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In May the President’s PNT Advisory Board heard a presentation about a National Guard project called NITRO. RNT Foundation President, Dana Goward, recently spoke with the project’s leader, Maj. Gen. Richard R. Neely, Adjutant General, Illinois National Guard, to find out more.

Mr. Goward: Thanks for speaking with us, General. Could you start by telling us what NITRO is and why it’s important?

Maj. Gen. Neely: Of course. NITRO is a project to ensure that the National Guard and our state’s first-responder partners can maintain communications and other critical functions even if we lose GPS timing signals.

NITRO is an acronym for Nationwide Integration of Timing Resiliency for Operations. ]You know how we in the military love our acronyms.

Telecoms and most of the rest of America’s critical infrastructure are dependent on timing from GPS. However, GPS signals are weak, highly vulnerable and under threat.

In addition to bad actors who can and do jam and spoof signals, accidental interference happens all the time. Operations at the Dallas and Denver airports were each interrupted by accident for more than a day last year, for example. A couple of years ago, a passenger airliner almost hit a mountain because of interference with GPS.

Q: It sounds like this is a safety of life issue.

A: It is. Right now, if we lost GPS signals and had to respond to a domestic attack, natural disaster, or other contingency, I am confident there would be additional unnecessary casualties. We are building NITRO so that we can save those lives and keep America safe.

Q: So how does NITRO work?

A: In addition to GPS, it gets multiple sources of space-based and terrestrial time from government and commercial providers. NITRO can use any trusted source. It is not provider- or vendor-specific.

Inputs are combined and compared, matched to the nation’s atomic clocks keeping Coordinated Universal Time, and users are sent the best accurate time multiple ways including over fiber, terrestrial broadcast, and resilient wireless networks.

Another great way in which I think it will be useful: NITRO gives us a common operating picture that can help detect and terminate GPS disruptions and anomalies around the country.

Q: Is the National Guard the only user?

A: Absolutely not! This is a state/federal partnership. The states’ Adjutant Generals are working with their Homeland Security Advisors to make it available to state, local, and tribal first responders. In some instances, also to critical infrastructure.

Even though we are in the early stages of implementation, NITRO is being used by seven states and 256 organizations and it is protecting more than 33 million people, including citizens here in Illinois.

Q: Is NITRO a tasking from the President or Congress? Who told you to do this?

A: NITRO helps execute long standing presidential policy and orders, as well as the recently released National Cybersecurity Implementation Plan. It also meets congressional mandates for backups and alternatives to GPS timing.

However, we created NITRO because we identified a serious threat to the National Guard’s mission execution. It closes 11 operational gaps for us, all without changes to end-user equipment.

Q: With what groups are the NITRO team working?

A: All the states are involved through their adjutant generals, homeland security advisors, and emergency managers. The NITRO board I chair is made up of the adjutant generals from six states.

We are also coordinating across the federal government, especially with the Departments of Homeland Security, Transportation, Commerce, and Energy.

As part of this we are partnering with the Department of Transportation to establish a NITRO engineering and operational site at Joint Base Cape Cod. This will allow engineers from different organizations to see more easily what we are doing and contribute their expertise.

Q: NITRO is going to provide timing signals in places and at times when GPS is not available. Won’t the National Guard also need navigation information?

A: Positioning and navigation are very important, but not quite as critical as timing. So, we are addressing that problem first. And since wireless location and navigation are often based on timing signals, NITRO will provide a good foundation for services and systems that can augment GPS-based navigation.

Q: So, how is the project going?

A: From a technical and operational standpoint, it’s going great. We have very high satisfaction ratings from NITRO users, and states are eager to be connected as soon as possible.

The technologies used are all mature, reasonably low cost, and most components are commercially available. So, engineering-wise it is low risk.

And our team is doing a great job helping folks move from full dependency on GPS to resilient positioning, navigation and timing (PNT) operations.

Q: Do you have any concerns going forward to full deployment?

A: The only thing I worry about is continued funding. Over the next five years we need something less than the cost of one GPS satellite. You would think that would be easy to find for an important effort like this, but it is a state/federal partnership, not a Department of Defense project. So, it falls into a kind of bureaucratic and budgetary no man’s land.

Q: What’s the solution for funding?

A: That’s not our call. The folks at the White House are exploring several alternatives, and I know several members of Congress are also concerned. We see a possibility of this fitting nicely with the recent infrastructure funding bill.

Q: It sounds like NITRO is something America really needs. Let’s hope they find a solution to the funding challenge, and quickly, to keep you on track. Thank you very much for your time!

A: My pleasure!

Read Richard Langley’s introduction to this article: “Innovation Insights: Falcon Gold analysis redux”

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As part of NASA’s increased interest in returning to the moon, the ability to acquire accurate, onboard navigation solutions will be indispensable for autonomous operations in cis-lunar space (see Figure 1). Artemis I recently made its weeks-long journey to the Moon, and spacecraft carrying components of the Lunar Gateway and Human Landing System are planned to follow suit. During launch and within the GNSS space service volume, space vehicles can depend on the robust navigation signals transmitted by GNSS constellations (GPS, GLONASS, BeiDou, and Galileo). However, beyond this region, NASA’s Deep Space Network (DSN) serves as the system to track and guide lunar spacecraft through the dark regions of cis-lunar space. Increasingly, development of a lunar navigation satellite system (LNSS) that relies on a low size, weight and power (SWaP) “smallSat” constellation is being discussed for various possible orbits such as low lunar orbit (LLO), near rectilinear halo orbit (NRHO) and elliptical frozen orbit (ELFO).

We have implemented direct positioning estimation (or collective detection) techniques to make the most of the limited and weak GPS signals (see Figure 2) that have been employed in other GNSS-degraded environments such as urban canyons. The algorithm used in conventional GNSS positioning employs a two-step method. In the first step, the receiver acquires signals to get a coarse estimate of the received signal’s phase offset. In the second step, the receiver tracks the signals using a delay lock loop coupled with a phase or frequency lock loop. The second step enables the receiver to get fine measurements, ultimately used to obtain a navigation solution. In the scenario addressed in our work, where a vehicle is navigating beyond the GPS satellite constellation, the signals are weak and sparse, and a conventional GPS receiver may not be able to acquire or maintain a lock on a satellite’s sidelobe signals to form a position solution. For a well-parameterized region of interest (that is, having a priori knowledge of the vehicle orbital state through dynamic filtering), and if the user’s clock error is known within a microsecond, a direct positioning estimator (DPE) can be used to improve acquisition sensitivity and obtain better position solutions. DPE works by incorporating code/carrier tracking loops and navigation solutions into a single step. It uses a priori information about the GPS satellites, user location, and clocks to directly estimate a position solution from the received signal. The delay-Doppler correlograms are first computed individually for the satellites and are then mapped onto a grid of possible candidate locations to produce a multi-dimensional spatial correlogram. By combining all signals using a cost function to determine the spatial location with the most correlation between satellites, the user position can be determined. As mentioned, signals received beyond the constellation will be sparse and weak, which makes DPE a desirable positioning method.

BACKGROUND

The proposed techniques draw from several studies exploring the use of weak signals and provide a groundwork for developing robust direct positioning methods for navigating beyond the constellation. NASA has supported and conducted several of the studies in developing further research into the use of signals in this space.

A study done by Kar-Ming Cheung and his colleagues at the Jet Propulsion Laboratory propagates the orbits of satellites in GPS, Galileo, and GLONASS constellations, and simulates the “weak GPS” real-time positioning and timing performances at lunar distance. The authors simulated an NRHO lunar vehicle based on the assumption that the lunar vehicle is in view of a GNSS satellite as long as it falls within the 40-degree beamwidth of the satellite’s antenna. The authors also simulate the 3D positioning performance as a function of the satellites’ ephemeris and pseudorange errors. Preliminary results showed that the lunar vehicle can see five to 13 satellites and achieve a 3D positioning error (one-sigma) of 200 to 300 meters based on reasonable ephemeris and pseudorange error assumptions. The authors also considered using relative positioning to mitigate the GNSS satellites’ ephemeris biases. Our work differs from this study in several key ways, including using real data collected beyond the GNSS constellations and investigating the method of direct positioning estimation for sparse signals.

Luke Winternitz and colleagues at the Goddard Space Flight Center described and predicted the performance of a conceptual autonomous GPS-based navigation system for NASA’s planned Lunar Gateway. The system was based on the flight-proven Magnetospheric Multiscale (MMS) GPS navigation system augmented with an Earth-pointed high-gain antenna, and optionally, an atomic clock. The authors used high-fidelity simulations calibrated against MMS flight data, making use of GPS transmitter patterns from the GPS Antenna Characterization Experiment project to predict the system’s performance in the Gateway NRHO. The results indicated that GPS can provide an autonomous, real-time navigation capability with comparable, or superior, performance to a ground-based DSN approach using eight hours of tracking data per day.

In direct positioning or collective detection research, Penina Axelrad and her colleagues at the University of Colorado at Boulder and the Charles Stark Draper Laboratory explored the use of GPS for autonomous orbit determination in geostationary orbit (GEO). They developed a novel approach for directly detecting and estimating the position of a GEO satellite using a very short duration GPS observation period that had been presented and demonstrated using a hardware simulator, radio-frequency sampling receiver, and MATLAB processing.

Ultimately, these studies and more have directed our research in exploring novel methods for navigating beyond the constellation space.

DATA COLLECTION

The data we used was collected as part of the U.S. Air Force Academy-sponsored Falcon Gold experiment and the data was also post-processed by analysts from the Aerospace Corporation. A few of the key notions behind the design of the experiment was to place an emphasis on off-the-shelf hardware components. The antenna used on board the spacecraft was a 2-inch patch antenna and the power source was a group of 30 NiMH batteries. To save power, the spacecraft collected 40-millisecond snapshots of data and only took data every five minutes. The GPS L1 frequency was down-converted to a 308.88 kHz intermediate frequency and was sampled at a low rate of 2 MHz (below the Nyquist rate) and the samples were only 1- bit wide. Again, the processing was designed to minimize power requirements.

METHODS AND SIMULATIONS

To test our techniques, we used real data collected from the Falcon Gold experiment on a launch vehicle upper stage (we’ll call it the Falcon Gold satellite) which collected data above the constellation on a HEO orbit. The data collected was sparse, and the signals were weak. However, the correlation process has shown that the collected data contained satellite pseudorandom noise codes (PRNs). Through preliminary investigation, we find that the acquired Doppler frequency offset matches the predicted orbit of the satellite when propagated forward from an initial state. The predicted orbit of the satellite was derived from the orbital parameters estimated using a batch least-squares fit of range-rate measurements using Aerospace Corporation’s TRACE orbit-determination software. The propagation method uses a Dormand-Prince eighth-order integration method with a 70-degree, first-order spherical harmonic gravity model and accounting for the gravitation of the Moon and Sun. The specifics of this investigation are detailed below.

The positions of the GPS satellites are calculated using broadcast messages (combined into so-called BRDC files) and International GNSS Service (IGS) precise orbit data products (SP3 files). GPS satellites broadcast signals containing their orbit details and timing information with respect to an atomic clock. Legacy GPS signals broadcast messages contain 15 ephemeris parameters, with new parameters provided every two hours. The IGS supports a global network of more than 500 ground stations, whose data is used to precisely determine the orbit (position and velocity in an Earth-based coordinate system) and clock corrections for each GNSS satellite. These satellite positions, along with the one calculated for the Falcon Gold satellite, allowed for the simulation of visibility conditions. In other words, by determining points along the Falcon Gold satellite trajectory, we determine whether the vehicle will be within the 50° beamwidth of a GPS satellite that is not blocked by Earth.

Figure 3 shows a plot rendering of the visibility conditions of the Falcon Gold satellite at a location along its orbit to the GPS satellite tracks. Figure 4 depicts three of the 12 segments where signals were detected and compares the predicted visibility to the satellites that were actually detected. A GPS satellite is predicted to be visible to the Falcon Gold satellite if the direct line-of-sight (DLOS) is not occluded by Earth and if the DLOS is within 25° of the GPS antenna boresight (see Figure 5).

As a preliminary step to evaluate the Falcon Gold data, we analyzed the Doppler shifts that were detected at 12 locations along the Falcon Gold trajectory above the constellation. By comparing the Doppler frequency shifts detected to the ones predicted by calculating the rate of change of the range between the GPS satellites and modeled Falcon Gold satellite, we calculated the range rate root-mean-square error (RMSE). Through this analysis, we were able to verify the locations on the predicted trajectory that closely matched the detected Doppler shifts.

These results are used to direct our investigations to regions of the dataset to parameterize our orbit track in a way to effectively search our delay and Doppler correlograms to populate our spatial correlograms within the DPE. Figure 6 shows the time history of the difference of predicted range rates on the trajectory and the detected range rates on the trajectory. That is, a constant detected range rate value is subtracted from a changing range rate for the duration of the trajectory and not just at the location on the trajectory at the detect time (dashed vertical line). From this we can see that the TRACE method gives range rates near the detected ranges at the approximate detection time for the 12 different segments.

Excluding Segment 12, which was below the MEO constellation altitude, Segment 6 has more detected range rates than that of the other segments. On closer inspection of this segment, and using IGS precise orbit data products, it appears that the minimum RMSE of the range rates from the detected PRNs is off from the reported detection time by several seconds (see Figure 7). Investigating regions along the Falcon Gold TRACE-estimated trajectory and assuming a mismatch in time tagging results in a location (in Earth-centered Earth-fixed coordinates) with a lower RMSE for the predicted range rates compared to detected range rates.

To determine the search space for the DPE, we first determine the location along the original TRACE-estimated trajectory with the minimum RMSE of range rates for each segment. Then we propagate the state (position and velocity) at the minimum location to the Segment 6 time stamp. If the time segment has more than three observed range rates (Segment 6 and Segment 12), we perform a least squares velocity estimate using the range-rate measurements, using the locations along the trajectory and selecting the location with the smallest RMSE. Then, for Segment 12, the position and velocity obtained from least squares is propagated backwards in time to the Segment 6 timestamp. All of these points along the trajectory as well as the original point from the TRACE estimated trajectory are used in a way similar to the method of using a sigma point filter. Specifically, the mean and covariance of the position and velocity values are used to sample a Gaussian distribution. This distribution will serve as the first iteration of the candidate locations for DPE. There were a total of three iteration steps and at each iteration the range of clock bias values over which to search was refined from a spacing of 1,000 meters, 100 meters, and 10 meters. Also on the third iteration, the sampled Gaussian distribution was resampled with 1,000 times the covariance matrix values in the directions perpendicular to the direction to Earth. This was done to gain better insight into the GPS satellites that were contributing to the DPE solution.

RESULTS

Figure 8 shows the correlation peaks for each of the signals reported to be detected using a 15-millisecond non-coherent integration time within the DPE acquisition. Satellite PRNs 4, 16 and 19 are clearly detected. Satellite PRN 29 is less obviously detected, but the maximum correlation value is associated with the reported detected frequency. However, this is the peak detected frequency only if the Doppler search band is narrowly selected around the reported detected frequency. Similarly, while the peak code delay shows a clear acquisition peak for PRNs 4, 16 and 19, for PRN 29 the peak value for code delay is more ambiguous with many peaks of similar magnitude of correlation power. Figure 8 depicts the regions around the max peak correlation chip delay.

For the first iteration of DPE, the peak coordinated acquisition values for PRN 16 and PRN 4 are chosen for the solution space. From the corresponding spatial correlogram, the chosen candidate solution is roughly 44 kilometers away from the original position estimated using TRACE.
For the second iteration of DPE, the clock bias is refined to search over a 100-meter spacing. The peak values for PRN 16 and PRN 19 are chosen for the solution space and the chosen candidate solution is roughly 38 kilometers away from the original position estimated using TRACE.
For the final iteration, Figures 9 and 10 depict the solutions with the 10-meter clock bias spacing and the approach of spreading the search space over the dimension perpendicular to the direction of Earth. Again, this was done to illustrate how the peak correlations appear to be drawing close to a single intersection location. However, the results fall short of the type of results shown in the spatial correlogram previously depicted in Figure 2 when many satellite signals were detected.

A similar iterative method was followed using not just the four detected PRNs, but any satellite that was predicted to be visible with the relaxed criteria allowing for visibility based on receiving signals from the first and second sidelobes of the antenna. This is predicted using a larger 40° away from the GPS antenna boresight criterion. The final spatial correlogram (Figure 11) shows similar results to the intersections shown in Figure 10. However, there is potentially another PRN shown with a peak contribution near the original intersection point. These results are somewhat inconclusive and will need to be investigated further.

CONCLUSIONS AND FUTURE WORK

Our research investigated the DPE approach of positioning beyond the GNSS constellations using real data. We will further investigate ways to parameterize our estimated orbit for use within a DPE algorithm in conjunction with other orbit determination techniques (such as filtering) as our results were promising but inconclusive. Some additional methods that may aid in this research include investigating the use of precise SP3 orbit files over the navigation message currently used (BRDC) within our DPE approach. Also, some additional work will need to be completed in determining the possibility of time tagging issues that could result in discrepancies and formulating additional methods related to visibility prediction that could aid in partitioning the search space. Additionally, we plan to investigate other segments where few signals were detected, but where more satellites are predicted to be visible (a better test of DPE). Finally, using full 40-millisecond data segments rather than the 15 milliseconds used to date may provide the additional signal strength needed to give more conclusive results.

ACKNOWLEDGMENTS

This article is based on the paper “Direct Positioning Estimation Beyond the Constellation Using Falcon Gold Data Collected on Highly Elliptical Orbit” presented at ION ITM 2023, the 2023 International Technical Meeting of the Institute of Navigation, Long Beach, California, January 23–26, 2023.

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KIRSTEN STRANDJORD is an assistant professor in the Aerospace Engineering Department at the University of Minnesota. She received her Ph.D. in aerospace engineering sciences from the University of Colorado Boulder.

FAITH CORNISH is a graduate student in the Aerospace Engineering Department at the University of Minnesota.

This is an introduction to the August 2023 Innovation article, “Far Out: Positioning above the GPS constellation”

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On October 25, 1997, a defense satellite was launched from Cape Canaveral on an Atlas rocket with a Centaur upper stage. The Centaur went into an elliptical geosynchronous transfer orbit with an apogee close to geostationary orbit radius before releasing the satellite. Bolted to the side of the Centaur was an instrument package containing a GPS digital sensor. This piggyback device was part of an experiment by students at the U.S. Air Force Academy to test some of the concepts of GPS navigation for high-altitude spacecraft.

The sensor captured 40-millisecond samples of GPS L1 signals collected by a patch antenna. The digital samples were downlinked to a ground station in Colorado Springs where they were subsequently processed. The equipment successfully operated from November 3 until at least November 9. During that time, GPS signals were detected across a wide range of altitudes above the GPS constellation including at times when the Falcon Gold antenna was only in view of a GPS satellite’s transmitting antenna sidelobes. The downlinked data was carefully archived. The Falcon Gold experiment was discussed by Thomas Powell of the Aerospace Corporation in an article he wrote for this column in October 1999 entitled “The View from Above: GPS on High-Altitude Spacecraft.”

Fast forward a couple of decades. Researchers at the University of Minnesota are taking a fresh look at the Falcon Gold data using some innovative analysis tools, which may prove beneficial for processing GNSS data from receivers on other satellites flying above the GNSS constellations even all the way to the Moon. In this quarter’s Innovation column, they tell us about their work and its potential benefit.

This Falcon Gold data study is a great example of how archived GNSS data can be reanalyzed with fresh insight and new techniques to milk even more and better results from the data. Another important example is the wealth of data that has been acquired by the International GNSS Service since beginning operations in 1994. The data in the archive is reprocessed from time to time to produce a more consistent long product set for analysis of sources of systematic error and to improve its ultimate accuracy. This results in a better understanding of Earth system dynamics, for example, including plate tectonics. The data from many other GNSS instruments flown in space is also archived allowing look backs for further and more detailed analyses. This includes my GPS Attitude, Positioning, and Profiling (GAP) instrument on the CASSIOPE scientific satellite, now part of ESA’s Swarm constellation. Researchers continue to produce interesting scientific results from the GAP data. So, it’s not always necessary to generate fresh data for a study – useful data may already exist. What’s old can indeed be new again!

ANELLO Photonics has released its GNSS inertial navigation system (INS), which is designed for reliable long-term GPS-denied navigation and localization.

Powered by ANELLO’s optical gyroscope technology and artificial intelligence-based sensor fusion engine, the ANELLO GNSS INS delivers robust, high-accuracy positioning and orientation for applications such as agriculture, construction, trucking, and autonomous vehicles.

The ANELLO GNSS INS comes equipped with unaided heading drift of less than 0.5°/hr, dual multi-band real-time kinematic capable GNSS engines, ASIL-D ready automotive qualified CPU, automotive 2-wire Ethernet, and dual high-speed CAN FD interfaces.

It also features dual RS-232 interfaces, hardware precision time protocol, IEEE 802.1AS. The ANELLO GNSS INS is IP68 waterproof, as well as resistant to dust, salt spray and chemicals.

In a biological preserve in Mexico’s Campeche State, a team of archaeologists have documented pyramids, palaces, a ball court and other remains of an ancient city they call Ocomtún, reported the New York Times.

Archeologists surveyed the site for six weeks in May and June, finding  50-foot-tall (15.2-meter-tall) structures resembling pyramids, as well as pottery and Mayan engravings they believe date to between 600 and 900 AD. The team determined the city was likely abandoned more than 1,000 years ago.

Mexico’s National Institute of Anthropology and History (INAH) hailed their findings late last month, saying they discovered the ancient city in “a vast area practically unknown to archaeology.”

“I’m often asked why nobody has come there, and I say, ‘Well, probably because you need to be a little nuts to go there,” said Ivan Sprajc, the survey’s lead archaeologist and a professor at a Slovenian research center, ZRC SAZU. “It’s not an easy job.”

Surveying the area has been revolutionized over the last decade by lidar — allowing researchers to survey densely forested areas that are difficult to explore on foot. Archeologists were able to use airborne lasers to pierce through dense vegetation and reveal the ancient structures and human-modified landscapes beneath.

INAH described the site as having once been a major center of Mayan life. Surrounded by wetlands, Ocomtún includes pyramids, plazas, elite residences and “strange” complexes of structures arranged almost in concentric circles, Dr. Sprajc told CNN.

“For example, we have several very curious architecture complexes of structures which are arranged in almost concentric circles. So, we are only guessing what this could be. Perhaps marketplaces,” he added.

Mexico’s National Institute of Anthropology and History team plans to return next year for further investigation.

China’s BeiDou GNSS is newer, has more features, is more accurate, and has more satellites in the skies of more nations than the venerable U.S. GPS, according to Sarah Sewall, Executive Vice President for Strategic Issues at IQT.

More than that, it is one example of “a new form of great power competition that most in the U.S. government don’t recognize,” she said. China is providing superior precision, navigation, and timing information to enhance its diplomatic, economic and military power and the United States cannot afford to cede this area of longstanding advantage.

In a recent paper published by Harvard’s Belfer Center for Science and International Affairs, “China’s BeiDou: New Dimensions of Great Power Competition,” Sewall and co-authors Tyler Vandenburg and Kaj Malden outline their finding that China’s version of GPS is part of a longstanding effort to join the technological ranks of leading nations and leverage its capabilities to achieve geopolitical advantage in many areas.

“First, the global reach of BeiDou ensures that the Peoples’ Liberation Army is no longer dependent on another nation’s satnav. China’s economy — and those of other nations relying on BeiDou — can continue to function even if GPS is degraded or denied,” Sewall stated. “This may increase Beijing’s incentives to attack other national satellite capabilities.”

“BeiDou is also an economic driver for the Chinese economy and innovation. The output of China’s commercial space and navigation services industry has increased by tens of billions in the last decade, and new applications such as precision agriculture and self-driving cars show no sign of slowing,” Sewall continued.

The focus of Sewall’s paper, though, is the way BeiDou supports China’s Belt and Road and Digital Silk Road initiatives to gain influence and leverage around the world. She points out that in cases where BeiDou provides the most accurate positioning, navigation, and timing (PNT) data, particularly in the global south, China may be able to hold much of another nation’s economy hostage.

The BeiDou constellation has more satellites than GPS or any other system. It also has more than ten times the monitoring stations in other countries than have been deployed for GPS. As a result, in many places, particularly in the developing world, BeiDou’s accuracy is much better.

Her assessment of BeiDou’s technical superiority received some unexpected support recently from a government advisory board on GPS. It reported that “GPS’s capabilities are now substantially inferior to those of China’s BeiDou,” and urged the administration to regain U.S. leadership in the field.

Being newer and more advanced makes it easier for China to encourage other nations to use BeiDou signals and purchase specialized equipment, especially when equipment purchases are heavily subsidized by the Chinese government.

This is important because systems such as GPS and BeiDou provide more than just directions to the nearest coffee shop. Their precise PNT signals are used for everything from synchronizing cellphone networks and industrial machine controls, to time stamping financial transactions, and coordinating electrical grids. GPS has been called “the silent utility” because signals are used in almost every technology.

“It is very difficult for government leaders in the developing world to turn down discounted infrastructure and opportunities for economic development,” Sewall said. “Even if they know that tying that infrastructure to Chinese signals may give the CCP [Chinese Communist Party] a future on/off switch to their economies.”

The West and the United States in particular, faces challenges confronting China’s efforts with BeiDou, according to Sewall.

“Many in government equate national power with military power, but that’s a narrow and insufficient formulation, particularly in the 21^st century,” Sewall said. “American officials under appreciate China’s efforts to create commercial technology dependencies abroad. The United States has left a vacuum in the developing world that our industry is seemingly unable to fill in the face of competition from Chinese firms that are heavily supported by their government.”

Sewall describes a Chinese “tech stack” being exported that include BeiDou services as part of Belt and Road and Digital Silk Road. It is comprised of a hierarchy of equipment that includes network cables, servers, and cell phones.

“We don’t really have a democratic approach to help foreign nations make meaningful technology choices. We risk ceding global infrastructure to China if we fail to help Western firms offer their own integrated products and services to the developing world,” she said.

If we recognized this new form of great power competition, America could easily leap frog China in areas such as satellite navigation, said Patrick Diamond, a member of the President’s Advisory Board on GPS.

“We could provide higher accuracy GPS and make signals much more secure though internet delivered authentication,” Diamond said. “We could offer complementary terrestrial systems to GPS that would give other nations their own sovereign source of precise time and location while at the same time cooperating with our signals from space.”

“Competing effectively with China in the coming decades will require Americans to think more holistically,” Sewall said, “from realizing that GPS is not just about the military and space, to understanding that national power is more than the ability to prosecute war.”

u-blox has released the LEXI-R4, a module customized for size-constrained application requirements. The device is suitable for small asset trackers, such as pet and personal trackers, micro-mobility devices, and luggage tags.

The LEXI-R4 module supports all LTE-M and NB-internet of things (IoT) bands, with an RF output power of 23 dBm. It is natively designed to support GNSS AT commands, and its dedicated port enables easy integration with any u-blox M10-based GNSS module, such as the MIA-M10.

Additionally, the module can connect to additional positioning services, such as AssistNow and CellLocate.

The compact size of the module, measuring 16 mm x 16 mm, results from a 40% footprint reduction in dimensions compared to the previous u-blox SARA-R4. Due to its small size, remaining space could host larger antennas, which can improve RF performance, or accommodate larger-size batteries.

Another feature of the LEXI-R4 is its 2G fallback capability. Whenever LTE-M/NB-IoT coverage conditions are not optimal, it continues to function by falling back onto a 2G network. The company said this feature could be helpful in countries where LTE-M/NB-IoT networks have yet to be fully deployed.

“Seen & Heard” is a monthly feature of GPS World magazine, traveling the world to capture interesting and unusual news stories involving the GNSS/PNT industry.

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Bikes get tricked out

Snik Bike is a new app-paired tracking device designed to help users track their bikes if they are lost or stolen, reported North Shore News. Snik Bike Security Co-founder Fraser Vaage developed Snik Bike after having two of his bikes stolen. Snik equips any bike with a rechargeable location device that can be installed in five minutes or less. After pairing the device, the bike is automatically registered with Project 529, which is an online bike registration service. Vaage emphasized that while this device is not a ride-tracking software, such as Strava, it acts as an odometer, tracking overall mileage. The battery is only activated when a bike is stolen, Vaage said, therefore, it’s unlikely Snik will run out of battery. However, if it does, the device diverts to AirTag technology as a backup.

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Lighthouses no more

With the wide adoption of GNSS, lighthouses on U.S. shorelines are no longer needed for navigation. To preserve these properties, the General Services Administration has been transferring ownership of the lighthouses to anyone willing to preserve them, reported The Guardian. This year, six lighthouses are being offered to federal, state or local government agencies, non-profits, educational organizations or anyone willing to make them publicly available for educational, cultural, or recreational purposes.

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Location data ad weather resiliency

A Southern Methodist University research team, led by Nicos Markris, measured Dallas’ resilience by recording anonymous cell phone location data among residents in the Dallas metroplex before, during, and after the February 2021 North American winter storm. Measuring a city’s resilience is critical for planning responses to future events and uncovering potential vulnerabilities. By averaging location data, Makris and his team outlined the movement patterns of Dallas residents during a typical week. They compared the normal movement patterns to those during and after the week of the winter storm to determine when Dallas started getting back to normal.

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GPS mitigates natural disasters

NASA’s Jet Propulsion Lab (JPL) is testing new ways to detect tsunami-like ocean waves before they cause catastrophic damage. The GNSS Upper Atmospheric Real-Time Disaster Information and Alert Network (GUARDIAN) is a new experimental monitoring system that can use data from clusters of GPS and other satellites to detect deadly waves triggered on Earth. Radio signals from GNSS are examined by scientific ground stations around the world. That data is then reviewed by the JPL’s Global Differential GPS network to help mitigate disasters. The GUARDIAN is still evolving and may be used in the future to develop early warning strategies, according to the United Nations’ International Committee on GNSS.

Wildfires have recently spread across Greece, Italy, Spain, Portugal, Algeria, Tunisia and Canada, causing mass environmental and economic damage as well as human casualties. Scientists have warned that wildfires are becoming more frequent and more widespread.

In response, an upgraded version of the World Fire Atlas from the European Space Agency (ESA) is now available. The atlas provides a detailed analysis and map of wildfires across the globe.

Rising global temperatures and the increased extreme weather has led to a surge in the number of wildfires rapidly consuming extensive areas of vegetation and forested lands.

Considering the severe wildfires, ESA has reopened its World Fire Atlas which offers an insight into the distribution of individual fires taking place at a global scale.

Through its interactive dashboard, users can compare the frequency of fires between countries as well as analyze the evolution of each wildfire taking place over time. The atlas was first available in 2019 and it supported both European civil protection agencies and firefighters.

The dashboard uses night-time data from the sea and land surface temperature radiometer (SLSTR) on board the Copernicus Sentinel-3A satellite. Working like a thermometer in the sky, the sensor measures thermal infrared radiation to take the temperature of Earth’s land surfaces which is used to detect the fires.

Data from the Copernicus Sentinel-3B satellite will be added to the atlas in December.

Over the previous seven years, data from the World Fire Atlas show a substantial number of fires detected in Portugal, Italy, Greece, France and Spain.

Data also shows that Canada has experienced 11,598 fires during the first seven months of this year alone. This is a 705% increase compared to fires detected over the same period of the previous six years. Canada is currently battling the country’s worst wildfire season on record, with more than 10 million ha of land burned, which is said to increase in the coming weeks.

The Japan Meteorological Agency (JMA) has reported that on July 10-17, data from GNSS signals indicated continuing minor inflation at shallow depths beneath Mount Ioyama, located on the northwest flank of the Karakuni-dake stratovolcano in the Kirishimayama volcano group in Japan.

Shallow volcanic earthquakes were recorded and vigorous fumarolic activity was visible at the fumarolic on the south side of Mount Ioyama. The alert level remained at two, on a five-level scale, and the public was warned to stay 1 km away from Mount Ioyama.

This JMA report was noted on July 18 in the Weekly Volcanic Activity Report, which is a cooperative project between the Smithsonian Institution’s Global Volcanism Program and the Volcano Hazards Program of the U.S. Geological Survey. The report is updated every Wednesday and averages 16 reported volcanoes.