Dana Goward, President of the Resilient Navigation and Timing Foundation, introducing Brad Parkinson and Matteo Luccio, GPS World EIC. (Image: RNTF)

On December 5, in Houston, Texas, at a gala event to celebrate the 50^th anniversary of GPS hosted by the Resilient Navigation and Timing Foundation, Matteo Luccio, Editor-in-Chief of GPS World, interviewed Brad Parkinson.

Here are two excerpts from the interview:

How does GPS today differ from the design that came out of the Lonely Halls meeting 50 years ago this past September?

Well, I’m very proud of what happened because, to my knowledge, there is no fundamental difference. Basically, that fundamental design has held up. … As a matter of fact, I still have one of the old Trimble handhelds, it’s called an EnsignGPS. It was one of those little devices that got shipped to the Iraq War. The other day, I pulled it out, batteries were kind of crummy, I got those squared away and went out, sure enough and navigated. I probably hadn’t pulled it out in at least 20 years. The point of the story is that evidently it still works.

What do you consider the most significant impact of GPS on society?

Well, the most significant impact is also probably the most perilous: kids today just take it for granted. They know where they are.

Watch the full interview below. 

<p>The post Celebrating 50 years of GPS: An evening with the father of GPS first appeared on GPS World.</p>

Image: USAF

GPS turns 50 this year, marking five decades of transforming the world in ways that have profoundly impacted society. Since its approval as a program on December 17th, 1973, GPS has revolutionized the way we navigate and comprehend our world, often in ways few realize.

To honor this achievement, a special event will be held at the South Shore Harbor Resort and Conference Center in Houston, Texas, on December 5, at 6:00PM. This event aims to be a historic tribute to GPS’s journey and its impact on the global community.

At the special event, Matteo Luccio, editor in chief of GPS World, will lead an engaging discussion with Brad Parkinson, the original chief architect of GPS, shedding light on the system’s early days, its far-reaching impacts on humanity, and exciting prospects for the future.

Members of the press, federal employees, Resilient Navigation Timing Foundation members, PNT Advisory Board members, and presenters may attend the event for free. Others can secure their attendance for $75, which includes an optional one-year membership in the RNT Foundation.

To reserve your spot, RSVP at inquiries@RNTFnd.org no later than November 27.

The President’s National Space-based Positioning, Navigation, and Timing Advisory Board, which advises the government on GPS and related issues, will meet the following two days in the same location. Members of the public are welcome and encouraged to attend. Click here for more information on that event.

Check back to watch a recording of the interview!

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Autonomous vehicles are a truly fascinating innovation. Most modern vehicles on roadways around the world have some level of autonomy, ranging from Level 1 features such as cruise control to Level 5 fully autonomous features such as the ability to monitor roadway conditions and perform safety-critical tasks without intervention by a human driver.

Even though autonomous vehicles have been continually developed and tested for years, adoption has been minimal. According to the University of Michigan Center for Sustainable Systems, a majority of researchers, manufacturers and experts predict widespread adoption of Level 5 autonomous vehicles by 2030 or later.

Several barriers have delayed the adoption of autonomous vehicles, such as concerns about safety, data security and cyberattacks; lack of consumer demand; liability laws and lack of regulatory legislation; and doubts as to their economic viability.

While their adoption is slow, autonomous vehicles have been widely praised for the range of benefits they would provide. According to the U.S. National Highway Traffic Safety Administration, they include: much greater road safety due to features such as advanced driver assistance systems, lidar, cameras, inertial navigation systems and more; greater independence for people with disabilities, senior citizens and low-income individuals; reduced road congestion due to the lower number of crashes and an increase in ride-sharing; and environmental benefits as the automotive industry transitions to all-electric vehicles.

Several technology and automotive companies also have seen the potential benefits of autonomous vehicles for many applications and the potential impact they could have on communities worldwide. In response, these companies have supported autonomous vehicle innovation and adoption by offering new products and working closely with educators, nonprofit organizations and other groups who aim to leverage it to connect the world.

Education meets automated racing

Safran Electronics & Defense, which specializes in resilient positioning, navigation and timing (PNT) solutions, has advanced the adoption of autonomous vehicles with its simulation software while simultaneously supporting current students in their academic pursuits.

To jointly develop future PNT technology and solutions Safran’s Minerva Academic Partnership Program supports partnerships with the academic community by providing its technology for student-led research projects that use GNSS signals. Leisa Butler, the program’s chair, elaborated on its mission: “Collaborating with our customers in academia while advancing PNT education is the program’s core purpose. We provide members with access to our powerful Skydel GNSS simulation engine.”

Safran and auburn university students are pictured with their autonomous F1 race car that competed in the Indy Autonomous Challenge on the Las Vegas Motor Speedway at CES 2023. Auburn students used Skydel, a Safran simulation engine, to improve the capabilities of the car and to learn how to make it safe and reliable on the track. (Image: Safran Electronics & Defense)

As a part of the program, Safran has a long-established partnership with Auburn University’s College of Engineering. Safran and Auburn University students participated in the Indy Autonomous Challenge, which took place on January 7, at the Las Vegas Motor Speedway during the 2023 Consumer Electronics Show. Nine autonomous Formula 1 race cars, representing colleges and universities from around the world, took part in a head-to-head driverless racing competition with some vehicles reaching speeds of more than 190 mph.

Safran has supported Auburn students before, during, and after this challenge by enabling them to leverage its GNSS simulators, such as Skydel and the GSG-8, which are used in the university’s autonomous vehicle lab. Butler said that giving students access to the simulation software prior to the high-speed races helped them troubleshoot and test the vehicles and improve the results.

“Resolving issues in the lab improves safety while saving time and money,” Butler stated. “The Indy car features multiple antennas. Since Skydel can support multiple instances simultaneously, the team can test heading and realistic scenarios in a simulated environment. This is before they race next to other vehicles at high speeds.

Safran also supports the general advancement of autonomous vehicle technology. Positioning and navigating autonomous vehicles involves the use of multiple technologies, including GNSS.

“Skydel is a valuable tool for the autonomous vehicle industry that wants realistic lab testing because it can support multiple, independent trajectories or antenna outputs simultaneously,” Butler said. She also pointed to the importance of developing mitigation techniques against jamming and spoofing.

“Using a simulator with the Skydel engine allows the user to test in all sorts of challenging environments before putting the wheels on the pavement. This lets the user make sure the vehicle is ready for real-world navigation and avoid costly mistakes. It also gives them a chance to practice and develop countermeasures against unintentional interference and malicious actors.”

Butler added that Safran is proud to support students who are helping to develop automated technology.

“Supporting Auburn’s Autonomous Vehicle team is an honor and a privilege. Student research represents the future of our industry,” Butler said. “We are proud to support them and see what they can accomplish with our simulation tools. We are confident that they will be able to gain valuable insights that will help them design, build and test their autonomous vehicles. It is our hope that their hard work will lead to the development of safe, efficient and affordable autonomous vehicles in the future.”

Accelerating mobility

Waymo, based in Mountain View, California, is an autonomous driving technology company. Formerly known as the Google self-driving car project, it was founded in 2009 and aimed to drive more than 10 uninterrupted 100-mile routes autonomously.

Its first fully autonomous ride on public roads took place in 2015, then Waymo became an independent self-driving technology company in 2016. It launched its first public trial of autonomous ride-hailing vehicles, called Waymo One, in Phoenix, Arizona in 2017, and has expanded its completely autonomous ride-hailing service trials to Scottsdale, Arizona, as well as San Francisco and Los Angeles.

The Waymo vehicle fleet also became fully electric this year.

360° Lidar, Radar, and cameras make up most of the technical elements of the fifth-generation Waymo fully autonomous vehicles. They also have redundant steering and braking, backup power systems, redundant inertial measurement systems for positioning, and more. (Image: Waymo)

Driving Change

According to its website, Waymo “represent[s] a diverse set of communities and interests, and we are coming together because we all share the belief that autonomous driving cars can save lives, improve independence, and create new mobility options.”

Some of Waymo’s community partners include Bike MS, the Arizona Council of the Blind, the Foundation for Senior Living, and Mothers Against Drunk Driving.

One community story to note is Waymo’s partnership with First Pace AZ — a supportive housing community for adults with autism, Down syndrome and other types of neurodiversity — to explore how Waymo could aid neurodiverse people.

Eli is a resident of First Place AZ and an adult with neurodiversity. He does not drive and relies heavily on ride-hailing services, carpooling, and the train to get to work and to volunteer. Not all public transportation is always available or accessible at certain hours. Additionally, human-driven rideshare and carpooling services can present bias from drivers and other passengers who do not understand the behavioral nuances of people who are neurodiverse.

To test the autonomous ride-hail Waymo One system, Eli and Natasha Grant, director of workplace and community inclusion at First Place AZ, hailed a ride to a local animal shelter.

After using the Waymo One service, Eli believed Waymo’s technology could help him stay connected to his community, wherever he may live in the future. Grant added that autonomous vehicles provide independence for individuals who may otherwise not be able to go to places to which they want and need to go.

Breaking social barriers

Community partners that fight food insecurity use Cruise’s autonomous vehicles to pick up left over food from businesses. (Image: Cruise)

Cruise is a self-driving car company based in San Francisco, California, and offers driverless rides in San Francisco; Austin, Texas; and Phoenix, Arizona. It was founded in 2013 by Kyle Vogt and acquired by General Motors in 2016.

Cruise first offered driverless ride-share services for its employees in 2017. In early 2020, the company began testing those driverless rides on public roads in San Francisco. Later that year, Cruise switched gears and repurposed a portion of its all-electric autonomous vehicle fleet to deliver meals to the community during the COVID-19 pandemic. It also began self-driving delivery trials in Arizona.

In 2021, Cruise announced plans for international driverless testing and expansion in Dubai and Japan. The next year, it opened its fully driverless service to public riders in San Francisco.

Delivering Hope

Cruise works with several community partners, such as the National Federation of the Blind, the SF-Marin Food Bank, and the San Francisco Giants.

“At Cruise, our commitment to social impact is a vital part of our business and an extension of our mission to improve life in our cities, especially for people underserved by transportation today,” the Cruise website stated.

In June, Cruise partnered with Replate — a nonprofit food rescue platform — to fight food insecurity and food waste in San Francisco and other communities. The partnership aims to use Cruise’s all-electric autonomous vehicle fleet, integrated with a national network of food recovery partnership from Replate, to pick up leftover food from local businesses and deliver it to organizations that help fight food insecurity.

The goal of the partnership is to create a sustainable cycle of food rescue that fights hunger and waste in local communities.

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Image: Kara Capaldo/iStock/Getty Images Plus/Getty Images

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.

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The Trektor hybrid robot for agriculture, made by the French company SITIA, can work on a variety of crops by changing the width of its wheelbase and can perform many repetitive tasks, such as spraying and hoeing. (Image: SITIA)

Precision agriculture has been around for more than 30 years and now covers the majority of U.S. farmland. It refers to the ability of farmers to observe, measure and respond precisely to the variability of soil and crop characteristics within and between fields by using maps of these characteristics and GNSS navigation. It enables them to reduce inputs of seed, water, fertilizer, pesticides and fuel while increasing outputs. It also enables them to work at night and in the fog and automate many functions at large feed lots.

For precision agriculture, GNSS integrity can mean the difference between, say, a robot protecting a vineyard by weeding and spraying pesticides or damaging it by straying onto the vines.

Autonomous Tractors, Mowers, and Feed Monitors

SITIA, a French company, has developed an autonomous tractor that is used by, among others, an organic vineyard in France’s Loire valley to tirelessly weed the narrow rows between the grape vines — compensating for the movement of young workers to cities. Thanks to the high accuracy and integrity of the Septentrio GNSS heading receiver inside, the autonomous tractor has decreased the damage to the vineyards by more than an order of magnitude compared to the traditional work done by a farmer with a manual tractor.

Renu Robotics, based in San Antonio, Texas, makes a robot for vegetation management, called Renubot. It uses machine learning, a form of artificial intelligence, to plan its route, optimize its energy consumption, perform self-diagnostics, collect environmental data and assess the topography that it traverses.

Navigation is based on a stored map of paths, a Septentrio RTK GPS receiver and sensors to avoid obstacles. A radio link enables the Renubot to communicate with a control center, for reporting and updates. When the Renubot returns to its recharge pod, it charges its lithium battery and performs updates and downloads.

Manabotix Pty. Ltd., an Australian company, has developed an automated system to monitor cattle in large feedlots, using GNSS, lidar scanning and other vision or perception technologies and artificial intelligence. This has greatly improved the accuracy and consistency of feedlot volume estimates, which for the previous 150 years had been the responsibility of a select few employees, who would visually gauge the amount of feed in concrete troughs. This visual inspection by humans was inherently imprecise, subjective, and inconsistent, often causing animals to eat too much or too little one day and get off their optimal growth curve or even become ill. Manabotix’s solution consists of a Septentrio AsteRx-U GNSS receiver and antenna, a lidar scanner, and an onboard processing platform.

Statistical Analysis

Integrity is a key aspect of all these applications. A part of delivering integrity is a statistical analysis called receiver autonomous integrity monitoring (RAIM), which was developed for such safety-critical applications as aviation or marine navigation. A refinement of RAIM, called RAIM+, takes this analysis to the next level as part of a larger positioning protection package.

For autonomous operation, it can be particularly hazardous to be overly optimistic about GNSS accuracy. This parameter is reported in the form of positioning uncertainty, which is the maximum possible error on the calculated position. It is especially necessary in challenging GNSS environments, where the receiver has a direct line of sight to only a limited number of GNSS satellites or where GNSS signals are degraded. RAIM alerts users when their receiver’s uncertainty strays beyond the limits they have chosen for their application.

Users can be deceived by a consistent position or movement — which can be consistently inaccurate. The positioning uncertainty gives them an indication of the extent to which they can rely on their receiver’s positioning accuracy at any given moment. The receiver operator can set an alarm limit, so that the receiver can flag situations when positioning uncertainty becomes too large.

The blue line in Figure 1 shows position uncertainty estimated by a GNSS receiver under favorable conditions, when the view of the sky is unobstructed, and the receiver has a direct line-of-sight to many satellites.

Figure 1. Under good GNSS conditions, the position uncertainty shown by the blue lines is well within the alarm limits, indicating safe operation. The actual position of the receiver should always remain within the blue uncertainty boundaries. (Image: Septentrio)

During favorable conditions, the positioning uncertainty stays well below the alarm limit because the calculated position is almost the same as the robot’s actual position. However, in challenging environments, the truthfulness of positioning uncertainty becomes most critical (see Figure 2).

Figure 2. In challenging environments receivers with high integrity report large positioning uncertainty, flagging possible inaccuracies to the system. If the receiver is too optimistic about its accuracy, the operation becomes hazardous. (Image: Septentrio)

For instance, when the view of the sky is partially obstructed by buildings or foliage, the receiver has access to only a limited number of GNSS satellites, making it harder to calculate accurate position. In such cases the receiver must report a higher positioning uncertainty, so that the system can take adequate action such as switching to lower speeds, staying further away from predefined boundaries, or stopping.

A low integrity receiver may keep reporting an optimistic positioning uncertainty, that stays below the preset alarm limit even when the calculated position is way off from the actual position. The number may look fine, but effectively it becomes a “robot on the loose,” no longer on its planned path with a risk of damaging itself and its surroundings.

Let us look at uncertainty limits in action during a GNSS car test in an urban canyon, where the view of the sky is partially obstructed by houses (see Figure 3). The orange lines are the positioning and its uncertainty boundaries reported by a Septentrio mosaic GNSS module in the car, while the red lines are the positioning and its uncertainty boundaries reported by another popular GNSS receiver. The white line shows the actual position of the car as it drives along the road. The orange uncertainty boundaries of the mosaic receiver are truthful and somewhat wider in this challenging environment, and you can see that the actual position always remains within these boundaries. On the other hand, the red trajectory jumps off course in a certain challenging spot on the road, with the actual position no more within the uncertainty boundaries, which remain too optimistic. In this case the competitor’s receiver gives a false sense of security and the system is unaware of its hazardous operation.

Figure 3. In an urban canyon car test the Septentrio receiver reports truthful position uncertainty. A competitor receiver seems to be more accurate, while the actual position is not even within its reported uncertainty boundaries. (Image: Septentrio)

If the receiver depicted by the red line provided navigational information for an ADAS automotive system, for example, this could mislead the system into thinking that the car switched lanes. If the system then attempted to correct the trajectory by switching back to the “correct lane” this would result in taking the car off course and potentially hitting the sidewalk or even another car.

RAIM vs RAIM+

The underlying mechanism behind truthful positioning uncertainty reporting is RAIM, which ensures a truthful positioning calculation based on statistical analysis and exclusion of any outlier satellites or signals. Septentrio receivers are designed for high integrity and take RAIM to the next level with RAIM+, guaranteeing truthfulness of positioning with a high degree of confidence.

In Septentrio receivers RAIM+ is a component of a larger receiver protection suite called GNSS+ comprising positioning protection on various levels including AIM+ anti-jamming and anti-spoofing, IONO+ resilience to ionospheric scintillations, and APME+ multipath mitigation.

Septentrio has fine-tuned its RAIM+ statistical model with more than 50 terabytes of field data collected over 20 years. It removes satellites and signals which may give errors due to multipath reflection, solar ionospheric activity, jamming and spoofing, while working together with the GNSS+ components mentioned above. Because of this multi-component protection architecture, it achieves a very high level of positioning accuracy and reliability which goes well beyond the standard RAIM. The RAIM+ statistical model is adaptive, highly detailed, and complete, taking advantage of all available GNSS constellations and signals. The full RAIM+ functionality is also available in Septentrio’s GNSS/INS receiver line. User controlled parameters allow it to be tuned to specific requirements.

The diagram in Figure 4 shows RAIM+ in action during a jamming and spoofing attack on a Septentrio GNSS receiver. While AIM+ removes the effects of GNSS jamming, both AIM+ and RAIM+ work together to block the spoofing attack. Satellites with high distance errors, shown on the middle graph, are removed by RAIM+ since they do not conform to the expected satellite distance.

Figure 4. In this scenario jamming gives satellite distance errors but is countered by AIM+ technology. During spoofing AIM+ eliminates some of the spoofed satellites, while other satellites that have wrong distances are dismissed by RAIM+ algorithms. (Image: Septentrio)

This example shows that even in the case of jamming and spoofing, Septentrio’s high integrity receiver technology delivers truthful and reliable positioning on which any autonomous system can count.

GNSS Design Around Reliability

GNSS receivers designed to be reliable strive for high integrity in both reporting of the positioning uncertainty as well as in RAIM+ advanced statistical modelling. This ensures that these receivers provide truthful and timely warning messages and are resilient in various challenging environments. Other technologies such as inertial navigation system (INS) can also be coupled to the GNSS receiver to extend positioning availability even during short GNSS outages. Quality indicators for satellite signals, CPU status, base-station quality and overall quality allow monitoring of positioning reliability at any given time. High-integrity GNSS receivers provide truthful positioning in autonomous machines such as the SITIA weeding tractor. They are also crucial components in safety-critical applications, assured PNT and any other application where accuracy and reliability matters.

<p>The post Integrity is integral to precision agriculture first appeared on GPS World.</p>

The projects have spanned from the Nuyakuk River in Alaska, Lake Tahoe in California, the Rio Grande in Texas, the entire coasts of South and North Carolina, the Achigan River in Quebec, Chesapeake Bay in Maryland and the Florida Keys.

In 2022, the company mapped and acquired topobathymetric lidar data for 14 projects including the Yellowstone River, Wyoming; Hells Canyon, Indiana; Revillagigedo Island, Alaska and Iles de la Madeleine in Quebec.

NV5 Geospatial first mapped these environments in 2012 using high-resolution bathymetric lidar and natural color imagery. The company mapped 34,051 acres of shoreline along the Sandy River, located in northwestern Oregon, to study the ever-changing basin geomorphology.

NV5 has also signed a two-year contract with the National Geodetic Survey of the National Oceanic and Atmospheric Administration to provide topobathymetric lidar, 4-band imagery and mapping of 3,115 sq miles of the Maine shoreline.

“For a decade we have been helping local, state, and federal government agencies as well as commercial and private entities gain the insights they need to solve some of their most challenging nearshore and riverine projects through our mapping technologies including topobathymetric lidar,” Kurt Allen, vice president of NV5 Geospatial, said. “Whether it be mapping the shoreline after a hurricane, updating the national shoreline, assisting water boards with flood planning, or hundreds of other possible use cases, we are constantly improving our technology and scalability to always be at the ready for our customers.”

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During a 12-day mission in the moon’s Mare Crisium basin, LuGRE will obtain the first GNSS fix on the lunar surface and receive signals from both GPS and Galileo. The LuGRE payload is managed by NASA’s Space Communications and Navigation program office.

This payload is a collaborative effort between NASA and the Italian Space Agency to expand the capabilities of Earth-based navigation systems. Navigation engineers at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, have been testing the payload’s GNSS receiver and low noise amplifier. The receiver was developed and built by the Italian company Qascom.

These components will be critical to LuGRE obtaining signals from the GPS and Galileo satellites. To prepare for operating on the moon, NASA engineers used a GNSS simulator to test and configure the payload to accurately receive and process the signals.

The LuGRE payload GNSS receiver and low noise amplifier. (Image: NASA/Dave Ryan)

The Goddard team delivered in February the flight hardware to Firefly Aerospace in Cedar Park, Texas, where it will be integrated into the Blue Ghost lander.

Astronauts and rovers traversing the lunar surface will need precise location and tracking data for their exploration endeavors. The data gathered from the LuGRE payload will be used to further develop GNSS-based navigation systems for future missions to the moon.

Image: NASA

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Image: Walmart

Two Walmart locations in Utah, one in Lindon and one in Herriman, are now providing UAV delivery for customers nearby. Walmart has UAV deliveries operated by DroneUp, Flytrex and Zipline at 36 stores in the United States.   

For a $3.99 fee, customers within a mile of the stores can receive their groceries via UAVs. The two Walmart locations in Utah can deliver more than 120 times per day and each UAV can carry up to 10 pounds. The hubs for deliveries are in the parking lots of each Walmart location and are operated by Federal Aviation Administration-certified pilots. 

Walmart is using UAV delivery in seven states, including Florida, Arizona, Texas, Utah, Virginia, North Carolina and Arkansas. The most common products delivered include ice cream, lemons, rotisserie chicken, Red Bull and paper towels, according to Walmart.   

Walmart drone deliveries launched in October 2019 in Arkansas. In 2022, Walmart completed more than 6,000 deliveries across all 36 participating locations. 

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