existing Continuously Operation Reference Stations (CORS) without the cost of deploying local base stations. With Trimble’s private network, users can attain consistent and reliable uptime.
TerraGo GeoPDF software suite version 7 offers new features to enable open, cross-platform, cloud and mobile access to advanced maps, engineering drawings, high-resolution imagery and other types of spatial data assets. Version 7 has tools for publishing GeoPDFs, including TerraGo Publisher for ArcGIS, TerraGo Publisher for ArcGIS Server, TerraGo Composer, TerraGo GeoPDF Platform Toolkit, TerraGo Publisher for Raster and TerraGo Toolbar. Features include PubPy, which extends and enhances integration into ArcGIS ArcPy to enable on-demand web services and GIS portals; and OpenGeoPDF, which adds Open Geospatial Consortium GeoPackage to GeoPDF documents to enable GIS-Lite applications using TerraGo Toolbar 7.0. Other features include mobile-workflow support, advanced layer control and remote desktop.
Aeropoints are desgined for for companies across the industrial sector — including mining, construction, quarries and landfills.
AeroPoints are smart ground-control points designed to make it easy to capture survey–accurate mapping using drones. The portable ground-control markers are visible from the air and capable of quickly capturing their own positions down to 2-centimeter absolute accuracy. AeroPoints work with any camera or drone, and integrate seamlessly with Propeller’s cloud–based data platform and processing engine. They’re solar–powered, durable and weather- resistant, and they don’t require any on-site connection. To use AeroPoints, customers simply lay them down, fly their drone, and then pick them up again. They automatically connect to a wireless or mobile hotspot when back in range to upload captured positional data.
The miniVUX-1UAV is a compact miniaturized 360-degree field-of-view lidar sensor weighing 1.6 kilograms. It is developed for the implementation of emerging survey solutions by small UAS, UAV and Remotely Piloted Aircraft Systems (RPAS). The sensor offers multi-target capability and accuracy using echo digitization and online waveform processing for data acquisition. It is capable of 100,000 measurements per second and offers an operating altitude of 100+ meters. Its small size and low weight make it suitable for mounting under limited weight and space conditions, allowing UAV-based acquisition of survey-grade measurement data for agriculture and forestry fieldwork, archaeology and cultural heritage documentation, glacier and snowfield mapping, and landslide monitoring.
Safer Together is designed to reduce the risk of mid-air collision between aircraft and UAVs. Developed by senseFly and the Air Navigation Pro app makers, it is designed to make the skies a safer place by providing general aviation (GA) pilots and drone operators with awareness of each other’s airborne activities, giving them the knowledge they need to take any actions necessary to avoid mid-air incidents around 200–400 feetabove ground level, where most light-weight drones fly. SenseFly added GA functionality to its eMotion flight-planning software, enabling operators to create a special advisory when activating automated drone flights. eMotion transmits the advisory to Air Navigation Pro’s server, which will push the information to all smart devices of connected app users. In turn, senseFly drone operators will be able to view the Air Navigation users’ flights in real time.
The Geo-iNAV 1000 SAASM is a low-cost, rugged SAASM GPS-aided inertial navigation system. It tightly couples a SAASM GPS sensor with a high-stability Quartz micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) to provide a high-performance navigation solution in challenging environments. Features include simple integration, SAASM GPS with path to M-code, internal high-accuracy quartz MEMS IMU, tight-coupling with Geodetics’ Extended Kalman Filter, in-motion dynamic alignment, and RS-232, RS422 and Ethernet (TCP/UDP) interfaces.
The Hover Camera Passport hovers in place to allow users to quickly and easily take photographs. The self-flying camera is aimed at consumers, flying without the restraints of controllers. Once the camera is unfolded and powered on, the passport can take 13-megapixel photos and 4,000-pixel (4K) video using proprietary embedded artificial intelligence technology. The Hover Camera Passport introduces a new design into the flying camera field, with its propellers and motors encased in a strong, light carbon-fiber structure that ensures fingers can’t slip through during normal use. Features include auto-follow with face and body tracking, 360 spin; orbit; and self-positioning using a combination of sonar, its downward viewing camera and artificial intelligence.
The Karma drone, designed to accompany a GoPro camera, features a compact, fits-in-a-small-backpack design and includes an image-stabilization grip that can be handheld or mounted to vehicles, gear and more. Karma is designed to capture smooth, stabilized video during almost any activity. Compact and foldable, the entire system fits into the included backpack that’s so comfortable to wear during any activity, users will forget they’ve got it on. The game-style controller features an integrated touch display, making it easy to fly without the need for a separate phone or tablet. The three-axis camera stabilizer can be removed from the drone and attached to the included Karma Grip for capturing ultra-smooth handheld and gear-mounted footage.
The Epson Moverio BT-300 augmented reality (AR) smart glasses are light, binocular and transparent with an organic light-emitting diode (OLED) display. Combining silicon-based OLED digital display technology and Android OS 5.1, the Moverio BT-300 enables transparent mobile augmented reality (AR) experiences, including while flying drones. With the DJI GO app and the Moverio glasses, drone pilots are able to see clear, transparent first-person views from the drone camera while simultaneously maintaining their line of sight with their aircraft.The DJI GO app works with the DJI Phantom, Inspire and Matrice series flying platforms as well as the Osmo handheld gimbal and camera.
The GPS-713-GGG-N and GPS-713-GGGL-N ATEX-qualified triple-frequency GNSS antennas come with Inmarsat rejection filters. Hazardous environments — those found on oil platforms, tankers and refineries — require compliance with the European 94/9EC ATEX directive. Based on the company’s Pinwheel technology, both antennas maximize performance with multi-constellation reception of L1, L2, L5 GPS; L1, L2, L3 GLONASS; B1, B2 BeiDou; and E1, E5a/b Galileo frequencies, the company said.The GPS-713-GGGL-N also supports L-band from 1525 to 1560 MHz. Customers can use the same antenna for GPS only, or up to quad-constellation applications, resulting in increased flexibility and reduced equipment costs. The two antennas deliver choke-ring-level antenna performance, but without the size and weight. Both provide enhanced Inmarsat interference rejection, which allows tracking of GNSS signals in the presence of high-powered Inmarsat transmitters typically found on marine vessels.
The GV-86 is a high-sensitivity GPS receiver module supporting dead reckoning, which enables positioning in environments where no GNSS signals can be received, such as tunnels, underground car parking and deep urban canyons. The receiver concurrently receives GPS, SBAS and QZSS satellite signals. The dead-reckoning function is realized by integrating the information from a gyro sensor and a velocity sensor. It has fast time to first fix, and highly improved noise tolerance, and a configurable position output update rate up to 10 Hz (10 times per second.)
SmartNet North America, a high-precision, high-availability network RTK correction service, is assuming operations and incorporating all of the Maine Technical Source (MTS) RTK Network into SmartNet. The merger brings professionals along the East Coast access to a broader coverage area, better geometry and optimized performance.
The MTS RTK Network has two national CORS base stations and 27 base stations covering most of New England. The incorporation of the MTS Network into SmartNet strengthens the network by giving users access to a range of additional tools, including full network quality monitoring and a comprehensive user portal with live status maps and rover management.
The MTS RTK Network has two national CORS base stations and 27 base stations covering most of New England.
Users will also be able to take advantage of immediate enhancements and investments SmartNet is currently making in the New England region. The network will continue to be supported by Maine Technical Source, the authorized sales and support organization for SmartNet solutions on the East Coast.
SmartNet North America is fully open to all makes and models of GNSS equipment and is designed to provide the highest reliability and accuracy 24/7. A variety of different subscription plans are available at the state, regional and national level for any application requiring precision GNSS corrections. The latest expansion brings the total number of SmartNet North America stations to over 1,200 in 40 states and 8 provinces, strengthening SmartNet’s position as the most extensive network coverage of any network service provider on the continent.
“Our commitment to excellence drives us to keep expanding to serve the needs of our customers,†said Wendy Watson, director of reference station operations — GNSS reference networks for SmartNet North America. “Whether it is through enriching our toolsets, adding new stations or incorporating existing networks with the assistance of valuable partners like Maine Technical Source, we will continue to make investments that provide users with the best possible service.”
“The MTS RTK Network was already built on reliable, high-performance Leica Geosystems GPS technology,†said Jim Bosworth of Maine Technical Source. “Now users will have the added benefit of being supported by the industry-leading SmartNet service. The incorporation of the MTS RTK Network into SmartNet is a logical next step in supporting our GPS and GNSS customers in the region.”
Talen-X has been given security approval by the GPS Directorate, allowing BroadSim to create and process Y-Code while in a classified environment.
BroadSim is a software-defined GNSS simulator that enables users to easily model true and spoofed signals. BroadSim was developed to simplify advanced jamming and spoofing scenarios with Navigation Warfare (NAVWAR) testing in mind.
BroadSim supports high dynamics, advanced jamming, spoofing and encrypted military codes.
Powered by Skydel’s SDX 1000-Hz software simulator engine, BroadSim can simulate multiple constellations including GPS, GLONASS, Galileo and BeiDou.
Software features:
Capable of generating and simulating multiple signal types
GPS L1, L2 with C/A, P, Y and M
GLONASS G1 and G2
Galileo E1 and E5
BeiDou B1 and B2
Intuitive control using Skydel’s SDX software
Utilizes four RF outputs, each with multiple simultaneous constellations
Generates high-fidelity jamming and interference signals
BroadSim hardware includes a generator and controller with two integrated commercial-off-the-shelf USRP radios, an integrated OctoClock-G with GPS disciplined oscillator, four frequency-independent transmit and receive channels and a UBX-160 RF daughterboard.
Location, location, location. It’s not just the tagline for real estate and sales; it’s about all of us, all of the time.
Thanks to technology, everything revolves around location these days. It is in our cars, smartphones, exercise trackers, and even our packages. GPS has revolutionized so many things in our lives, but most people do not know how it truly works. They get the general idea of satellites beaming radio signals to Earth and translated into a position on the Earth, but that’s as far as it gets for most.
Understanding the location relationship by points on the face of the Earth is something much more involved and gets quite complicated. Thanks to sophisticated computers and programming power, this complex bundle of formulas and computations are solved behind the scenes with little effort. All we know is that when our location shows up on our phone, we can share it with friends and family, search for the closest coffee shop, or have it tell us how long until we get home.
This also affects professional surveyors more than many of them truly understand. The introduction of GPS has allowed many to produce work products with greater efficiency, but without understanding the true geodesy, math and positional accuracies behind the technology.
Let’s take a look back in time to understand where we have come, to better understand why knowing the basis of datums is so important:
IN THE BEGINNING
Until the early 1900s, surveyors only measured what they could see and didn’t allow for any curvature of the Earth, (it is round, by the way…). Only after the introduction of long-baseline survey projects was there any consideration for adjustment to survey measurements.
Extensive surveying observations were performed nationwide to establish a network of standardized horizontal positions throughout the land. Using least-square adjustment methods originally developed by Carl Friedrich Gauss to help with estimation of orbital movement of the planets, this network was developed using the Clarke Ellipsoid of 1866 with a base point of Meade’s Ranch, Kansas.
The observed location of the initial point was determined at 39°13’26.686” North latitude, 98°32’30.506” West longitude; from here, all latitudes and longitudes are measured using the Clarke Ellipsoid for reference.
This datum, called the North American Datum of 1927 (NAD27), was used extensively by government surveyors and geodesists for many decades, but because of the highly involved mathematics involved in the computations, very few private surveyors were trained to work within the datum.
More than 26,000 survey stations were used in the computation of NAD27, all being manually observed and measured. The electronic distance meter and long-range theodolite help proliferate more reference points over time, but still required heavy-duty computation to determine results for the new positions.
THE COMPUTER AGE
The implementation of computers, both mainframe and personal computers, allowed for further development of programming that analyzed survey data faster and more accurately than humanly possible. This technology allowed geodesists to compute positions with more reliable results, but still lacked significant involvement by professional surveyors.
As I’ve covered in previous articles, the development of a global positioning system by the Department of Defense created the ability to establish locations nearly anywhere. Their work started in the late 1950s with the development of an inter-continental geodetic system (World Geodetic System 1960 or WGS 60) to work with other nations. Continued refinement in the WGS data allowed for the development of a new geodetic datum that would be Earth-centered rather than the fixed-station method used by NAD27.
In addition to the measuring method, there was also a much larger number of monuments now available for implementing into the new system. Approximately 250,000 points were included in the initial database for the new datum along with additional terrestrial and Doppler satellite data to create the North American Datum of 1983 (NAD83). Improvements with NAD83 over NAD27 included the correction and improvement of data distortion from earlier observations through the increased densification of information.
A big difference from the previous datum was the use of the Geodetic Reference System of 1980 (GRS80) instead of the previously implemented Clarke Ellipsoid. It also offered global projection rather than localized realization of data. Because of these large differences based on projection methods, use of a larger ellipsoid and basis of coordinate values, it is somewhat easy to distinguish the difference between the two datums. But like life itself, everything is subject to change.
BUT CHANGE IS INEVITABLE
The National Geospatial-Intelligence Agency (NGA) published a Standardization Document in July 2014 outlining WGS 84, its parameters and history, along with the intended relationship with local geodetic systems.
The standards covered in the document included:
Coordinate Systems
The use of GPS in the development of the WGS84 Reference Frame
Ellipsoid and its defining parameters
Ellipsoidal Gravity formula
Earth Gravitational Model 2008 (EGM2008)
EGM2008 Geoid Model
The World Magnetic Model (WMM)
WGS 84 relationships with other Geodetic Systems
Accuracy of WGS 84 and its models
Implementation Guidelines
NGA continues to improve and refine the WGS 84 reference frame in order to standardize all future GNSS measurement. Let’s take a look at a few more specific characteristics of our current reference frames.
WGS 84 BASICS
The WGS 84 Coordinate System is a Conventional Terrestrial Reference System (CTRS). It has a right-handed, Earth-fixed orthogonal coordinate format. The system origin also serves as the geometric center of the WGS 84 ellipsoid, and the Z-axis serves as the rotational axis of this ellipsoid of revolution.
It was established in 1987 with the intent of aligning with the Bureau International de l’Heure (BIH) Terrestrial System, also known as the BTS reference frame. Initial accuracies of the reference frame were 1-2 meters; ongoing refinement was important to the NGA team and development continued.
The WGS 84 Reference Frame has been updated six times, with revisions taking place in 1994, 1997, 2002, 2012 and 2013. These updates are intended to incorporate international conventions and to align with the International Terrestrial Reference Frame 2008 (ITRF2008).
Environmental changes in updated models and methods have begun to make discrepancies in the relationship between the reference frames, so improvements have been made to cause these periodic changes to the WGS 84 frame. The intent and result of each revision has been to improve its accuracy and precision, so applying constraints to WGS 84 in order to align it with ITRF results in maintaining continuity with other GNSS worldwide.
With this latest revision to the WGS 84 reference frame, WGS 84 (G1762), the transformation differences with the International GNSS Service (IGb08) is essentially zero. This means users of the latest version of WGS 84 can use the data in its original state to translate to international measurements when necessary.
ITRF2008 was recently updated to ITRF2014, but maintains its consistent relationship with WGS 84 (G1762) with centimeter-level accuracy.
The original WGS 84 reference frame is still used by most consumer-grade GPS devices (smartphones, vehicle navigation, etc.). It has retained the original major-axis value to eliminate the need for various updates and modifications for these devices and mapping software. This allows existing collections of geospatial data to retain its values and not be subject to transformation or additional computation.
NAD83 BASICS
The NAD83 coordinate reference system is a horizontal adjustment of existing data from previous surveys, Doppler and Very Long Baseline Interferometry (VLBI) data. The geocentric datum is earth-centered/Earth-fixed, utilizes the GRS80 ellipsoid, and is intended to be identical to the original WGS 84 reference frame with the origin at the center of the mass of the Earth.
The implementation of GPS-based data collection uncovered a discrepancy with the originally calculated center of the reference frame of up to 2 meters. This revelation rendered the reference frame flawed under its original configuration with positional errors up to 1-2 meters being commonplace.
By 1997, additional observation data was introduced along with application of high-accuracy reference network (HARN) information to greatly increase horizontal accuracy. This was followed by the addition of continuously operating reference station (CORS) data through 2002, and then by the implementation of the National Spatial Reference System (NSRS) in 2007. The last major re-adjustment occurred in 2011 with more observation and CORS data.
It is from this framework that the State Plane Coordinate (SPC) systems were developed for localized use. Transformation parameters were created to allow smaller coordinate values for easier use in all types for mapping and data collection. This is also where most surveyors were introduced to a simplified form of geodesy, but without the complicated formulas generally associated with its use.
Hardware and software enhancements have made the implementation of SPC systems much easier than past computations. The continued refinement of the NAD83 system through significant adjustments and equipment upgrades has given the surveyor a lot of confidence in this system, but I still caution our profession to promote QA/QC programs to verify the information being collected. GPS data acquisition techniques are not infallible and appropriate caution during use is still required.
SYSTEM COMPARISON
The concept of a world geodetic system is to provide a globally dedicated reference system and to minimize or eliminate the need for local systems. The usual reason for a local coordinate system was to meet the needs for an area before the implementation of a larger system was possible. So often, the worst part of having and maintaining a horizontal system separate from a world system is the means and methods of transformation/translation of data.
In the meantime, here are a few of the main differences between WGS 84 and NAD83:
While both use a similar ellipsoid, they differ slightly and thus create different results.
The coordinate system for WGS 84 is geographic, and the NAD83 system is projected.
WGS 84 values are points in space, while NAD83 coordinates are physical locations on the Earth.
WGS 84 is based upon the NAVSTAR satellite system, and the NAD83 system is based upon a network of ground points, observation data and CORS.
WGS 84 ellipsoid is defined as a geocentric, equipotential frame, whereas NAD83 considers GRAV-D data collection and tectonic plate velocities.
While the original WGS 84 system aligns with the NAD83 (1986) adjustment, further refinement of WGS 84 has been completed to maintain similarity to ITRF realizations.
Until there is a redevelopment of the GPS system (including hardware), we must realize the limitation of each system and work together to make sure the relationship is understood by all who work with it.
DATA COLLECTION NOTES
With the advances in GNSS receivers, data collectors and RTK network opportunities, GPS data has proliferated greatly in the past 20+ years. What began as simple data collection with complex computing necessary to determine positional values has now turned into a plethora of available systems at your fingertips. Surveyors are now considered an “expert” in geodesy overnight, with very little education or knowledge of what they are truly measuring and publishing for coordinate and geodetic values.
A majority of GPS data collection happens in a real-time network (RTN) scenario: (1) with a base station on a published coordinate point or OPUS-derived value, or (2) with a cellular-based RTN. Both situations are typically constrained by built-in NAD83 parameters within the data collector software to produce localized or state plane coordinate values. For projects that rely on these coordinates, these methods are perfectly acceptable.
Where the fork in the road appears is when geodetic values are required for data collection of geographic information system (GIS) database creation. Many GIS users understand the difference between WGS 84 and NAD83 data, whereas the typical professional surveyor does not. The data required for GIS use (such as Esri, Google Earth and Microsoft Virtual Earth) is typically defaulted to WGS 84 because most mapping is done for use by those with the simplest needs: the consumer. Consumers are using GPS in many personal devices, and keeping the programming and mapping requirements simple is key to their success. Excessive accuracy is not necessary when it comes to these devices, so a meter or two variations is perfectly acceptable. That is why the original WGS 84 reference frame is programmed into these devices and is still utilized for most large-scale mapping needs. But what happens when the mapping needs to be more precise?
The need for precise data collection gets us back to the surveying community. Information collected by most surveyors is assumed to be in WGS 84 because “That’s what my data collector told me it was.” Ideally, the best way to gather actual WGS 84 values is to occupy the required locations and collect satellite data using a stationary, dual-frequency GPS receiver and noting the correct epoch and associated fixed-station GPS coordinate data used. Locations derived from data collected in local coordinate systems and transformed to WGS 84 values will be subject to characteristics and distortions potentially affecting the local system. This leads your subject data down an uncertainty path that may not be acceptable to your delivered product.
Typically, data collected in NAD83 (2011) is in the 1- to 2-meter accuracy range from WGS 84 as previous discussed. These accuracies are not usually acceptable in the surveying world and hopefully not in most GIS base-layer situations either.
One of the best solutions for high-accuracy data collection that will be more compatible with GIS database needs is to start your data collection with ITRF-based points, if possible. This method keeps your data consistent with current WGS 84 reference frame parameters and will fit seamlessly into most systems as required. Most hardware and software systems allow for its implementation as a coordinate system option and is just as easy to use as our normal NAD83 based systems. This helps provide less headache with data correlation to the client’s requirements and keeps the playing field closer to level.
For surveyors, here’s the bottom line: our responsibility is to provide the client data in the most accurate and precise condition possible. Our profession needs to re-educate ourselves to better understand what the data collector is truly producing rather than relying on a wing and prayer that it meets the client’s needs.
Think back to your early math class days; we spent many hours learning trigonometry functions by hand before we were turned loose with a calculator with sin, cos, and tan buttons. Learning longhand what was being produced helped us to understand how those complex calculations were completed.
We need to think of this GPS data collection process in the same manner, and not just hope the “ghost in the machine” spits out the right numbers for the project. The worst thing you can tell a client is that you “think” the data is correct because you’re just not sure…
BUT THERE IS GOOD NEWS…
The good news for geographic data users in the United States is that the National Geodetic Survey (NGS) is working on a new datum that will incorporate radical new changes in combining horizontal and vertical datums. Visit the NGS website for more information. The initial framework sounds very robust and user-friendly, so keep your eyes and ears open for more details as they develop. I’m looking forward to the new system and so should surveyors everywhere.
The problem sometimes with technology is that it moves forward so quickly that good innovations get passed over due to previous acceptance and reluctance to upgrade (such as Sony Betamax, Microsoft Zune, etc.). This has been true with geodetic datums and the introduction of GPS for mainstream use. It will be an age-old issue, but I look forward to better and brighter days ahead.
Now, where did I leave my trusty Junior Geodesist Secret Decoder Ring?
NovAtel Inc. has placed a research contract to determine how GNSS technology can deliver a positioning solution that meets both the safety and accuracy requirements of unmanned automotive vehicles.
The research will include study concepts for high-precision, high-integrity carrier phase algorithms as well as threat models and safety monitors with the purpose of improving the safety of autonomous land transportation.
Syntony GNSS, a simulator company based in Toulouse, France, has landed a €1 million location infrastructure project for the underground metro in Stockholm, Sweden.
Stockholm’s metro stations are deep underground, dug under the sea in and around Stockholm. The metro lacked a system that would enable emergency 911 calls with associated essential localized position information to be carried from within the stations.
Syntony was able to provide a GPS-like signal infrastructure at the stations that is compatible with GPS-enabled smartphones. Instead of using Wi-Fi and Bluetooth, the system reproduces the GPS signal with transmitters, a signal recognizable by smartphones. With the system installed, emergency calls can be located in the underground. During its proof-of-concept tests, Syntony verified that there was no radiation of the signal outside any of the entrances to the test station — and therefore no GPS interference.
The system worked so well that Syntony was contracted in January to equip all 50 metro stations in Stockholm. Syntony is now is in talks with Singapore and is working to spread its system to the metros of other major cities worldwide.
An antenna upgrade for U.S. Navy submarines is being provided to improve GPS anti-jamming capabilities.
Mayflower Communications Company, subcontractor to Lockheed Martin Sippican, is applying its Submarine Anti-Jam GPS Enhancement (SAGE) capability to the U.S. Navy Multifunction Mast Antenna System (OE-538B) upgrade to improve submarine communications and meet Navigation Warfare (NAVWAR) requirements.
The SAGE (NavGuard 501) GPS anti-jam unit.
The Mayflower SAGE — a variant of Small Antenna System (SAS) — was developed specifically for inclusion on Submarine Platforms to support U.S. Navy requirements for GPS anti-jam.
The SAGE’s small size and feature set make it capable for ease of integration by Lockheed Martin Sippican into the OE-538B antenna mast.
The SAGE is a high performance and low size, weight and power (SWaP) cost-effective antenna system that will enable the U.S. Navy submarine fleet to operate in GPS contested or denied (NAVWAR) environments.
The SAGE (NavGuard 501) can supply clean GPS Signals to multiple GPS receivers from a single antenna and is compatible with C/A, SAASM P(Y), and M-code receivers. The SAGE fits he small SWaP requirements of the OE-538B antenna mast.
The SAGE is Mayflower’s latest federated, affordable anti-jam solution that leverages proven small antenna system (SAS) technology and provides Iridium capability in an integrated antenna. The SAS solution has been extensively tested by the federal government on multiple platforms.
The SAGE is the highest performance and smallest GPS anti-jam federated solution with Iridium capability in the market. The SAGE AJ solution offers an affordable SWaP-C alternative over larger and more expensive existing anti-jam systems.
The Space and Naval Warfare Systems Command (SPAWAR HQ) awarded the sole source contract for the development of an OE-538B antenna upgrade and procurement to Lockheed Martin Sippican/Granite State Manufacturing Submarine Antenna Joint Venture. The contract is in support of the Program Executive Office for Command, Control, Communications, Computers, and Intelligence (PEO C4I), Undersea Integration Program Office (PMW/A 770).
Mayflower was selected by the U.S. Navy and Lockheed Martin Sippican to design, develop, and integrate the Submarine Anti-Jam GPS Enhancement (SAGE) (NavGuard 501) product.
Joseph Thomas, Mayflower’s Director of Government Programs, said, “The SAGE product has given Mayflower the opportunity to support a U.S. Navy National Strategic Level Platform and to expand into the next generation of small SWaP NAVWAR GPS Anti-Jam systems. The SAGE ensures we can continue to offer the warfighters the very latest and most efficient technology to support operations in an A2AD Environment”.
Mayflower is working closely with Lockheed Martin Sippican to complete integration and environmental qualification of the SAGE to support the OE-538B program requirements.
By Karen Parrish, DoD News, Defense Media Activity
An Air Force program that will provide a vital new command system for the global positioning system satellite constellation in the shortest time possible will continue despite cost growth, Defense Department officials have confirmed.
Frank Kendall, undersecretary of defense for acquisition, technology and logistics, announced Oct. 12 the continuation of an over-cost program supporting the global positioning system. Here, Kendall is briefed by Jose Romero-Mariona on cybersecurity science and technology during Kendall’s visit to Space and Naval Warfare Systems Center Pacific in San Diego, Aug. 24. (Navy photo by Aaron Lebsack)
The next-generation operational control system, known as OCX, reached what is called a Nunn-McCurdy breach on June 30. The Nunn-McCurdy provision applies to weapons programs and requires the military services to notify Congress if a program’s cost per unit increases 25 percent or more over the current baseline estimate.
But well before June 30, defense acquisition experts began working with Raytheon, the contractor for OCX, to resolve program issues. In December 2015, Undersecretary of Defense for Acquisition, Technology and Logistics Frank Kendall directed in-depth quarterly reviews, including a series of “deep dives” overseen by him. Certification activities began in July 2016, and culminated with Kendall certifying the program to Congress yesterday, thus allowing the program to continue.
Next-Generation GPS
James MacStravic, acting assistant secretary of defense for acquisition, discussed OCX and its importance with DoD News.
“This is what the controllers on the ground are going to use to make sure that all the satellites are talking to each other, that they’re exchanging the same information [and] that they’re where they’re supposed to be,” he said.
The OCX system will command all modernized and legacy GPS satellites, manage all civil and military navigation signals and provide improved cybersecurity and resilience for the next generation of GPS operations.
The OCX program includes the following phases: Block 0, to perform launch and checkout of GPS-III satellites; Block 1, to command all navigation signals, including the modernized military signal; and Block 2, for additional enhancements to signal assurance and navigation warfare capabilities. The ground segment capability not only supports military forces, but also civil, commercial and scientific uses. The current total program cost estimate for OCX is $5.46 billion.
OCX will consist of:
A master control station and alternate master control station;
Dedicated monitor stations;
Ground antennas;
GPS system simulator; and
Standardized space trainer
Turning the Program Around
Defense officials said factors in the OCX cost growth included late recognition of the magnitude of information assurance work that was required, concurrent systems engineering that drove significant rework, inconsistent configuration management of the program baselines, immature software and a lack of automation across the program. These issues drove schedule slips, which in turn increased the cost of the program, leading to the breach.
MacStravic described the efforts defense officials and Raytheon have made to turn the program around. He emphasized the work has included the personal involvement of Kendall, Air Force Secretary Deborah Lee James and Raytheon’s chief executive officer.
“What we spent the summer doing was making sure … does this program have the right management resources, the right financial resources and an appropriate schedule to succeed?” MacStravic said.
Officials report that after three on-site quarterly reviews, Kendall’s assessment is that Raytheon is making substantial progress on the program, but that some additional schedule increase has occurred and that there is risk of more schedule increases.
Progress has been sufficient to support certification under the Nunn-McCurdy process, officials said. Kendall’s office will continue the OCX quarterly reviews begun in March 2016, which to date have included the secretary and principal deputy acquisition chief of the Air Force, the program executive officer and Raytheon’s chief executive officer.
The alternatives to certifying the program included several options, including program termination, but this was deemed simply unworkable, due to the extended time it would require to design and field a new ground system for the vital GPS III network.
According to officials, the future of the OCX program will depend upon Raytheon’s ability to demonstrate that it can deliver the needed capability to the Air Force at acceptable cost and within an acceptable time.
