GPS World

Author: Tracy Cozzens

  • Simulation tool verifies GPS/INS integrated systems

    Simulation tool verifies GPS/INS integrated systems

    Image: metamorworks/Shutterstock.com
    Image: metamorworks/ Shutterstock.com

    In ultra-tight with new simulation tool

    A GPS/inertial trajectory data simulation podium can generate simulation data sets for all levels of GPS/INS integration. Here it verifies the operation and performance of a new ultra-tight GPS/INS integrated system, adaptable for both software and conventional hardware receivers.

    Navigation systems for land vehicles, embedded in passenger cars, ambulances, police cars, fire trucks and others, provide reasonable accuracy in open-sky environments, but under conditions such as underpasses and tunnels GPS satellite signals cannot be readily tracked since they are not consistently available or have low signal power. One major factor that directly impacts the effectiveness of receivers in terms of complexity and speed is receiver architecture.

    Scalar (conventional) signal tracking architectures process each satellite signal individually: pseudoranges and pseudorange rate measurements are produced separately and only combined in the navigation filter to generate the required solution. Hence, no information exchange happens between the different tracking channels.

    On the contrary, vector tracking systems combine all the channels in one system along with the navigation filter to produce pseudoranges, pseudorange rates and the navigation solution all at the same time. Figure 1 shows the general architecture of a vector tracking system. Vector-tracking architectures have proven themselves able to provide better performance over scalar tracking systems in challenging environments where most satellite signals are received at low signal-to-noise ratios (SNR).

    Figure 1. General view of the vector-based signal tracking system. (Image: Authors)
    Figure 1. General view of the vector-based signal tracking system. (Image: Authors)

    Any information available about the satellite constellation and user position and dynamics can be used to predict the received signals. Therefore, the best estimation we have for the receiver position and dynamics makes the vector tracking loops more robust. One approach to reduce or perhaps remove the receiver dynamic stress in the signal tracking loops is to provide external aiding information.

    Several sensor types have been augmented with GPS to improve navigation system accuracy and reliability. The most common systems that have been widely augmented with GPS are inertial sensor systems (INS). Because an INS system can provide a continuous solution at a high data rate, it is virtually a twin to the GPS with respect to its widespread use in navigation applications.

    Using the solution obtained from INS, one can estimate a line-of-sight acceleration that can be integrated to obtain a line-of-sight velocity. Car odometers also provide reasonably accurate measurements of the vehicle speed. Incorporating this velocity (from INS or other aiding sources) into tracking-loop computations helps the tracking loop to maintain tracking at a lower bandwidth even when high dynamics are experienced at the receiver. When the aiding source to the GPS signal tracking loops is an INS, the system is known as ultra-tight GPS/INS integration. Figure 2 shows a general block diagram of an ultra-tightly coupled GPS/INS integration system.

    Figure 2. Ultra-tightly coupled GPS/INS integrated system. (Image: Authors)
    Figure 2. Ultra-tightly coupled GPS/INS integrated system. (Image: Authors)

    The ultra-tight GPS/INS integrated system enhances a GPS receiver’s tracking ability in challenging environments and consequently improves navigation availability.

    Loose. The loosely coupled integration mode is easier to implement since the inertial and GPS navigation solutions are generated independently before being weighted together in a separate navigation filter. The advantages of this coupling strategy are that the INS errors are bounded by the GPS updates, the INS can be used to bridge GPS updates, and the GPS can be used to help calibrate the deterministic parts of the inertial errors instantly. The main drawback of this strategy, however, is that it requires at least four satellites in view which cannot always be guaranteed because of signal interruption due to many factors such as signal blockage by trees or tall buildings.

    Tight. The tightly coupled integration mode combines both systems into a single navigation filter. The major limitation of visibility of at least four satellites is removed since this integration mode can provide a GPS update even if fewer than four satellites are visible. The tightly coupled architecture also overcomes the problem of correlated measurements that arises due to cascaded Kalman filtering in the loosely coupled approach. However, these advantages come with the penalty of increased system complexity.

    Ultra-tight. In the ultra-tightly coupled integration approach, the raw measurements come from one step further towards the front end of a GPS receiver, in the form of I (in-phase) and Q ( quadrature ) signal samples. These I and Q measurements are integrated with the position, velocity and attitude of the INS in a complementary filter. The integration of INS-derived Doppler feedback to the carrier tracking loops provides a vital benefit to this system; the INS Doppler aiding removes the vehicle Doppler from the GPS signal. Hence, it results in a significant reduction in the carrier tracking loop bandwidth. In addition, due to lower bandwidths, the accuracy of the raw measurements is further increased.

    The proposed method uses a variant of the Kalman filter as the core of the navigation processor coupled with the inertial sensor’s input in a reduced inertial sensor system (RISS) configuration and car speed odometer; see Figure 3. Additionally, the data sets used in this work are generated using a newly composed GPS/INS trajectory data simulation platform.

    Figure 3. Reduced inertial sensor system (RISS). (Image: Authors)
    Figure 3. Reduced inertial sensor system (RISS). (Image: Authors)

    Secondly, it demonstrates a novel GPS/INS trajectory data simulation podium. This combined simulation system can produce simulation data sets for all levels of GPS/INS integration and is used to verify the operation and performance of the ultra-tight GPS/INS integrated system.

    SYSTEM ARCHITECTURE AND IMPLEMENTATION

    The goal of signal tracking loops is to monitor changes in the main signal parameters, namely, code phase and carrier frequency, to keep the locally generated signal aligned with the received signal. Successful tracking of these variables will provide good estimations of the parameters that are required for the navigation filter to function correctly. Errors in the code phase and carrier frequency are usually represented as:

       (1)

       (2)

    where  and  are the measured and estimated code phases, respectively.  and  are the measured and estimated carrier Doppler frequencies, respectively. These estimated errors at the signal tracking stage are directly linked to the errors in the states at the navigation filter.

    Each tracking channel provides its own measurements based on a discriminator’s output. All the measurements are then processed together in the navigation filter and feedback is provided to each channel based on the obtained navigation solution results. The filter will process the error signals received from the discriminators in the form of code phase error  and frequency error . Thus, the measurements of the filter will be pseudorange errors and pseudorange rate errors.

      (3)

      (4)

    Where fcode is the code frequency = 1.023 x 106 Hz, fcarrier is the nominal L1 frequency = 1575.42 MHz, and η represents the measurement noise vector.

    The computations of the navigation solution start with a mechanization process where we first calculate pitch, roll and azimuth angles. Knowing the Azimuth and pitch angles, vehicle forward velocity can be projected into East, North and Up velocities. The East and North velocities are transformed into geodetic coordinates and then integrated over the sample interval to obtain positions in latitude and longitude. The vertical component of velocity is integrated to obtain altitude. At this stage, we run the Kalman navigation filter through its two-step known cycle, prediction and update, incorporating any available measurements to estimate the receivers’ new position and velocity. Then, the estimated pseudoranges and pseudorange rates are calculated. Finally, the computed code and carrier frequencies are fed back to control the code and carrier oscillator inputs to align the locally generated signal with the incoming signal.

    COMBINED SIMULATION SYSTEM

    In our work, we combined two existing INS and GNSS simulators to build a comprehensive simulation tool that can produce a limitless number of data sets of repeated trajectories under entirely controlled circumstances. Moreover, these data sets can be used for any level of GPS/INS integration system validation. The system is also used to verify the performance of the above proposed ultra-tight GPS/INS integration system architecture.

    For the GPS data, a satellite navigation simulation signal generator was used to build and generate the desired trajectory. The selected model has the ability to provide dynamic capacity in Doppler and signal power levels as well as adequate channels to simulate line-of-sight and multipath satellite signals. The unit is driven by a software package that comes in different versions; the most powerful version is used in this research to drive the simulation hardware system to generate the output radio frequency (RF) signal.
    A receiver front-end then generates the discretized data stream in the form of in-phase (I) and quadrature-phase (Q) signals. The unit is a rugged dual-frequency L1/L2 front-end intended mainly for software receiver and interference detection systems. The unit is capable of logging L1/L2 data at bandwidths of 2.5 MHz, 5.0 MHz, 10 MHz and 20 MHz with data quantization varying from 1 bit to 8 bits.

    For the INS data sets, the INS simulator, developed by the Mobile Multi-sensor Group at the University of Calgary, is used for simulating inertial measurement unit (IMU) raw data. The INS simulator can virtually generate the raw data measurements of any grade of IMUs such as navigation, tactical and consumer-grade systems. A wide number of sensor errors can be simulated using this software such as bias instability, random walk, scale factor, errors due to thermal drift and g-sensitivity and so on. While the simulator can generate raw IMU measurements using user-defined vehicle motion and dynamics, such as static scenarios, straight line, constant velocities, accelerations, turns and bumpy roads, and it can also accept externally injected vehicle dynamics from real trajectory data.

    Figure 4 shows a high-level diagram of the trajectory data flow from the two arms of the synthesized simulator. Several conversion code scripts were written to convert raw data into the implementation platform workspace format. Both data sets were then merged through the implemented algorithm to provide the navigation solution.

    Figure 4. Data simulation tool flow diagram. (Image: Authors)
    Figure 4. Data simulation tool flow diagram. (Image: Authors)

    Step 1 of Simulation Process. The trajectory design, Figure 5, outlines the general aspects of the process. Among these are the type of platform to be simulated, for example. land vehicles, ships, aircraft and so on; the satellite constellation, typically GPS, Galileo or GLONASS; the environment, whether rural, suburban or urban; and error sources, including ionospheric and tropospheric effects. All of this is done using the simulator’s software.

    Figure 5. Trajectory data flow Step 1. (Image: Authors)
    Figure 5. Trajectory data flow Step 1. (Image: Authors)

    Step 2. This incorporates the implementation of the data stream that is fed into the signal generator hardware, which transforms this into an RF signal (Figure 6). Concurrently, the reference trajectory data is logged on the same computer that hosts the simulation software. The I and Q branches are recorded, simultaneously with the reference trajectory, on a GNSS receiver front-end.

    Figure 6. Trajectory data flow Step 2. (Image: Authors)
    Figure 6. Trajectory data flow Step 2. (Image: Authors)

    Step 3. Finally, the inertial data is simulated. First, the INS simulator is configured according to the desired simulation parameters. Among these are the sensor data rate, grade (or quality) of the selected sensor(s), and some initialization quantities that are obtained from the output of the GNSS signal simulator. Once the configuration process is complete, data extracted from the reference trajectory is converted into a format appropriate to the INS simulator, and the inertial data simulation is performed. At this stage, data from both the GNSS side and INS side can be converted into a format suitable for use by the integrated INS/GNSS system (see Figure 7).

    Figure 7. Data flow, Step 3. (Image: Authors)
    Figure 7. Data flow, Step 3. (Image: Authors)

    EXPERIMENTAL WORK

    Using the complete simulation system, several simulation data sets are used to verify the performance of the proposed algorithm in semi real-life scenarios. Each time a chosen scenario is run on the Spirent GNSS simulator, the software data is applied to the Spirent hardware to generate the RF signal, which is then applied to the input of the front-end unit to provide the corresponding I and Q signal streams. Meanwhile, the trajectory data is logged from the simulator to be used as a reference and then fed to the INS simulator to generate the corresponding raw IMU data. Finally, the I and Q and raw IMU data are combined (when the ultra-tight solution is used) in a software receiver code to extract the ultimate positioning solution. For scalar and vector-based signal tracking, only GPS data is used. One sample trajectory that simulates a land vehicle driving at low speed is selected to show results of the proposed method.

    Table 1 shows initialization of the key parameters during the simulation period. A GPS-only satellite constellation is used. We also limited the maximum number of simulated satellites to seven.

    RESULTS

    The reference solution used to evaluate the proposed method and combined simulation system is the pure data sets extracted from the Spirent GNSS simulator. The figures below show results of 80 seconds of data processing. At around seven seconds of the period, a 43-dB signal drop was applied for 8 seconds on channel number 1, which is assigned to track PRN number 06. A similar signal drop is partially overlapped with this, but was applied for only 5 seconds on channel number 3, which is dedicated to track PRN number 21. The following abbreviations are used in the figures: ST for scalar tracking, VT for vector tracking, and UT for ultra-tight GPS/INS integration system.

    Figure 8 and Figure 9 show the carrier frequency for PRN 06 and PRN 21. Large frequency errors (greater than 100 Hz) are noticeable in the scalar tracking system. The vector tracking system, however, was much less affected, showing more resistance to the drop in signal-to-noise ratio. The ultra-tight GPS/INS integration system was nearly unaffected and maintained a very accurate carrier frequency estimation throughout the simulated trajectory.

    Figure 8. Estimated carrier frequency for PRN #6. (Image: Authors)
    Figure 8. Estimated carrier frequency for PRN #6. (Image: Authors)
    Figure 9. Estimated carrier frequency for PRN #21. (Image: Authors)
    Figure 9. Estimated carrier frequency for PRN #21. (Image: Authors)

    The trend of the position errors is plotted in Figures 10, 11 and 12. The maximum position error was around 15 meters in the case of vector tracking, whereas the maximum position error from the ultra-tight system was below 4 meters in the worst case.

    Figure 10. Position X error. (Image: Authors)
    Figure 10. Position X error. (Image: Authors)
    Figure 11. Position Y error. (Image: Authors)
    Figure 11. Position Y error. (Image: Authors)
    Figure 12. Position Z error. (Image: Authors)
    Figure 12. Position Z error. (Image: Authors)

    Velocity errors are depicted in Figures 13, 14 and 15. Velocity errors for the vector tracking system reached about 2 meters per second during the low signal-to-noise ratio period. However, they were only small fractions of a meter per second for the ultra-tight GPS/INS integration system.

    Figure 13. Velocity X error. (Image: Authors)
    Figure 13. Velocity X error. (Image: Authors)
    Figure 14. Velocity Y error. (Image: Authors)
    Figure 14. Velocity Y error. (Image: Authors)
    Figure 15. Velocity Z error. (Image: Authors)
    Figure 15. Velocity Z error. (Image: Authors)

    CONCLUSIONS

    This article shows the performance of a newly proposed ultra-tight GPS/INS integrated system using an RISS that is intended to enhance GPS receivers’ tracking ability in challenging environments, thus improving navigation availability. Additionally, we present a freshly combined GPS/INS trajectory data simulator that can be used to generate simulation data sets for all levels of GPS/INS integration. The two components of the simulator are demonstrated to be perfectly linked. Performance of the algorithm was tested using several trajectories, and the algorithm demonstrated durability against harsh signal degradation. Acceptable position and velocity errors were achieved. Expected future improvements to the algorithm aim to employ longer integration time, and the performance of different grades of IMUs are to be simulated.

    ACKNOWLEDGMENT

    This work described in this article was first presented at the ION GNSS+ 2018 conference in Miami, Florida.

    MANUFACTURERS

    The Spirent GSS6700 Satellite Navigation Simulation Signal Generator was used in these tests, with SimGen software. The NovAtel FireHose front-end generated the discretized data stream.

    MALEK KARAIM is a Ph.D. candidate at the Department of Electrical and Computer Engineering, Queen’s University, Canada. He is working within the Navigation and Instrumentation Research (NavINST) Group at Queens’ University/Royal Military College of Canada.
    MOHAMED YOUSSEF received his Ph.D. degree from the Department of Geomatics Engineering and the Department of Electrical and Computer Engineering, University of Calgary, Alberta, Canada. He leads GNSS R&D activities at Sony North America.
    ABOELMAGD NOURELDIN is a cross-appointment associate professor at the departments of electrical and computer engineering in Queen’s University and the Royal Military College (RMC) of Canada. He is the director of the Navigation and Instrumentation Research Laboratory at RMC.

  • New GPS receiver uses multipath for better time synchronization

    New GPS receiver uses multipath for better time synchronization

    A new receiver for GPS and other GNSS improves time-synchronization accuracy in areas with severe reception conditions, such as among buildings and in mountainous areas.

    The receiver was developed by Nippon Telegraph and Telephone Corporation (NTT) and Furuno Electric Co. Ltd.

    Furuno plans to begin sales of the new GF-88 series time synchronization GNSS receivers in April 2019, and to deploy it widely in fields such as 4G/5G mobile base stations, financial trading, power grids and data centers.

    The GF-88’s new algorithm makes use of multipath signals, those reflected or diffracted from buildings and other structures, which previously inhibited accuracy of time synchronization.

    By integrating a new satellite signal selection algorithm developed by NTT into Furuno’s time synchronization GNSS receiver, in addition to signals from satellites in line-of-sight locations, multipath signals can be used to reduce time error, the companies said.

    In a real multipath reception test environment, time error was reduced to approximately one fifth of earlier values.

    The remarkable result promises to enable time synchronization accuracy close to that obtained in open-sky reception environments with no obstructions, even in environments previously considered poor and unsuitable for accurate time synchronization, such as among buildings or in mountainous areas.

    The companies will exhibit the results at Tsukuba Forum 2018 Oct. 25-26, and at ITSF 2018, in Bucharest, Romania, Nov. 5-8.

    More information is available here.

    Satellite selection algorithm. (Image: NTT/Furuno)
    Satellite selection algorithm. (Image: NTT/Furuno)
    GNSS receiver prototype performance test results, (Image: NTT/Furuno)
    GNSS receiver prototype performance test results, (Image: NTT/Furuno)
  • FAA restricts drones near DOD and USCG ships, subs

    FAA restricts drones near DOD and USCG ships, subs

    The Federal Aviation Administration (FAA) has issued more drone flight restrictions — this time, near U.S. Navy and U.S. Coast Guard vessels operating in the vicinity of Naval Base Kitsap, Washington, and Naval Submarine Base Kings Bay, Georgia.

    Drone operations are required to maintain a distance of at least 3,000 feet laterally and 1,000 feet vertically from the ships and submarines.

    The Ohio-class ballistic-missile submarine USS Nebraska returns to Naval Base Kitsap-Bangor following sea trials. (Photo: U.S. Navy/Lt.Cmdr. Michael Smith, Commander, Submarine Group Nine)
    The Ohio-class ballistic-missile submarine USS Nebraska returns to Naval Base Kitsap-Bangor following sea trials. (Photo: U.S. Navy/Lt.Cmdr. Michael Smith, Commander, Submarine Group Nine)

    At the request of the Department of Defense (DOD) and the United States Coast Guard (USCG), the FAA is using its existing authority under Title 14 of the Code of Federal Regulations § 99.7 — “Special Security Instructions” — to address concerns about potentially malicious drone operations over certain, high-priority maritime operations.

    The special security instructions, provided in an FAA Notice to Airmen (NOTAM), are now in effect. Additional information on these special security instructions includes a visual depiction and geospatial definition of the relevant airspace.

    The FAA also warns drone operators that the USN and USCG vessels are authorized by law to take protective action against drones perceived to be safety or security threats, which could result in seizure, damage or destruction of the drones.

    Operators who don’t comply may face civil penalties and criminal charges.

    Any operator with an overriding reason of public interest or necessity (such as conducting a search-and-rescue mission) to operate their drone in close proximity to the cited USN and USCG vessels must first coordinate with the USN or USCG point of contact.

    In a separate Special Notice Advisory NOTAM, also effective today, the FAA strongly advises drone operators to remain clear of DOD and Department of Energy (DOE) facilities and mobile assets, as well as USCG vessels.

    The notice applies nationwide and alerts operators who ignore this caution and conduct drone flights perceived to be a safety or security threat to these facilities and mobile assets could face a reaction by security forces that results in the interference, disruption, seizure, damage or destruction of their drone.

    Information can be found here on these two NOTAMs, and all of the locations currently covered by § 99.7 restrictions. This website also provides an interactive map, downloadable geospatial data, and other important details. Additional information, including frequently asked questions, is available on the FAA’s UAS website.

  • Fujitsu low-power GNSS module aimed at consumer devices

    Fujitsu has introduced a low-power multi-GNSS module for consumer devices and asset tracking. (Graphic: Fujitsu)
    Fujitsu has introduced a low-power multi-GNSS module for consumer devices and asset tracking. (Graphic: Fujitsu)

    The MSB1054 multi-receiver module requires no external components and has built-in Flash memory, meeting needs of smartwatches, fitness trackers, logistics and navigation.

    Fujitsu Electronics Europe (FEEU) is expanding its ultra-low power portfolio to include a multi-receiver GNSS module: the MSB1054. The ability to receive signals from several satellite systems significantly reduces the time to first fix, providing for faster and more accurate positioning, the company said.

    Photo: Fujitsu
    Photo: Fujitsu

    Besides the GNSS device itself, the MSB1054 provides a built-in RF-front end (SAW filter, low-noise amplifier) as well as a temperature compensated crystal oscillator (TCXO), so with the exception of an antenna no external component is required.

    Furthermore, Fujitsu’s GNSS module is equipped with a built-in Flash memory for quick “hot start” to save the navigation data and further optimize performance.

    With its dimensions of 5.8×6.2×1 millimeters and 3.4 mA current in low-power mode (such as for tracking), the MSB1054 is designed for a variety of applications such as smartwatches, fitness trackers and asset tracking, and can navigate indoors or outdoors, the company added.

  • STMicroelectronics offers connected-car automotive MCU

    STMicroelectronics offers connected-car automotive MCU

    New connected-car automotive microcontroller (MCU) enables secure remote updates and high-speed in-vehicle networking.

    Image: STMicroelectronics
    Image: STMicroelectronic

    STMicroelectronics (ST) has launched a new flagship SPC58 H Line as part of its Chorus series of automotive microcontrollers (MCUs).

    The new line can run multiple applications concurrently to allow more flexible and cost-effective vehicle electronics architectures.

    The SPC58 H line has three high-performance processor cores, more than 1.2MB RAM and powerful on-chip peripherals, the company said.

    As critical vehicle powertrain, body, chassis and infotainment features increasingly become defined by software, securely delivering updates such as fixes and option packs over the air (OTA) enhances cost efficiency and customer convenience, the company said.

    With high security and large on-chip code storage, ST’s Chorus automotive microcontroller is a gateway/domain-controller chip capable of handling major OTA updates securely.

    Two independent Ethernet ports provide high-speed connectivity between multiple Chorus chips throughout the vehicle and enable responsive in-vehicle diagnostics. Also featuring 16 CAN-FD and 24 LINFlex interfaces, Chorus can act as a gateway for multiple ECUs (electronic control units) and support smart-gateway functionality via 2 Ethernet interfaces also on-chip.

    “The way carmakers create, configure, deploy and maintain new vehicles is changing, as software-defined functionality makes advanced features, flexibility and convenience ever more widely accessible,” said Luca Rodeschini, microcontroller business unit director at STMicroelectronics. “Our latest and highest-performing Chorus microcontroller, being OTA-ready and with dual Ethernet ports up to Gigabit speeds, creates a state-of-the-art platform for seamless, safe and secure in-car connectivity and control.”

    To protect connected-car functionalities and allow OTA updates to be applied safely, the new Chorus chip contains a Hardware Security Module capable of asymmetric cryptography. Being EVITA Full compliant, it implements industry-leading attack prevention, detection and containment techniques.

    Some customers have received samples of the SPC58 Chorus H Line microcontrollers in the next generation of smart gateways and central body modules, and are also evaluating the devices for battery-management units and ADAS safety controllers.

  • DroneNode designed to protect outdoor events from UAVs

    DroneNode designed to protect outdoor events from UAVs

    The portable DroneNode. (Photo: DroneShield)
    The portable DroneNode. (Photo: DroneShield)

    DroneShield has launched DroneNode in response to end-user requirements.

    DroneNode is an evolution of the company’s DroneCannon product. It is a portable, compact and inconspicuous counter-drone jamming device that law enforcement can use at large outdoor events without raising public concern.

    DroneNode comes in a portable case approximately 50 x 50 centimeters square. It can be set up in seconds and requires very little training to operate, the company said.

    It can simultaneously jam 2.4 GHz, 5.8 GHz and GNSS L1 and L2 bands up to one kilometer, causing drones to return to their point of origin or land. DroneNode is also effective against swarm attacks. Emergency broadcasts, cellphone communication and other dedicated channels will not be affected.

    According to the company, DroneNode’s covert design makes it a suitable counter-drone solution for public events where protection from drone threats is a priority. Designed within a rugged carry case, DroneNode is easy to transport and is protected from the elements.

    DroneNode is powered by a NATO-approved self contained battery with room for a second battery stored in the accessories tray.

    “The release of DroneNode continues DroneShield’s leadership in drone security for public events,” said Oleg Vornik, DroneShield’s CEO. “DroneShield’s recent credentials in the area include the 2018 Olympics, the 2018 Commonwealth Games, 2018 ASEAN-Australia Special Summit, the 2017 Hawaii Ironman World Championship, and the 2015 to 2017 Boston Marathons. The company’s products are well positioned to protect large public gatherings globally.”

    According to DroneShield, the product is particularly relevant given the recent drone attack on the Venezuelan president and the high-profile mail bomb terrorist attacks in the United States, heightening the awareness of law enforcement globally to potential threats to high-profile political targets.

    A Venezuela soldier received head injuries in the drone attack. (Photo: Released by Xinhua News Agency)
    A Venezuela soldier received head injuries in a the drone attack against the president. (Photo: Released by Xinhua News Agency)

    FCC Authorization Pending. DroneNode and DroneCannon have not been authorized as required by the U.S. Federal Communications Commission (FCC). The devices are not, and may not be, offered for sale or lease, or sold or leased, in the United States, other than to the U.S. government and its agencies, until authorization is obtained.

    The use of such devices in the United States by other persons or entities, including state or local government agencies, is prohibited by federal law. Laws limiting the availability of such devices of certain types of users may apply in other jurisdictions, and any sales will be conducted only in compliance with the applicable laws.

     

  • Microdrones used for Autobahn corridor mapping

    Screenshot: Microdrones video
    Screenshot: Microdrones video

    In Halle, Germany, Microdrones worked with construction company Strabag to fly the mdMapper1000DG above Highway A33 to create a point cloud and orthophoto of a 12-kilometer stretch of the Autobahn.

    The drone was equipped with special transponders to make it visible to German Air Traffic Control, enabling beyond-visual-line-of-sight (BVLOS) flight. BVLOS allows for longer flights that cover more area and capture more data.

    Using the drone for corridor mapping of the Autobahn enables closer inspection and visualization of the highway to find pavement imperfections, road wear and tear, and other potential safety hazards, Microdrones said.

  • GeoDecisions expands geospatial data services with acquisition of WorldView Solutions

    GeoDecisions, Gannett Fleming’s geospatial technology division, has acquired WorldView Solutions, a geographic information systems (GIS) consulting firm based in Richmond, Virginia.

    The acquisition, which became effective Oct. 26, expands the geospatial data services that GeoDecisions provides to commercial clients as well as federal, state and local governments.

    “Consolidation of the geospatial marketplace is necessary for firms to remain competitive and provide the most robust and seamless solutions to clients,” said Brendan Wesdock, MCP, GISP, president of GeoDecisions. “We’ve collaborated with WorldView on many projects, and our corporate cultures, client-centered approach, and long-term business goals are in lockstep. The acquisition makes great sense because, by combining forces, we are better equipped to invest in creating products that push the boundaries of geospatial technology and bring greater value to our clients while advancing an aggressive growth plan to expand our geographic footprint.”

    WorldView has offered geospatial technology solutions for nearly 20 years, providing resource and asset management, machine learning, artificial intelligence and consulting capabilities to the private and public sectors and nongovernmental organizations. The firm’s 45 employees have been retained and there are not any immediate changes in project management or technical staff for existing WorldView projects.

    “Through this acquisition, WorldView’s employees have access to the enhanced capabilities and expanded resources that GeoDecisions and its parent company, Gannett Fleming, bring to the table as a 2,300-person company,” said Jamie Christensen, former president and CEO of WorldView. “Together, we are strengthened in our ability to work with our clients to define their needs and identify the most effective geospatial solutions to solve their complex challenges.”

    GeoDecisions will continue to offer ready-to-install products created by WorldView, including PracticeKeeper, a comprehensive web-based solution that enables soil and water conservation districts, departments of environmental protection, and private entities to track all data related to conservation planning, nutrient management, watershed management, erosion and sediment control, and compliance and complaint management.

    OrbWeaver, a cloud-based geospatial data-mining tool that provides location-based insights to clients across industries, will also remain available. The software uses specified geospatial parameters and datasets along with machine learning algorithms to discover, integrate, and map other relevant target data sources such as environmental conditions, demographic characteristics, transportation infrastructure, and existing businesses.

    For instance, a real estate agent may use the tool to discover, mine, and rank relevant data sets for a full-scope analysis of properties they are considering for purchase.

    According to the companies, WorldView has successfully undertaken many assignments for municipalities, districts and counties, as well as state and federal projects. Recent projects in their portfolio include: the development of the Virginia Department of Environmental Quality’s Land Application Tracking Module to better track the permits and biosolids land application activity throughout the Commonwealth; the implementation of Spotsylvania Utilities Department’s new asset management system, Cityworks; the implementation and maintenance of the Virginia Department of Transportation’s SMART Portal, a web-based solution that collects funding applications and supports statewide prioritization for transportation project selection; the implementation of PracticeKeeper to help Durham County Soil & Water Conservation District develop and manage conservation plans, document best management practices and improve reporting; and processing more than 20 terabytes of raster data for the University of Vermont to categorize the Chesapeake Bay watershed into 12 land-cover types to support the Chesapeake Conservancy’s watershed and storm water management and conservation efforts.

  • Cohda Wireless demos self-driving connected cars on city streets

    Cohda Wireless demos self-driving connected cars on city streets

    Cohda Wireless has successfully demonstrated its connected autonomous vehicle technology in a live trial on the streets of the city of Adelaide, Australia.

    The trial proved the potential for connected self-driven vehicles to make streets safer and that Cohda’s technology is effective even in challenging urban canyons.

    In an area covering two city blocks east of Adelaide’s Victoria Square, the demonstration replicated a scenario that is a daily occurrence on the streets of cities all over the world.

    In the scenario, two vehicles approach a four-way intersection at right angles to each other. Car 2, driven by a human, fails to adhere to the red-light signal and approaches the intersection at speed, intending to “skip” the red light. Car 1, a connected autonomous vehicle, is approaching the intersection from another direction and intends to proceed through the intersection on the green light.

    In a real-life scenario, there would be a risk of a collision as human drivers will invariably approach the intersection when the light is green, fully confident that all other road users will obey the traffic signals. In an instance where Car 2 disobeyed the traffic signal and Car 1 was unable to see the approaching danger, due to visibility being obstructed by buildings or other infrastructure, a collision would be especially likely.

    But as Cohda Wireless’s Chief Technical Officer Professor Paul Alexander explained, if the vehicles were connected using Cohda’s V2X (Vehicle-To-Everything) technology, a potential collision situation would be detected and avoided well in advance of it actually happening.

    “We demonstrated that when vehicles are connected to each other using our smart V2X technology, Car 1, the connected autonomous vehicle, would detect that Car 2 is approaching the red light at speed and is probably not going to stop. This allows the connected autonomous vehicle to pre-emptively identify and respond to the threat by slowing down and stopping.”

    “Cohda’s V2X technology allows vehicles to ‘speak to each other’ to extend their perception horizon,” added Alexander.

    “The technology provides the vehicle with an awareness of its environment and risk factors associated with it, consistently and accurately up to ten times per second, enabling it to make decisions that a human being would not be capable of making as the driver of the vehicle.”

    Cohda’s Smart Cars Smart City initiative was funded by the South Australian Department of Transport and Infrastructure’s Future Mobility Lab Fund. In June this year, Cohda Wireless took ownership of two specially-modified vehicles from the U.S. that it is using in advanced trials of its V2X (Vehicle-To-Everything) technology.

    The two Lincoln MKZ sedans were fitted with the ADAS (Advanced Driver Assistance Systems), ROS (Robot Operating System) various sensors including lidar, radar, cameras, GPS as well as in-vehicle compute platform and Cohda’s GNSS- independent positioning technology.

    The fusion and cooperation of the various sensors and Cohda’s V2X technology augment the vehicles’ perception capability and make the autonomous vehicles features more practical, to include threat detection, the dangers associated with blind intersections and vulnerable road users, the company said.

    “Our goal today was not only to demonstrate the efficacy of our technology in enabling self-driven vehicles to communicate with each other, but also to do so in a city environment where so-called ‘urban canyons’ significantly affect the ability of systems reliant on Global Navigation Satellite Systems (GNSS) to achieve accurate positioning,” Alexander said.

    “The area in the city of Adelaide in which the trial was conducted was one such urban canyon where positioning through GNSS can be off by up to 40 meters, but with our V2X Locate technology positioning accuracy is improved to within a meter.”

    Photo: Cohda Wireless
    Photo: Cohda Wireless

    Cohda Wireless demonstrated the efficacy and accuracy of its V2X-Locate system in a 2017 trial in New York City where it repeatedly demonstrated sub-meter accuracy while driving along Sixth Avenue, which has the tallest buildings in the Big Apple. Comparably tested GPS-based systems were as much as tens of meters off-course, at times showing cars driving through buildings.

    Cohda’s V2X technology underpins and complements other technology used by autonomous vehicles such as cameras, sensors, radars and lidars by enabling cooperative perception.

    “The role of technology in making our roads safer is probably not generally understood but we hope that this demonstration has helped to prove that with the appropriate technology and infrastructure, connected self-driving vehicles are safer to have on our roads than vehicles controlled entirely by human beings,” added Alexander.

  • Autotalks launches vehicle-to-everything chipset

    Graphic: Autotalks
    Graphic: Autotalks

    Israel-based Autotalks has launched what it calls a global V2X (vehicle-to-everything) chipset.

    The chipset supports both dedicated short-range communications (DSRC) and cellular vehicle-to-everything (C-V2X) technology — both allow vehicles to share their location and speed to help prevent accidents and improve the safety of autonomous driving systems, the company said.

    The chipset’s processor also could allow customers to switch between the two standards. It minimizes development, testing and certification efforts for a V2X system to be deployed anywhere via a software-defined toggle between the two V2X technologies.

    Two competing standards

    Automakers have announced intentions to equip their new car models with V2X technology. In recent years, V2X has diverged into two different solutions, DSRC and C-V2X.

    While DSRC-based V2X is deployed in the U.S., Europe and Japan, C-V2X is gaining momentum in other regions. Its fundamentally different architectures have made it difficult to harmonize a single global solution.

    Autotalks’ response is to equip its second-generation chipsets with C-V2X in addition to native support of DSRC.

    Autotalks’ deployment-ready, second-generation V2X chipset supports both DSRC and C-V2X direct communications (PC5 protocol) at the highest security level. According to the company, the chipset supports DSRC based on 802.11p/ITS-G5 standards and C-V2X based on 3GPP specifications.

    Autotalks said its chipsets were designed to meet V2X market requirements and standards, including security, environmental, quality, thermal and other requirements.

  • FCC to vote on allowing US devices to use Galileo

    FCC to vote on allowing US devices to use Galileo

    The U.S. Federal Communications Commission will vote in November on whether to allow U.S. devices to access Galileo.

    The Galileo Order is tentatively on the agenda for the Open Commission Meeting scheduled for Thursday, Nov. 15:

    Galileo Order – The Commission will consider an Order that addresses waivers of certain satellite licensing requirements for receive-only earth stations operating with the Galileo Radionavigation-Satellite Service. (IB Docket No. 17-16)

    “Enabling the Galileo system to work in concert with the U.S. GPS constellation should make GPS more precise, reliable and resilient for American consumers and businesses alike ,” said FCC Chairman Ajit Pai.

    In 2015, the National Telecommunications and Information Administration (NTIA) submitted to the FCC a request from the European Commission to waive certain of the commission’s earth station licensing rules to permit non-federal U.S. receive-only earth stations to operate with Galileo.

    The NTIA recommended grant of the requested waivers, and the International Bureau issued a Public Notice seeking comment on the potential public interest benefits and technical issues associated with the waiver request.

    The FCC is proposing to waive its licensing requirements for non-federal operations with Galileo signals known as E1 and E5, subject to certain technical constraints, officials said.

    The FCC includes conditions to ensure users of satellite-based positioning, navigation and timing services in the United States will benefit from Galileo signals. The systems are interoperable under a 2004 agreement.

    Below is a summary of the order; the full text can be downloaded here.

    • Grant in part the request of the European Commission for waivers of certain of the Commission’s earth station licensing rules to permit non-federal U.S. receive-only earth stations to operate with specific signals of the Galileo GNSS without obtaining a license or grant of market access.
    • Find that the Galileo GNSS is uniquely situated as a foreign GNSS system with respect to the U.S. GPS, since the two systems are interoperable and radiofrequency compatible pursuant to the 2004 European Union/United States Galileo-GPS Agreement.
    • Find that there are significant public interest benefits associated with operations of non-federal U.S. receive-only earth stations with the Galileo GNSS, including increased availability, reliability, and resiliency of position, navigation, and timing services in the United States.
    • Grant the request for operations with the Galileo E1 signal, which is transmitted over the 1559-1591 MHz frequency band.
    • Grant the request, and a waiver of the non-federal portion of the U.S. Table of Frequency Allocations, for operations with the Galileo E5 signal, which is transmitted over the 1164-1219 MHz frequency band.
    • Deny the request for operations with the Galileo E6 signal, which is transmitted over the 1260-1300 MHz frequency band, since there is no federal or non-federal allocation for RNSS in the U.S. Table of Frequency Allocations in that band and grant of waiver could constrain our future spectrum management for non-federal operations in the U.S. in spectrum above 1300 MHz, where potential changes in the non-federal allocation are under consideration.
  • PrecisionHawk joins with DJI to refine airport geofencing

    PrecisionHawk joins with DJI to refine airport geofencing

    New risk-based “bow-tie” zones will help protect aircraft using PrecisionHawk’s Low Altitude Traffic and Airspace Safety (LATAS) platform.

    DJI is improving its geofencing technology to refine the airspace limitations for drone flights near airports, providing smarter protection for airplanes in critical areas.

    DJI has updated Geospatial Environment Online (GEO) Version 2.0, and will phase it in starting in November when the revised zones will take effect for airspace around airports in the United States. Upgrades in other regions will follow.

    Image: DJI
    Image: DJI

    The new system allows GEO to create detailed three-dimensional “bow-tie” safety zones surrounding runway flight paths, and to use complex polygon shapes around other sensitive facilities, rather than simple circles.

    The new restrictions better reflect the actual safety risk posed in those areas, while allowing more flights to the side of runways where risk is substantially lower.

    Runway exclusion zones. DJI’s new geofencing also incorporates the principles of Section 384 of the recently enacted U.S. Federal Aviation Administration (FAA) Reauthorization Act designating the final approach corridor to active runways at major airports to be “runway exclusion zones” for unauthorized drones. DJI customers should update their DJI GO 4 flight control app and aircraft firmware to ensure these improvements are implemented.

    To obtain reliable geospatial information for the enhanced shapes in GEO 2.0, DJI has chosen a new data provider that can provide highly accurate details such as the exact locations of airport runways and facility boundaries.

    PrecisionHawk’s LATAS. In North America, DJI will use data from PrecisionHawk Inc., replacing DJI’s previous geospatial data provider AirMap. Under a partnership agreement, PrecisionHawk’s Low Altitude Traffic and Airspace Safety (LATAS) platform will provide DJI customers with critical airspace information that will position them to fly safely in North America.

    DJI will be able to refine airspace limitations for drone flights near airports, providing smarter protection for drones in critical areas and clarifying restrictions, PrecisionHawk said.

    “PrecisionHawk has a corporate commitment to safely integrating drones into the airspace and enabling complex operations,” said Diana Cooper, senior vice president of policy and strategy at PrecisionHawk. “Through our work under the FAA Pathfinder Program, we have shown how technology can play a critical role in unlocking advanced operations, including beyond visual line of sight flight.”

    GEO 2.0 Development. DJI first created No-Fly Zones for its drones in 2013 and introduced the more refined GEO system three years later, adding live updates and new zones for prisons and nuclear power plants, while providing flexible self-unlocking for professionals.

    Both systems recognized that the overwhelming majority of drone pilots want to fly safely and responsibly, and want an easy-to-use guide to help them understand the airspace so they can do so.

    Image: PixOArtist's rendering of a no-drone sign near an airport. Image: PixOne/Shutterstock.comne/Shutterstock.com
    Artist’s rendering of a no-drone sign near an airport. Image: PixOne/Shutterstock.com

    To develop GEO 2.0, DJI collaborated with general aviation pilots through the Aircraft Owners and Pilots Association (AOPA) and with airports through the American Association of Airport Executives (AAAE) to incorporate their expertise and guidance about air traffic and airports into DJI’s new geofencing methods.

    DJI geofencing uses GPS and other navigational satellite signals to automatically help prevent drones from flying near sensitive locations such as airports, prisons, nuclear power plants and high-profile events.

    In certain locations, a DJI drone cannot take off or fly in a geofenced area without special authorization. Drone pilots with verified DJI accounts can unlock some areas if they have legitimate reasons and necessary approvals, but the most critical areas require special action from DJI to unlock them.

    DJI has streamlined the approval process so professional drone pilots with authorization to fly in sensitive locations can receive unlocking codes within 30 minutes.

    The GEO System. The GEO system previously geofenced a 5-mile circle around airports, with enhanced restrictions in a smaller circle encompassing the airport area.

    GEO 2.0 applies the strongest restrictions to a 1.2 kilometer- (3/4 mile)-wide rectangle around each runway and the flight paths at either end, where airplanes actually ascend and descend. Less strict restrictions apply to an oval area within 6 kilometers (3.7 miles) of each runway.

    This bow-tie shape opens more areas on the sides of runways to beneficial drone uses, as well as low-altitude areas more than 3 kilometers (1.9 miles) from the end of a runway, while increasing protection in the locations where traditional aircraft actually fly.

    Artist's concept of a drone approaching a commercial airliner. Image: PixOne/Shutterstock.com
    Artist’s concept of a drone approaching a commercial airliner. Image: PixOne/Shutterstock.com

    Aviation Parameters. DJI’s new boundary areas around airport runways are based on the International Civil Aviation Organization’s Annex 14 standard for airspace safety near runways and the FAA’s Part 77 parameters for “imaginary surfaces” and air navigation obstructions.

    DJI’s categorization of airports is based on traffic volume principles defined in statutes such as U.S. Title 49 section 47102, and the FAA’s criteria developed in 2012 for categorizing general aviation airports.

    Using these aviation parameters, DJI has aligned its geofencing safety feature to broader understandings of airspace and airport risk. This chart demonstrates how GEO 2.0 applies those detailed, risk-based airspace boundaries to the airspace around airports that can be considered to involve relative high, medium, and low risk (see graphic).

    LATAS. Through its work under the FAA Pathfinder Program, PrecisionHawk has shown how technology such as LATAS can play a critical role in unlocking advanced operations, including beyond visual line of sight flight. LATAS was tested under the Pathfinder Program to facilitate safe beyond visual line of sight operations.

    LATAS brings a combined set of geospatial and software tools to the market. In addition to providing improved geospatial data, the LATAS platform features specialized display elements, including telemetry and access to the Harris real-time manned aircraft feed. Using these elements pilots can easily observe the relative altitude and horizontal separation of intruding aircraft and other mission-critical measures.