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The U.S. Air Force Research Laboratory has pushed back the launch of the Navigation Technology Satellite-3 (NTS-3) until spring 2024 as the debut of the Vulcan Centaur rocket from the United Launch Alliance (ULA) — that NTS-3 was set to be launched on — has been delayed, reported Defense News.

NTS-3 was scheduled to launch later this year aboard and would remain in a near-geosynchronous orbit for an inaugural year of testing. The experimental satellite aims to shape the future of U.S. positioning, navigation and timing capabilities and to help U.S. forces to operate in GPS-denied environments and areas prone to spoofing.

According to Defense News, ULA delayed the debut of the Vulcan Centaur rocket as it is incorporating a fix to a testing anomaly, which was discovered in March.

NTS-3 minimizes the impacts of GPS jamming through rapidly reprogrammable signal waveforms, frequency agility and increased signal strength. Its embedded software and firmware are reprogrammable on-orbit.

When paired with reprogrammable receivers, the U.S. Air Force and U.S. Space Force can react in real time as threats evolve on the battlefield. In addition, NTS-3 has enhanced processors to support more complex signals.

In January, L3Harris delivered the NTS-3 vehicle to Kirtland Air Force Base, New Mexico, to prepare the satellite for launch. The Air Force Research Laboratory and L3Harris are working together to complete space vehicle testing, as well as to launch vehicle integration and enterprise integration to confirm compatibility between the control segment, ground receivers and the satellite vehicle.

Off the coast of Long Island, New York, UAVs are sweeping the ocean patrolling for any danger that may lurk below the water. This follows a recent increase in shark encounters for beachgoers, reported USA Today.

According to George Gorman, the state’s park director in Long Island, there have been five shark bites reported this year as shark season is just beginning.

On July 6, the sighting of a 10-foot shark prompted officials to keep people out of the water at Robert Moses State Park. This is the same Long Island beach that delayed its opening on July 4, after a UAV spotted a school of 50 sand sharks off the coast.

Even if the injuries have not been serious, Gorman and others are concerned by the spike in shark sightings and encounters.

The UAVs conduct three sweeps a day on popular Long Island beaches — once before opening, sometime midday, and a final round before the end of the day.

Cary Epstein, a lifeguard supervisor who pilots UAVs at Jones Beach, explained how UAVs provide additional viewpoints to lifeguards on the beach.

“When you’re up in an elevated lifeguard station or a lifeguard stand, you can see up and you can see out, but you can’t see straight down,” Epstein said. “When we do have sharks that are eating on these fish, it’s very, very clear to us. You could see it, no questions asked.”

Additional state funding has been provided for more advanced UAVs to spot sharks.
New York Governor, Kathy Hochul, recently announced a new program that will provide $1 million toward purchasing 60 new shark-monitoring UAVs. The new devices will build on the enhanced shark safety measures at Long Island state park beaches — including more trained staff, new jet skis, and more buffer zones between swimming areas and fishing areas.

More than 350 UAVs were lost during a practice light display show in Melbourne, Australia, on July 14, ahead of a scheduled performance for the opening of the women’s World Cup.

The UAVs appeared to stop mid-show and plummet into the Yarra River. Divers have since fished out hundreds of the UAVs.

According to the Resilient Navigation and Timing Foundation, the likely cause of the mass-crash was caused by interference with GPS signals. This incident shows that having multiple and robust navigation sources is important for safe UAV operation.

PlantiQ — an atmospheric observing systems company — will begin daily delivery of its signal to noise ratio GNSS-radio occultation (RO) data to the National Oceanic Atmospheric Administration (NOAA) under the NOAA’s IDIQ-2 operational Delivery Order-2.

The NOAA has allocated $59.6 million over the next five years to use commercial satellite data to achieve high-quality weather forecasting and atmospheric research.

“By incorporating PlanetiQ’s commercial high quality GNSS-RO data, coupled with our deep understanding of RO technology, NOAA will have the information to significantly improve short and medium-range weather forecasts, and provide essential insights to enhance climate change research for the government, military and the private sector,” Ira Scharf, PlanetiQ CEO, said.

PlanetiQ supplies GNSS-RO data to NOAA from its growing constellation of satellites, which has become a critical part of the global observing system.

Turf Tank — inventor of an autonomous, GPS-guided line marking robot, built and designed specifically for painting athletic fields — has released the Turf Tank Two.
This robot features dual motor drives for enhanced torque and optimized wheels for traction. On its own and controlled through a tablet, the Turf Tank Two can paint a regulation 11 versus 11 soccer field in less than 24 minutes, a baseball or softball field in less than 11 minutes, a lacrosse field in less than 26 minutes, and a full 100-yard football field in less than 3.5 hours. It can also paint logos and numbers.

The Turf Tank Two is 43 in x 33 in x 22.5 in. It weighs 123 lbs, without paint or the battery installed, and it can hold 5.5 gallons of paint.

Enhanced features of the Turf Tank Two also include a revamped sprayer module and advanced control features — including a redesigned front panel that has convenient pause/resume options with LED indicators displaying the robot’s status and a start/stop sprayer button. An LED indicator also comes on the battery.

Turf Tank Two is both eco- and environmentally friendly, the company says. Its batteries are rechargeable and because of the robot’s precision and accuracy, it uses significantly less paint and eliminates the overspray that is common with either painting by hand or using many of the older paint machines and sprayers in the market.

Guided by GPS, the Turf Tank Two uses a base station to ensure its accuracy. The base station becomes a fixed point from which the robot knows to paint the same exact field every time it is dispatched. The base station communicates with satellites to ensure the accuracy of the field dimensions.

Once the user installs a particular field layout, it becomes a simple drag and drop process through the tablet. From there, it’s as simple as setting one to four points on each field to give the robot a starting point, and then the robot will paint that field autonomously.

Whether preparing for natural disasters or responding to everyday emergencies, first responders depend on the accuracy and dependability of GPS data to keep our communities safe. However, the increasing number and intensity of natural disasters, such as wildfires and hurricanes, and ongoing first responder staffing shortages have pushed the industry to look for ways to combine the tried-and-true benefits of GPS with new artificial intelligence (AI) technology to alert sooner, respond faster, and restore better than ever. The integration of AI’s adaptive learning capabilities with the ability of GPS to operate in areas of low or no connectivity make for cutting-edge emergency service solutions.

New technologies incorporating both AI and GPS have already proven to save time and protect lives by quickly identifying and assessing potential fires. For example, in 2022, Sonoma County, California, used FireScout — an AI-powered fire detection solution — to monitor live footage for signs of fire and alert authorities. In one instance, the county found that FireScout’s AI solution detected and located — using GPS data — a fire 10 minutes before the 911 service was alerted about it, giving responders a head start on containing the fire. FireScout looks to integrate GPS functions more fully into their AI-enabled cameras with exact coordinate information. Investments in innovations that facilitate rapid response to natural disasters will lead to greater safety for first responders and their communities across the country.

One way the industry is investing in GPS-powered AI innovation is through problem-solving competitions such as XPrize Wildfire, which encourages the development of cutting-edge solutions to wildfires. Teams will compete in one of two tracks: the Autonomous Wildfire Response track, which requires teams to combine AI and GPS data to differentiate between high-risk actual fires and decoy fires and then quickly suppress the real fires, and the Space-Based Wildfire Detection and Intelligence track, which requires teams to use satellites to accurately pinpoint fires across vast areas then relay that information to stations on the ground. GPS industry leader Lockheed Martin is providing a $1 million Accurate Detection Intelligence Bonus Prize to the winner of the XPrize Wildfire competition. Competitions such as XPrize Wildfire will result in products that can identify fires faster, reducing response times and minimizing damages to communities.

Additionally, new GPS-powered AI solutions are bringing emergency resources to more people in the wake of hurricanes. In the aftermath of hurricanes, emergency personnel are tasked with identifying and allocating resources to restoration efforts. GPS-powered AI technologies such as the University of Connecticut’s hurricane monitoring system, compare pre-storm and post-storm satellite imagery to spot potential environmental and safety issues, such as flood water or damaged neighborhoods. The system then highlights those areas on a map and shares the coordinates of high-damage areas with emergency personnel. Services such as these support communities and allow restoration efforts to begin sooner with less risk to surveyors and responders.

Beyond natural disasters, GPS also is being used with AI technology to shorten response times for emergency vehicles. Many towns, including St. Louis, Michigan, and Leon Valley, Texas, have implemented AI traffic light systems that use location data to detect the location of ambulances and fire trucks to give the vehicles a path of green lights, clearing out any traffic that might have slowed response times. Similarly, researchers at the University of Southern California are using UAVs — guided and tracked using GPS data — to carry automated external defibrillators (AEDs) to remote locations. These UAVs use coordinates provided by GPS receivers to operate in areas of limited connectivity and AI to determine the most efficient landing locations for different terrains. Ongoing research and further investment into the critical intersections of GPS and AI technology will help promote a safer future by supporting first responders and protecting communities in emergencies.

The GPS Innovation Alliance (GPSIA) welcomes innovations in GPS and AI technologies that continue to revolutionize the way we respond to natural disasters and life-threatening emergencies. GPSIA is proud to support the expansion of these disaster-mitigating solutions by uplifting innovative research and design efforts, promoting new ideas, and ensuring adequate regulation is in place to protect users across the globe.

The Federal Aviation Administration (FAA) has released an implementation plan outlining the steps it and others will need to take to enable advanced air mobility (AAM) operations safely. The plan, called Innovate28, includes various components and a timeline for their implementation to hopefully be completed by 2028.

This plan serves as a foundation for making entry into service routine and predictable by maximizing the use of existing procedures and infrastructure. It addresses how the agency and partners will certify aircraft and pilots, manage airspace access, ensure pilot training, develop infrastructure, maintain security and engage communities.

The plan also includes a planning guide that can be applied to any site, laying out key integration objectives and sequences.

Among the entities that play a role in this plan include: the FAA; the advanced air mobility industry; labor partners, NASA; United States Department of Homeland Security; United States Department of Energy; power industry; and state, local and tribal communities.

The FAA also is collaborating with stakeholders, including through the United States Department of Transportation’s Advanced Air Mobility Interagency Working Group.

The plan’s highlights include:

Operations

• Pilots will be able to fly the new advanced mobility aircraft to and from multiple locations at the sites, using predetermined flight schedules with pilots aboard.
• Advanced air mobility aircraft likely will operate up to 4,000 feet altitude in urban and metropolitan areas, using existing or modified low altitude visual flight rules (VFR) routes where possible within controlled Class B and C airspace around major airports.

Infrastructure

• Operators, manufacturers, state and local governments, and other stakeholders will be responsible for planning, developing and enabling heliport/vertiport infrastructure.
• Advanced air mobility will initially operate at existing heliports, commercial service airports and general aviation airports. Modifications may be necessary to install charging stations, parking zones and taxiing space.

Power Grid

• The electrical power grid may require upgrades to serve advanced air mobility operations.
• The FAA has an interagency agreement with the Department of Energy’s National Renewable Energy Lab to determine how aircraft electrification affects a vertiport, heliport or airport’s electrical grid.

Security

• The Department of Homeland Security will determine what type of security is necessary.
• The Transportation Security Administration and FAA are evaluating the need for expanded cybersecurity requirements due to the use of advanced technology and operational protocols.

Environment

• The FAA will consider the environmental impacts of advanced air mobility operations, including factors such as noise, air quality, visual disturbances and disruption to wildlife.

Community Engagement

• The FAA will engage with airports, and local, state, and tribal communities to better understand community concerns about advanced air mobility operations, including noise and mitigations.
• Many other stakeholders, such as advanced air mobility operators and airport and vertiport operators will have important roles in community engagement.

The FAA’s full Innovate28 plan can be found here.

Q-CTRL, a quantum technologies company, has partnered with Australia’s Department of Defence to develop quantum sensors that will deliver quantum-assured navigation capability for military platforms.

The company’s partnership is a multi-year effort to field-deploy and validate miniaturized systems on defense platforms. It represents one of the first international partnerships between government and the private sector to apply quantum technology in real defense settings.

Quantum-enhanced navigation technology enables accurate vehicle positioning over long periods when GPS is unavailable. In air, space, underground and underwater, quantum navigation enables long-endurance missions that are otherwise impossible and is resilient against jamming or spoofing.

Q-CTRL announced its quantum sensing division in 2022. The company has worked with partners including Advanced Navigation and the Australian Army to demonstrate and deliver its technology for applications that include remote drone detection.

The United Kingdom’s first fully electric self-driving bus began service on public roads from the Didcot Parkway railway station in June, reported the BBC.

First Bus, the UK’s largest bus operator, said the bus’ radar, lidar and artificial intelligence technology could safely steer, accelerate and brake without human intervention.

While the bus is fully autonomous, it does have a safety driver who is able to override operations if needed.

The 15-seat bus makes a six-mile loop from the station to Milton Park in Oxfordshire, UK, and runs six days a week every 40 minutes.

By using muon-detecting ground stations synchronized with an underground muon-detecting receiver, researchers at the University of Tokyo were able to calculate a receiver’s position in the basement of a six-story building without requiring GPS signals. The muometric positioning system (muPS) team was led by Hiroyuki Tanaka.

As GNSS cannot penetrate rock or water, muon technology could be used in future search and rescue efforts, to monitor undersea volcanoes, and guide autonomous vehicles underground and underwater. Muons are fast, subatomic-sized particles that have been used to wirelessly navigate underground.

MuPS was first created to help detect seafloor changes caused by underwater volcanoes or tectonic movement. It uses four muon-detecting reference stations above ground to provide coordinates for a muon-detecting receiver underground.

Early versions of muPS required the receiver to be connected to a ground station by a wire. However, new research uses high-precision quartz clocks to synchronize the ground stations with the receiver. The four parameters provided by the reference stations plus the synchronized clocks used to measure the muons’ “time-of-flight” enables the receiver’s coordinates to be determined. This system is called the muometric wireless navigation system (MuWNS).

To test the navigation ability of MuWNS, reference detectors were placed on the sixth floor of a building while a researcher took a receiver detector to the basement floor. They slowly walked up and down the corridors of the basement while holding the receiver. Rather than navigating in real time, measurements were taken and used to calculate their route and confirm the path they had taken.

The full published study can be found here.