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Seen & Heard: Invasive species vs. UAVs and protecting farms with GIS

“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.


I Wonder What’s Under There?

Image: Lokibaho/iStock/Getty Images Plus/Getty Images

Image: Lokibaho/iStock/Getty Images Plus/Getty Images

Researchers at the University of Connecticut have conducted one of the largest understory species mapping projects using satellite data and have published the results of the study in the Remote Sensing of Environment journal. In this study, the researchers proposed an automated dense Sentinel-2 time series-based approach for understory plant communities and created maps of four understory classes that include native shrubs of greenbrier and mountain laurel, invasive shrubs of barberry, and the assemblage of mixed invasives at 10 m resolution in Connecticut’s deciduous forests. The researchers developed a strategy that distinguished plant species with an accuracy of 93% and determined that 53% of Connecticut’s understory is now comprised of invasive plant species such as barberry, bittersweet, winged euonymus (burning bush), and multi-flora rose.


Invasive Species VS. UAVs

Image: Donn Bartram

Image: Donn Bartram

Researchers at West Virginia University are using UAVs to develop tools to detect, map, treat and monitor invasive plant species with a grant from the Richard King Mellon Foundation. Multiflora rose is an invasive shrub that threatens native plants in more than 40 states, including West Virginia and Pennsylvania. This project aims to equip UAVs with sensors to collect environmental data in a designated area of southwestern Pennsylvania over multiple seasons. The research team will use that data, combined with machine learning technology, to develop software that can identify multiflora rose and, eventually, other invasive species.


Protecting Farms with GIS

For farmers, every centimeter counts. ComNav’s AG360 Pro autosteering system controls pass-to-pass accuracy within 2.5 cm. (Photo: Daniel Balakov/E+/Getty Images)

Image: Daniel Balakov/E+/Getty Images

American Farmland Trust (AFT) is partnering with government agencies and advocacy groups in South Carolina to deploy GIS mapping tools to predict areas at the highest risk of development in the state. Palmetto 2040: Visioning Alternative Futures, Launching Solutions is a geospatial modeling and policy analysis tool designed to identify and model future outcomes. This mapping tool will project what land in South Carolina is at highest risk of development by 2040. The analysis will consider both rapid population growth and climate change impact on settlement patterns and agriculture, according to AFT.


USV Take Hurricanes

Image: SailDrone

Image: SailDrone

Saildrone is deploying 12 uncrewed surface vehicles (USV) into the tropical Atlantic and Gulf of Mexico this summer, supporting research by the National Oceanic and Atmospheric Administration (NOAA) to advance hurricane forecasting. Ten USVs will be deployed from St. Thomas, U.S. Virgin Islands; St. Petersburg, Florida; and Charleston, South Carolina; to operate in areas with a high probability of intercepting a storm, as indicated by historical data. Two vehicles will remain on land, ready for quick deployment in the event of an approaching hurricane. NOAA will use the data collected by the USVs to improve hurricane forecast models.

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The power to outpace the threat

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This video is sponsored content by BAE Systems. 

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Mapping Hurricane Idalia

According to the U.S. National Hurricane Center (NHC), Hurricane Idalia made landfall along the Gulf Coast of Florida around 7:45 a.m. EDT on August 30 as a Category 3 hurricane. The NHC is continuing to map the storm’s path, and as of 9:00 a.m. EDT, a catastrophic storm surge was occurring with damaging winds spreading inland over Northern Florida.

Idalia is expected to bring excessive rainfall along its path from Florida through the Carolinas. The heavy rain could shift depending on the storm’s exact path.

Peak storm surge forecast in Florida. (Image: National Hurricane Center)

Peak storm surge forecast in Florida. (Image: National Hurricane Center)

This hurricane and future storms this hurricane season, have the potential to become supercharged as sea surface temperatures have clocked record high temperatures.

Idalia is the ninth named storm to form in the Atlantic in 2023.

In late May, the National Oceanic and Atmospheric Administration (NOAA) predicted that there would be 12 to 17 named storms this year. However, on Aug. 10, NOAA revised its estimate to 14 to 21 storms.

There were 14 named storms last year, after two extremely busy Atlantic hurricane seasons in which forecasters ran out of names and had to resort to backup lists, reported The New York Times.

Readers can stay updated with Hurricane Idalia at the NHC website.

Image: National Hurricane Center

Image: National Hurricane Center

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uAvionix, CAP collaborate to expand low-altitude aircraft data for search and rescue missions

Image: uAvionix

Image: uAvionix

uAvionix has partnered with Civil Air Patrol (CAP) to deploy a DO-260B-compliant, dual-band Automatic Dependent Surveillance-Broadcast (ADS-B) receiver network to complement Federal Aviation Administration (FAA) sensor data with low-altitude aircraft positions in support of CAP’s radar analysis mission.

The ADS-B receiver technology — already in use in Virginia — is designed to shorten the accident-to-rescue time in the National Radar Analysis Team’s search and rescue efforts.

Through the leadership of CAP’s Virginia Wing, members throughout the state have assisted uAvionix in locating suitable receiver sites and supported the installation of small, low-weight FlightStation ADS-B receivers at various airports.

The dual-mode (1090 MHz and 978 MHz) FlightStations receive transponder data from aircraft, which is centrally received and transmitted to the radar team server at Maxwell Air Force Base, Alabama, where it’s combined with FAA sensor data.

The CAP team uses FAA data and advanced technologies in its search and rescue efforts. The team is activated by the Air Force Rescue Coordination Center when there is a report of a possible missing aircraft or crash. Once the team is activated, analysis and actionable data can be provided in minutes to an incident commander, instead of the days or hours required before the team’s creation.

The FlightLine roll-out consists of several ATC grade ADS-B receivers with overlapping coverage, allowing for validation of transmitted ADS-B data and pinpoint multilaterated positions. Traditional ADS-B and radar concentrate mostly on airports and higher altitudes in support of air traffic control.

Most other available data sources largely exclude coverage for 978Mhz transponders, typically used by general aviation aircraft. Virginia is the first state in the U.S. to have complete coverage down to 500 ft of altitude. The new ADS-B is rapidly expanding to other CAP wings across the U.S.

“The introduction of ADS-B has resulted in a significant improvement of general aviation safety,” said Christian Ramsey, managing director, uAvionix. “Expanding on the FAA coverage at lower altitude and for UAT [universal access transceiver] transponders typically carried by general aviation will further enhance the tools used in safety of life activities such as CAP’ ‘s emergency services mission.”

The radar analysis team is calling on all CAP Squadrons to volunteer to host and install additional receivers where additional coverage is needed. Young said his team will prioritize areas where existing coverage is weak.

For more information and to register your squadron for a FlightStation unit, click here.

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Hexagon equips fully autonomous road trains

Image: Hexagon/Mineral Resources

Image: Hexagon/Mineral Resources

Hexagon has partnered with Mineral Resources (MinRes) to provide an autonomous haulage solution for a fleet of 120 fully autonomous road trains in Australia. The company says this will transform safety, productivity and sustainability in the region.

The fully autonomous road trains are a full-site, truck-agnostic solution. The addition of unmanned and autonomous systems will form an essential part of the supply chain for the MinRes Onslow Iron project in Western Australia’s Pilbara region.

The center of the autonomous platooning system is Hexagon’s autonomous solutions stack integrating drive-by-wire technology with an autonomous management system to orchestrate vehicle movement in road train haulage.

“Today’s agreement with MinRes will ensure that off-road transport activities will be safer, more sustainable, and more productive,” Paolo Guglielmini, president and CEO of Hexagon, said. “I’m excited to see how similar solutions can be applied in other off-road markets such as agriculture and heavy industry.”

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Google Maps APIs help map environmental information

Image: Google

Image: Google

Google has released three Google Maps application programming interfaces (APIs) for developers to map solar potential, air quality and pollen levels. The three APIs apply artificial intelligence (AI) and machine learning, along with aerial imagery and environmental data, to provide up-to-date information about these three variables, enabling developers, businesses, and organizations to build tools that map and mitigate environmental impact.

The Solar API utilizes mapping and computing resources to design detailed rooftop solar potential data available for more than 320 million buildings across 40 countries including the United States, France and Japan. To obtain this data, the AI model extracts 3D information about roof geometry from aerial imagery, while considering past weather patterns and energy costs, enabling quicker installation of solar panels.

The Air Quality API shows air quality data, pollution heatmaps, and pollutant details for more than 100 countries around the world. The API validates and organizes several terabytes of data an hour from multiple data sources — including government monitoring stations, meteorological data, sensors and satellites — to provide a local and universal index.

Google Maps uses machine learning and live traffic information to predict different pollutants in an area at a given time. The Air Quality API offers companies in healthcare, the automotive market and other forms of transportation the ability to provide accurate and timely air quality information to their users.

The Pollen API shows current pollen information for common allergens in more than 65 countries. The API provides localized pollen count data, heatmap visualizations, detailed plant allergen information, and actionable tips for allergy-sufferers to limit exposure. To obtain this information, Google Maps uses machine learning to determine where specific pollen-producing plants are located.

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Hemisphere launches GNSS smart antenna

Image: Hemisphere

Image: Hemisphere

Hemisphere has released the A631 GNSS smart antenna for agricultural, marine, GIS, mapping and other applications.

The A631 combines Hemisphere’s Athena GNSS engine and Atlas L-band correction technologies with a new web user interface (WebUI). Optional features include 16 GB of internal storage, Bluetooth and Wi-Fi. The compact antenna is designed for rugged environments and meets IP67 requirements.

With multiple operating modes, A631 can be used as an RTK base station or rover. The device is supported by Hemisphere’s Atlas Portal, which empowers users to update firmware and enable functionality, including Atlas subscriptions for accuracies from meter to sub-decimeter levels.

A631 also supports BaseLink and SmartLink modes. SmartLink allows users to directly connect AtlasLink as an extension to any existing system that has industry-standard connectivity options. BaseLink automatically sets up AtlasLink as a permanent reference station, delivering corrections to any other GNSS receiver being used for positioning.

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Harxon introduces GNSS solution for precision agriculture

Image: Harxon

Image: Harxon

Harxon has launched its TS122 family of smart antennas for demanding precision agriculture applications to increase GNSS availability, accuracy and reliability.

The smart antenna family is designed for high-performance semi-autonomous or autonomous applications that require centimeter-level accuracy – even in highly variable terrain and GNSS-obstructed environments. The TS122 family can be used for agriculture OEMs, integrators that develop precision agriculture solutions, autonomous solution providers and more.

There are two models for the new TS122 smart antenna: EUAA and EUUB. Each model has different performance options to fit users’ individual needs.

TS122 EUAA, with ±10cm P2P accuracy and standalone technology, is best for high-performance semi-autonomous or autonomous applications requiring centimeter-level accuracy, even in challenging GNSS-obstructed environments.

TS122 EUUB has single point 1.5cm circular error probable (CEP) and ±15cm P2P accuracy. Both models support RS-232 serial ports and Bluetooth communication for easy configuration of the smart antenna via users installing a configuration app on a phone or tablets, the company said.

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I/NAV improvements now available to Galileo Open Service users

Image: ESA

Image: ESA

The Galileo Open Service has been upgraded with three features added to its I/NAV message, one of the four message types broadcast by Galileo satellites. These features are now available to all Galileo Open Service users. 

The process of upgrading the Galileo Full Operational Capability constellation satellites has been finalized and the I/NAV improvements are openly accessible through the I/NAV message carried by the E1-B signal. If users have experienced delays when turning on a GNSS device, the recent I/NAV improvements may reduce them significantly, reported the European Union Agency for the Space Programme (EUSPA).   

The I/NAV message is now faster and offers more robust positioning. The Reed Solomon Outer Forward Error Correction (RS FEC2) increases demodulation robustness, which enhances the sensitivity. It also improves the overall time to retrieve clock and ephemeris data (time to CED) with the broadcasting of additional, redundant CED information while allowing for the device to restore potentially corrupted data autonomously. 

The Reduced CED (RedCED) enables fast initial positioning, with lower than nominal accuracy, by decoding a single I/NAV word, while waiting to receive the four I/NAV words carrying the full-precision CED.  

The combination of RS FEC2 and RedCED enables I/NAV to obtain a first course position solution faster and to reduce the time required to obtain a first full accuracy solution (RS FEC2). This translates into a reduced time to first fix (TTFF) for the Open Service users, particularly when operating in harsh environments. 

Additionally, the improvements benefit applications working in assisted GNSS (A-GNSS) mode, through the Secondary Synchronisation Pattern (SSP). In A-GNSS mode, when navigation data is received from non-GNSS channels and the receiver’s knowledge of the Galileo System Time is affected by a relatively large error, typically in the order of a few seconds, the clock uncertainty must be resolved quickly and stably.  

With the I/NAV improvements, receivers will be able to do this via the new SSP feature, thus reducing the TTFF, also in A-GNSS mode. 

For more information, please see the I/NAV Navigation Message Improvements Info Note. 

While the I/NAV improvements are fully operational, EUSPA will launch a testing campaign open to receiver manufacturers, that will consist of several testing windows. The tests will allow the participants to have a confirmation of the correct implementation of the OS SIS ICD 2.0 — i.e., the right processing of the three I/NAV improvements in their products. 

The tests will be conducted at the laboratories of the European Commission’s Joint Research Centre in Ispra, Italy, and of the European Space Agency ESA/ESTEC in Noordwijk, The Netherlands.  

EUSPA will assign each applicant to one of the two laboratories depending on the specific conditions and availability. 

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Faux signals for real results: Spirent Communications / Spirent Federal Systems

An exclusive interview with Mark Holbrow, VP of Product Development, Spirent Communications and Roger Hart, Sr. Director of Engineering, Spirent Federal Systems. For more exclusive interviews from this cover story, click here.


What are your roles?

MH: Our business is based in the UK. I am responsible for the vision and direction of the Technology portfolio required by Spirent’s Positioning Technology business unit.

RH: I am responsible for the U.S. add-on components to the simulator, the restricted signals, and support for the U.S. government labs and contractors.

How have the need for simulation or the requirements for it changed in the past five years, with the completion of the BeiDou and Galileo GNSS constellations, the rise in jamming and spoofing threats, the sharp increase in corrections services, and the advent of new LEO-based PNT services?

MH: I would say that the need for thorough and comprehensive testing has never been greater. That need is being driven on multiple fronts due to the understandable pressure on PNT systems needing to deliver enhanced accuracy, reliability and resilience, in the presence of emerging threat vectors and an expanding application space that’s utilizing ever more complex combinations of new and enhanced signals and sensors of opportunity. Underpinning Spirent’s leadership in ensuring the test needs for this evolving, challenging and increasingly diverse market are its team, its technology and its partners. That team is well-established, dedicated and highly experienced — their sole focus is designing, manufacturing and supporting PNT test solutions. The technology focuses around our pioneering dedicated SDR hardware platform and software simulation engine, which allied provide performance, scalability and flexibility, within an open accessible architecture. In addition, close collaboration with our selected partners ensures the opportunity to support and integrate new and emerging PNT technologies through their tools, applications and hardware.

You mention the advent of LEO. A key reason why Spirent was first to market and successfully supported an early LEO + GNSS receiver test-bed (through close and collaboration with Xona and NovAtel) was driven by team, technology and partners.

Two other important areas that have definitely continued to grow and evolve in importance and priority have to be increased realism and test automation. Both are areas in which Spirent continues to prioritize and invest R&D dollars.

Spirent’s integrated, software-defined wavefront simulation system for a 5-element controlled reception pattern antenna (CRPA). Spirent solutions support 16+ antenna elements. (Image: Spirent)

Spirent’s integrated, software-defined wavefront simulation system for a 5-element controlled reception pattern antenna (CRPA). Spirent solutions support 16+ antenna elements. (Image: Spirent)

With all these additional signals, is it still a single simulator or do you have to somehow split it up into different modules?

MH: Good point. Again, a key element with the Spirent solution is that it is very scaleabale and flexible. Spirent has a generic SDR that can be re-purposed to simulate whatever signals are required. That way, we can compile different signals from either one radio or multiple radios coming from the same system. Together with being able to bring in multiple chassis to gradually grow the simulation solution, while also maintaining for each of those signals the fidelity, channel count, and accuracy that customers demand.

Including every signal currently available?

MH: Absolutely, sir. In fact, signals that are still on the drawing board as well. We can enable the user with effectively an arbitrary waveform simulator or ‘sandbox’ to experiment with different modulation schemes, different chipping rates, codes, bandwidths and navigation data content. So, in addition to using that architecture to generate the signals, we allow customers to experiment with it themselves. That’s certainly accelerated over these last five years, and there’s no sign of it stopping. We’re currently working with customers and partners all over the globe who are developing both brand new and emerging PNT systems, whilst also providing all the vital simulation tools to aid the R&D of existing and planned SIS evolutions.

RH: The increasing number of signals that we can support multiplies the permutations and combinations of test cases that users can do. There is a lot of emphasis also on the user interface side of things, so that from one interface you can also easily control all these interfaces with third-party tools, because proliferation of signals produces a huge possible test volume.

What are the specific challenges in realistically simulating new LEO-based signals and any new services being developed for which you don’t have any live sky signals to record yet, only ICDs and other documents?

MH: Again, great question. The key reason Spirent excels in this arena is that the core simulation engine and SDR are agnostic of the constellation and signal type that’s being generated. So, the underlying principles of accuracy, range rate, pseudo-range control, and delay, together with the RF fidelity from Spirent’s SDR+ Sim engine, can be readily manipulated to simulate the wealth of emerging signals, including LEO.

The other area that becomes very important is that if we do not have sight of the ICD, we can enable customers to use our tools to readily populate elements of that ICD themselves. That way, the best of both worlds is achieved, i.e. a turnkey SIS solution, or we can just enable the customer to do it themselves.

Are accuracy requirements or any other requirements for simulation increasing to enable emerging applications?

MH: They are. Both current and emerging test needs are continuing to drive the need for enhanced simulation realism. Always a tough nut to crack, but our hard-won experience and expertise, allied with continuing adoption of latest-generation technology, is allowing us to take some significant strides forward. Real-world testing has an incredibly important role to play and that’s why at Spirent we continue to invest in and develop the GSS6450 Record & Playback System (RPS). However, we are also on that quest for the ‘Holy Grail’ that has all the well understood and necessary advantages of lab-based testing but with the simulation environment being as true to the real world as possible.

A further area where both current and emerging test needs are demanding more and more from the test environment is resilience testing. Spirent now supports a multitude of vulnerability and corresponding mitigation/prevention test cases. Those test cases become increasingly complex as multiple combinations of the threat/mitigation surface evolve — including jamming, spoofing, cyber-attack and CRPA.

Many of these test cases are driving the state of the art and, especially in the case of CRPA testing, Spirent’s purpose-designed SDR comes into its own. Technology bakeoffs and corresponding customer adoption have shown that only through the use of that dedicated purpose-built technology, the simulator test bed can deliver the necessary carrier and code phase stability, very low levels of uncorrelated noise across antenna elements and high J/S that is demanded.

Again, with respect to flexibility, we also support ways to let customers generate their own IQ data. That data can be streamed into the Spirent simulator and combined sympathetically and coherently with the signals generated inside the platform. So, you can layer new signals on existing ones, or introduce a completely new dedicated IQ stream.Finally, hardware-in-the -loop (HIL) testing requirements continue to be a crucial aspect in test coverage. Whether that application is automotive, projectiles or autonomous vehicles, the need for lower latency and higher 6DOF sampling to capture as many trajectory nuances as possible continues to grow. Spirent’s 2KHz system achieves very high iteration rates (SIR) and <2msec latency.

What are the key differences between your simulators for use in the lab and those for use in the field? I assume that the latter are lighter, smaller, and less power hungry. Do they use modules so that users can pick the ones they need for a particular test?

MH: We do support in-the-field test use cases. Spirent has record-and-replay (RPS) systems to take soundings in a wide-band RF environment, record them, then bring them back into the lab for replay. They are sized to fit into a backpack, battery-powered, accessible, and easy to use.

Recently, we have also taken some of our signal generator IP and been able to create a smaller form factor portable simulator for outside use. Its footprint is considerably smaller than that of one of our lab-based simulators. It’s primarily a mechanism for testing the resilience in the field of devices under test. Armed with a Spirent simulator and the appropriate transmit licenses, a customer can put their DUT through an array of vulnerability test cases in a live real-world environment.

You mentioned licenses. As far as jamming, specifically, and maybe spoofing, I presume that you’ll need a license for a specific time and place and that you will have to be far away from, say, an airport.

Absolutely. Right. The details will vary depending on the jurisdiction, but you will need a license to transmit. And, as you rightly say, often those places will be very remote so as not to interfere with the public. We’ve had instances where we’ll work with a customer who has those appropriate licenses and then we can provide this equipment for them to be able to put it through a battery of tests.

You generate the spoofing in your simulator, of course. Do you also generate the jamming inside the same box or from a separate jammer nearby?

It could be either. We can use our simulators to generate internally wide range of interference signals supporting a wide bandwidth, high max o/p power and large dynamic range. This is especially important in instances of CRPA testing, in which it is vital to accurately reproducing a jamming wavefront commensurate with the arrival angle and delay incident at each antenna element. Correspondingly, we support turn-key solutions to connect, control and integrate 3rd party external signal generators into the test scenario.

Are you at liberty to describe any recent success stories?

We have a Xona simulator. So, this is back on the topic of LEO. We’ve recently released that in partnership with Xona. We are also working closely with Hexagon. All those things I mentioned earlier about enabling the customer to use the flexible features that we have, that is where it came into its own. That’s certainly a significant recent success.

We’re continuing to add many realism-related capabilities, including simulating the vibration and temperature effects of inertial systems. Working with a Swiss partner called Space PNT, we’ve recently introduced another LEO-based product, called SimORBIT. That tool enables us to generate incredibly representative and accurate LEO orbits that also include gravitational effects based upon the SV size. We recently introduced a new software tool to support “GNSS Assurance” requirements.

We have a newly patented cloud-based software application called GNSS Foresight that enables users to understand the GNSS coverage they would expect during a particular time, date location and trajectory inclusive of the 3D environment they would be experiencing. We continue to evolve the tool to support real-time operation to enable it to deliver aiding content to appropriately equipped systems.

We continue to be able to support more and more automation. Automation has always been important, but with ever increasing demands of test asset utilization and in a post-pandemic world of remote working, it’s more important than ever right now. The number of test cases and corner cases required and the amount of equipment, coverage, and efficiency required, which was being demanded by using our kit means that automation is vital. So, we’ve introduced several new automation tools to build up on top of our current SimREMOTE interface.

Spirent has also developed a simulation test solution for the Galileo Open Service Navigation Message Authentication (OSNMA) mechanism. SimOSNMA is designed to work with Spirent’s GNSS simulation platforms to test OSNMA signal conformance, which will bring new levels of robustness for both civilian and commercial GNSS uses. SimOSNMA provides developers with vital new simulation tools to test for OSNMA, the security protocol that enables GNSS receivers to verify the authenticity of signals distributed from the Galileo satellite constellation. Designed to combat spoofing, OSNMA ensures that the data received is authentic and has not been modified in any way. It is currently completing the test phase before its formal launch, and SimOSNMA enables developers to simulate and test OSNMA signals and features, allowing GNSS receiver manufacturers and application developers to accelerate and assure development programs.