Warning sirens about the vulnerabilities of GPS to jamming, spoofing, solar activity and other disruptions have been blaring for many years. Now the U.S. Department of Transportation (DOT), which represents other federal civil departments and agencies on all GPS-related matters within the federal government, might finally be moving from study to action. On September 12, at the annual meeting of the Civil GPS Service Interface Committee held in conjunction with ION GNSS+ in Denver, Robert Hampshire, DOT’s Deputy Assistant Secretary for Research and Technology and Chief Science Officer, announced the release of DOT’s Complementary Positioning Navigation and Timing Action Plan. It aims to drive CPNT adoption across the United States transportation system and within other critical infrastructure areas. You can read more here and download the planhere.
Which GPS vulnerabilities does DOT aim to address and how quickly can it “drive adoption” of CPNT? Attempting to answer these questions requires pushing through a dense thicket of bureaucratic jargon. I asked Karen Van Dyke, Director for Positioning, Navigation, and Timing (PNT) and Spectrum Management in Hampshire’s office four questions. What follows are excerpts from her answers. You can read her full response here.
What is your office’s charter within the federal government to advance the development and deployment of complementary PNT?
Her office’s efforts, Van Dyke told me, “support federal policy governing PNT programs and activities for national and homeland security, civil, commercial, and scientific purposes. These include Executive Order 13905, Strengthening National Resilience Through Responsible Use of Positioning, Navigation, and Timing Services (EO 13905) and Space Policy Directive 7, The United States Space-Based Positioning, Navigation, and Timing Policy (SPD-7).”
Which GPS vulnerabilities and at what scale is this plan addressing?
The action plan, Van Dyke told me, “addresses disruption, denial, and manipulation of GPS for critical infrastructure sectors” on “both a widespread and local scale.”
How and when will this action plan move the federal government’s posture on CPNT from study to action?
Van Dyke cited field demonstrations conducted in 2020 by the Volpe Center of candidate PNT technologies that could offer complementary service in the event of GPS disruptions and a 2021 report to Congress that distilled the PNT resiliency recommendations. DOT, she said, should develop “system requirements for PNT functions that support safety-critical services” and “standards, test procedures, and monitoring capabilities to ensure that PNT services, and the equipage that utilize them, meet the necessary levels of safety and resilience”.
How does DOT intend to engage PNT stakeholders?
Van Dyke pointed to a PNT Industry roundtable that DOT held in August 2022 that included representatives from CPNT technology vendors and critical infrastructure sectors and “informed the development” of the action plan. She also pointed out that on September 11, DOT issued a request for information “as one of the steps to drive adoption” of CPNT services “to augment GPS for the nation’s transportation system, and through the executive branch interagency process, for other critical infrastructure sectors.”
Septentrio has been working on port automation projects with Kalmar, a Finnish company that offers a wide range of cargo handling solutions and services to ports, terminals, distribution centers and heavy industry. I discussed this collaboration with Stef van der Loo, market access manager at Septentrio. Following are excerpts of our conversation. For a much longer version, click here.
What are the challenges operating in a port?
In a container terminal or port, everything is interconnected and, therefore, complex. Lately, GNSS has become more popular, especially when coupled with inertial navigation, because the technology has become more capable of delivering centimeter-level accuracy even in challenging environments where the line-of-sight to GNSS satellites may be partially blocked by containers or structures.
What drives higher accuracy?
this Kalmar container handler has a Septentrio high-accuracy GNSS/INS receiver and an inertial system, which operate in challenging environments of low satellite visibility. (Image: Kalmar)
Every year, every terminal stacks a certain number of containers, but not all the information about them is given to the terminal operating system (TOS) automatically. Sometimes, operators must search for misplaced containers, which may require stopping operations and deploying additional personnel. Additionally, it is not very safe to go into these yards. This is one reason why ports began to deploy positioning systems. However, ten years ago, with meter accuracy, they were failing all the time. Now, improvements in the technology have enabled GNSS to become fit for the challenge. In terminals, you can use GNSS or INS systems for vehicle traffic management, autonomous vehicles and tasks, or to get the position of a container.
For example, when a reach stacker reaches into a stack and locks a container in place, it’s crucial to have a very reliable centimeter-level position. Errors grow as the data is processed from the control systems to the TOS. To know for certain the position of a container when it was placed in a stack errors must not exceed half a meter. Therefore, the reliability and accuracy of the GNSS/INS is crucial for container positioning.
Do you buy the IMUs and do all the integration?
We buy the IMUs mostly from Analog Devices. The integrated inertial navigation solution is our own. We focus on inertial navigation in several markets — including logistics, autonomous mining, and agricultural robotics.
What is the division of labor between you and Kalmar?
Kalmar is both an OEM and an integrator. They are a guru for the automation of logistics terminals. We work with them mainly as an integrator. They will go to a terminal, like other integrators, and install the systems and other equipment. Kalmar built a whole sensor stack with all types of sensors and integrated this in their packages, such as SmartPort. With a train-the-trainer principle, our engineers trained Kalmar employees, so they have first line control of the installations and troubleshooting. Then we are ready to support them where we can. We have a continuous feedback loop with several logistics customers for suggestions and product recommendations for the evolution of our products and services for this segment.
Straddling containers
JAVAD GNSS
Straddle carrier in operation equipped with DELTA-3S. (Image: Canva)
One of the largest container companies in the world needed a solution to manage its straddle carriers, which are specialized container handling vehicles at ports that can pick up large containers and move them to trucks, trains, or other container stacks. This is very challenging for container terminal operators because ports are highly complex operating environments that also provide other maritime services, such as storing and managing cargo, forwarding freight, and clearing customs. To handle containers safely and efficiently, modern terminals have buildings, equipment, and cranes in addition to straddle carriers. All this infrastructure creates a lot of multipath that stresses the capabilities of GNSS receivers.
To develop and install this new system for straddle carrier vehicles, the container company turned to JAVAD GNSS and to ALLSAT GmbH, a German engineering, geodetic and electronic company founded in 1991 that has been JAVAD’s German distribution partner since 1995. To address the challenge, in 2022, ALLSAT GmbH applied a new digital twin concept to supply and support the commissioning of several hundred JAVAD GNSS rover solutions at three international seaports. This required obtaining real-time and highly accurate positional data for moving straddle carriers and uploading it to a terminal information system for control and documentation.
ALLSAT deployed a geodetic conceptual design that integrates JAVAD GNSS Delta-3S receivers and RingAnt G5T and GrAnt-G5T antennas to deliver precise surveying of two GNSS reference stations per port, then commissioned the system on all the straddle carrier vehicles from a single source. It also developed a solution employing two redundantly operating reference stations that broadcast RTK correction data for all GNSS (GPS, Galileo, GLONASS, and BeiDou) on different IP addresses/radio frequencies. All the JAVAD RTK rovers can receive and process data from both correction sources in parallel thanks to their 874 channels and parallel processors. This offers two advantages. First, it provides a comprehensive fallback in the unlikely event that one reference station fails. Second, it greatly improves the reliability, speed and accuracy of the rovers, which operate in an environment rife with signal shadowing and multipath influences.
Working closely with its client and JAVAD GNSS, ALLSAT was able to implement this project, from initial idea to verification and commissioning, in only a few weeks. The combination of redundant, multi-constellation reference stations and JAVAD GNSS multi-base RTK yielded a solution that is highly reliable and available, providing for continuous operation despite the challenging environmental conditions. Additionally, JAVAD GNSS provides firmware updates for the life of the devices, which will enable the customer to rely on this base rover solution for the next 10 years.
Tracking trains
M3 Systems
(Image: Logiplus)
M3 Systems, a French-Belgian geolocation company founded in 1999, has long supported the R&D activities of European space and civil aviation agencies. It also markets products that it developed through its R&D activities. In recent years, M3 Systems expanded its activities into the automotive and rail sectors. To develop a new device for trains, it partnered with two Belgian companies: Logiplus, which makes onboard electronic systems for trains, and ALSTOM Belgium, a division of ALSTOM group, which builds trains and equipment for train tracks. “The objective during the product design was the development of a hybrid sensor that uses both a GNSS sensor to provide absolute positioning, and an inertial measurement unit (IMU) to compensate for environmental obstructions such as trees and urban canyons by calculating the train’s position based on its last GNSS-based absolute position,” explained Jérémy Skelton, project lead at M3 Systems.
IMUs have long been coupled with GNSS because each technology compensates for the other one’s limitations: IMUs suffer from drift and GNSS receivers from signal loss in certain environments. In theory, surveying the tracks and using odometry to monitor a train’s linear position on them would suffice to locate it. In practice, however, wheel encoders “are prone to errors because the wheels are subjected to a lot of sliding and skidding,” Skelton said.“So, we need completely independent sensors.”
This requirement led ALSTOM to propose the development of the IGLOO (an acronym for IMU & GNSS vehicle odometry) input device, which integrates all the different sensors. Logiplus designed and manufactured the hardware, while M3 Systems wrote the algorithm.
The project, which was partially funded thanks to a grant from the European Regional Development Fund and supported by the Région Wallonne of Belgium, was divided into three components:
The software to couple the IMU and the GNSS to compute the train’s velocity.
The auto-calibration solution, which eliminates the need for automatic calibration when starting the sensor.
A hardware platform that incorporates a low cost IMU.
The consortium defines three kinds of zones in which a train will operate, depending on the trustworthiness in each zone of the GNSS signals. “For example, an environment with a clear view of the sky and no nearby obstacles is trustworthy,” Skelton said, “while a forest, an urban canyon, or the entry into a tunnel are not. Without GNSS support, eventually the IMU will also become unreliable.”
At very low speeds, errors must be very low, but at higher speeds a greater speed error is allowed. Operators can extract different levels of data from a GNSS receiver. To achieve a tight GNSS-INS coupling, they can use the Doppler delays and hybridize them with the IMU or use the tracking loop and set the range and Doppler. For a loose coupling, they can directly use the GNSS receiver’s positioning, velocity, and timing data. All couplings are performed by using Bayesian filters, for example the Kalman filter. “Loose coupling will give you less accuracy, reliability, and integrity, but it will also be less CPU-intensive,” Skelton said.
For data acquisition on a train, M3 Systems generated a printed circuit board (PCB) with a u-blox GNSS receiver, a Septentrio Asterix GNSS receiver, nine IMUs (which enables them to choose the best one for the use case), a reference trajectory unit that provides ground truth, and a computer that takes the data from the GNSS receivers and the IMUs. “Everything was integrated for measurement purposes on a rack on a train that runs here in Belgium,” Skelton said, “and all the data was retrieved automatically via a 4G internet connection. We have collected a few thousand kilometers traveled, a few hours of tunnels, and both trustworthy and untrustworthy GNSS signals.”
M3 Systems’ partner Logiplus designed the product to support the hybridization software and interface with the European vital computer (EVC), which monitors and continuously calculates the train’s maximum speed and braking curve. “It is critical for the EVC to have perfect knowledge of the train’s speed, which is the main reason we designed this new device,” Skelton said. “What is specific in that hardware is the computing power, the two systems (GNSS and inertial), and the data fusion algorithm, which allows the hardware to evolve. For example, we can switch to a different IMU.”
The IGLOO system complies with the specified safety requirements, contributing to a more reliable knowledge of the train speed, which reduces the risk of accidents and fatalities, improves traffic flow, and improves the efficiency and safety of the train operations, Skelton pointed out.
Surveying a railroad
Eos Positioning Systems
A rail tunnel at Leigh-on-Sea in East of England. Arcadis used Eos Arrow 100 GNSS receivers alongside Esri’s ArcGIS Survey123 to collect rail assets with submeter accuracy in real time. (Image: Amaro)
Network Rail, which owns and manages the railway infrastructure in England, Scotland and Wales, needed an as-is survey of up to 50,000 electrical assets along 400 miles of rails in the eastern region of the country. It turned to Arcadis, a design and consultancy firm that specializes in sustainable design and engineering services. The project required delivering accurate building information modeling (BIM) plans of the rail line to support operations and maintenance of the electrified infrastructure, while ensuring a safe working environment for the surveying teams. Using Arrow 100 GNSS receivers from Canadian manufacturer Eos Positioning Systems and Esri’s ArcGIS Survey123 and ArcGIS Hub software, Arcadis was able to efficiently capture the data with sub-meter accuracy and share it with Network Rail in real-time.
Arcadis decided to conduct a digital field survey to collect the data and to use GIS to manage it, said Gideon Simons, Associate Director of GIS and Geospatial Consultant at Arcadis. “We provided the survey teams iPads, the Esri application, and the GNSS receivers.” For corrections, it used the Ordnance Survey’s OS Net. “We found through a few assessments and testing that the Eos Arrow’s precision was good enough to meet the project’s requirements.”
The region surveyed is mostly rural but the rail line traverses some very urbanized areas. “One of the first challenges was surveying under cover in stations and in quite a few tunnels. So, we developed methodologies using georeferenced plans and imagery and taking temporary datums using GNSS outside the tunnels, to measure distance and offsets to the assets in the tunnels with measuring wheels that allowed for post-survey processing and the location accuracy required,” said Simons.
Photography was also a key to the success of the project. “In just one depot, we surveyed thousands of assets with many inside train sheds,” said Simons. “We use 360-degree cameras and train view cameras, so that we really understand where assets should be placed.”
The next stage for Network Rail is to maintain that equipment — whether it’s replacing it, bringing it up to code, or potentially installing new assets, Simons pointed out. “In the UK, we use a variety of measurements — imperial and metric. So, it’s been very helpful for the client to have just one source of truth reference that supports their work yet that can still link with other systems and ease communication with wider teams.”
An exclusive interview with Stef van der Loo, market access manager, Septentrio. For more exclusive interviews from this cover story, click here.
What are your key markets and how does this port project fit in?
We have many markets, of course, but we have a big focus on machine automation, mainly for large industrial machinery. Think of agriculture and construction. Port logistics is a newcomer in a sense. In the last 20 years, there’s been a lot of testing with GPS receivers in terminals, but not as much as in construction because the two environments are very different. In a container terminal or port, everything is interconnected and, therefore, complex.
You can equip an excavator with a 3D system and import this data into a building information modeling (BIM) system, but sometimes data is missing and the system breaks. If that happens in logistics the whole chain breaks and you’re stuck. Lately, GNSS has become more popular, especially when coupled with inertial navigation, because the technology has become more capable of delivering centimeter-level accuracy even in challenging environments where the line-of-sight to GNSS satellites may be partially blocked by containers or structures.
So, GNSS is becoming more of a fit for the logistics market.
What have been the drivers of higher accuracy in the past 20 years?
The terminal operators want to increase their throughput of containers. Automation will not always speed up the handling of containers, because autonomous vehicles might move slower than those operated by experienced human operators.
In logistics they started looking at positioning to deal with the loss of containers. Every year, every terminal stacks a certain number of containers, but not all the information about them is given to the terminal operating system (TOS) automatically. If you keep on stacking but with missing data every container on top of a missed one will be wrong, so you fill your system with wrong data. Sometimes, operators must search for misplaced containers, which may require stopping operations and deploying additional personnel. Additionally, it is not very safe to go into these yards. This is one reason why ports began to deploy positioning systems. However, ten years ago, with meter accuracy, they were failing all the time. Now, improvements in the technology have enabled GNSS to become fit for the challenge.
Nowadays, in terminals, you see many non-GNSS positioning systems, such as radar systems, to steer cranes and position containers. We’re replacing many of these systems. There are also transponders in the roads, for vehicle traffic management and for area guided vehicles (AGVs), which are fully autonomous and need centimeter-precision everywhere. GNSS does not work everywhere. You always have some disruptions or gaps in coverage. However, the newer inertial systems can compensate for short GNSS outages so that you get reliable centimeter accuracy. Additionally, the cranes are increasingly automated. Gantry cranes, for example, are on rubber tires but constrained in their movements. Reach stackers, forklifts, and terminal tractors, on the other hand, have free movement. These vehicles are typically equipped with the GNSS or INS systems for traffic management or container and cargo positioning.
The next step would be to move to semi- or fully-autonomous vehicles, of course. GNSS is not enough for that; autonomous technology needs to have different sensors. It’s extremely difficult to prove and to test a new system in a terminal, because it’s an uninterrupted chain of interconnection between the sea, the stacking of the containers, and ground transportation. You cannot just go in with an autonomous forklift or an autonomous reachstacker and try out something. However, you can only prove it when you do it in that chain. Otherwise, it’s a standalone kind of test. So, that’s the biggest obstacle.
Don’t containers have a barcode you can scan or a serial number you can see with a camera?
Yes, they do. The problem is not so much the number on the container but its virtual number in the terminal’s layout. Let’s say that you put container A on square C1. What if you deviate half a meter and TOS puts it automatically in the system in C2 instead? That’s often where mistakes occur. So, you can have OCR scanners and easily scan the code on the container. The problem is where you place the container.
What about the virtual image of all the container stacks?
Yes, the digital twin, like in construction. However, in construction you don’t need the infrastructure. You don’t need to install a radar in a certain place, calibrate it, enter it in the maps, et cetera. That’s more the survey part of construction. The biggest win is when you can equip a vehicle with a standalone system. It needs RTK, but it is standalone for the port. You don’t need large infrastructure, you don’t need to drill holes every two meters to place transponders in the roads in the whole area, perhaps just a small part. That saves them a lot of investments and maintenance.
In terminals, you can use GNSS or INS systems for vehicle traffic management, autonomous vehicles and tasks, or to get the position of a container. For example, when a reach stacker reaches into a stack and locks a container in place, it’s crucial to have a very reliable centimeter-level position. Errors grow as the data is processed from the control systems to the TOS. To know for certain the position of a container when it was placed in a stack errors must not exceed half a meter. Therefore, the reliability and accuracy of the GNSS/INS is crucial for container positioning.
Many AGVs carrying containers still work with road transponders. But if we can assist with our GNSS and INS products, they may be able to make a hybrid form of terminal. In perhaps 80% to 90% of the terminal, GNSS/INS works fine because you have a relatively clear view of the sky.
We already play a big role with Kalmar. They are replacing all legacy positioning systems, which are often heavy on the infrastructure side. So, they’re stuck in their layout, they are not flexible anymore. To handle the positioning of the containers, they preferably do not use any fixed infrastructure. That’s one of the drivers within their SmartPort automation service. So, it’s for flexibility, for traffic management, automation and to position the containers.
The autonomous side is a whole other category. There are many semi-autonomous terminals and they’re partly closed, so nobody can enter them. There you need to do everything fully autonomously, of course, because there are no people inside. Here, too, the Septentrio systems play a role, similar to that of other autonomous vehicle markets. Yet the autonomous terminal evolution is still in its early days. The non-container logistics might take a leap here. We have an increasing number of customers who are developing or retrofitting autonomous logistics vehicles such as the terminal tractors, reach stackers and forklifts mentioned before, specifically for yards and factory plants.
In September, the U.S. Department of Transportation (DOT) released the Complementary PNT Action Plan: DOT Actions to Drive CPNT Adoption. On October 16, Matteo Luccio asked a few questions about the plan to Karen Van Dyke, Director for Positioning, Navigation, and Timing (PNT) and Spectrum Management in the U.S. Department of Transportation’s Office of the Assistant Secretary for Research and Technology (OST-R). Below are Luccio’s questions and Van Dyke’s responses.
What is your office’s charter within the federal government to advance the development and deployment of complementary PNT?
The U.S. Department of Transportation (DOT) is the lead for civil PNT requirements in the United States and represents the Federal civil departments and agencies in the development, acquisition, management, and operations of GPS. The DOT Positioning, Navigation, and Timing (PNT) and Spectrum Management program (within the Office of the Assistant Secretary for Research and Technology) coordinates the development of Departmental positions on PNT and spectrum policy to ensure safety, mobility, and efficiency of the transportation network. The Department also provides civil PNT system policy analysis and coordination representing Federal civil agencies responsible for critical infrastructure in the requirements development, acquisition, management, and operations of GPS.
These efforts support Federal policy governing PNT programs and activities for national and homeland security, civil, commercial, and scientific purposes. These include Executive Order 13905, Strengthening National Resilience Through Responsible Use of Positioning, Navigation, and Timing Services (EO 13905), and Space Policy Directive 7, The United States Space-Based Positioning, Navigation, and Timing Policy (SPD-7).
Which GPS vulnerabilities and at what scale is this plan addressing?
The DOT Complementary PNT Action Plan addresses disruption, denial, and manipulation of GPS for critical infrastructure sectors. These vulnerabilities of GPS include unintentional and intentional jamming and spoofing (both measurement and data spoofing) of the GPS signal and physically impeded environments in which the availability of the GPS signal is impacted (e.g., indoors, underground, and urban canyons). This plan is intended to address vulnerabilities/limitations of GPS on both a widespread and local scale.
How and when will this action plan move the federal government’s posture on CPNT from study to action?
In 2020, the DOT Volpe National Transportation Systems Center (Volpe Center) conducted field demonstrations of candidate PNT technologies that could offer complementary service in the event of GPS disruptions. The purpose of the demonstrations was to gather information on PNT technologies at a high technology readiness level (TRL) that can work in the absence of GPS.
While this demonstration was a snapshot in time, there were two central recommendations from the demonstration:
U.S. DOT should develop system requirements for PNT functions that support safety critical services.
U.S. DOT should develop standards, test procedures, and monitoring capabilities to ensure that PNT services, and the equipage that utilize them, meet the necessary levels of safety and resilience identified in Recommendation 1.
The culmination of the demonstration program was the 2021 Report to Congress, Complementary PNT and GPS Backup Technologies Demonstration Report (2021 Demonstration Report). The PNT resiliency recommendations distilled in the 2021 Demonstration Report were vetted through a Federal interagency review process. During the same period, SPD-7 (directed to U.S. Federal Space-Based PNT service providers) and EO 13905 (directed to PNT users) were issued in a coordinated effort to strengthen U.S. PNT policy.
As part of its ongoing responsibilities as civil PNT lead, the Department has developed a Complementary PNT Action Plan to drive CPNT adoption across the Nation’s transportation system and within other critical infrastructure sectors. The plan describes actions that the DOT plans to pursue over the next several years, including engaging PNT stakeholders; monitoring and supporting the development of CPNT specifications and standards; establishing resources and procedures for CPNT testing and evaluation; and creating a Federal PNT Services Clearinghouse. Taken together with efforts of other Federal partners, these initiatives will continue to strengthen the resilience of the Nation’s PNT-dependent systems, resulting in safer, more secure critical infrastructure.
It should be noted that the U.S. Government is not procuring CPNT systems for non-Federal stakeholders, and as always, all activities are subject to the availability of appropriations.
How does DOT intend to engage PNT stakeholders?
DOT held a PNT Industry roundtable on August 4, 2022 that included representatives from Complementary PNT Technology vendors and critical infrastructure sectors. https://www.transportation.gov/pntindustryround
Feedback from this DOT industry roundtable informed the development of the DOT Complementary PNT Action Plan.
On September 11, 2023, DOT issued a Request for Information (RFI) as one of the steps to drive adoption of Complementary PNT services to augment GPS for the Nation’s transportation system, and through the Executive Branch Interagency Process, for other critical infrastructure sectors. U.S. DOT is planning a resiliency test, evaluation, and performance monitoring strategy for PNT-dependent transportation systems. Taken together with efforts of other Federal partners, these initiatives will strengthen resilience of the Nation’s PNT-dependent systems through the U.S. Government’s purchasing power as a demanding customer of Complementary PNT (CPNT) services, along with critical infrastructure owners and operators, resulting in safer, more secure critical infrastructure for the nation.
The DOT Volpe Center issued this RFI seeking information from industry about availability and interest in carrying out a small-scale deployment of very high technical readiness level (Technology Readiness Level (TRL)≥8) CPNT technologies at a field test range to characterize the capabilities and limitations of such technologies to provide PNT information that meet critical infrastructure needs when GPS service is not available and/or degraded due environmental, unintentional, and/or intentional disruptions. This deployment is intended to test these technologies against CI relevant requirements in order to gain confidence in performance and foster user adoption.
It is likely that DOT will hold future industry roundtables with Complementary PNT technology vendors and critical infrastructure sector owners and operators.
Pasternack has launched its new line of IoT multiband combination antennas. Designed for vehicles, fleets and pivotal base stations, the technology aims to revolutionize how industries perceive and use mobile connectivity.
The antennas integrate 4G, 5G, Wi-Fi and GPS bands to offer emergency teams, on-the-move fleets and first responders an unwavering link, even in harsh environments.
Facilitated with both FAKRA and SMA connectors and extended 17-foot cable leads, users can seamlessly integrate the technology. It also has an IP69K rating, certifying it for both indoor and outdoor deployments.
MIMO capabilities improve data transmission speeds and reliability, ensuring consistent high-bandwidth connections. The antenna’s GPS/GNSS component, enhanced with LNA and amplified by a 26 dB gain, offers users improved navigation and tracking precision.
GMV has been selected by BMW Group to supply its safe and precise positioning technology, GMV GSharp, for the next generation of BMW Group’s autonomous vehicles.
GSharp is equipped with an onboard positioning engine (PE) software and a GNSS corrections service, allowing vehicles to collect augmentation data and safety-related information for computing an accurate and reliable user position.
Both the correction service and positioning engine are developed following the ISO 26262 and ISO 21448 standards to ensure compliance with safety requirements. The solution also complies with the concept of security-from-design as per ISO 21434, including the necessary counter-measures in the SW and system and in the GNSS related attack detection or anti-spoofing and anti-jamming schemes.
The most demanding automotive project management practices and industry standards for software engineering (A-SPICE CL3) have been applied during its development.
In addition to the software side, GMV’s solution relies on a secure and redundant physical infrastructure. GMV owns and operates a worldwide GNSS station network, which provides the GNSS raw data needed to generate the corrections. These corrections are computed within two physically independent data centers, providing GMV’s solution the required availability levels for automated driving applications.
The antennas come equipped with a high gain of 28 dB or 30 dB, enabling them to capture signals in challenging terrains and conditions. One of their standout features is the use of right-hand circular polarization (RHCP), which reduces signal interference and multipath effects.
With waterproof and dustproof ratings ranging from IPX6 to IP66, these antennas are engineered to excel in the harsh environments and are ideal for vehicle tracking, fleet management, telematics, navigation systems and autonomous vehicles.
The antennas also come with both SMA and FAKRA connector options, ensuring wide-ranging system compatibility. They are tailored for the GPS L1 frequency and are available in both passive and active versions. Mounting them is user-friendly, with options for direct vehicle mount or the added convenience of a magnet mount.
The natural sciences overlap — hence such fields as geophysics, astrobiology and biochemistry. So do the social sciences and humanities — hence such fields as political economy, political philosophy and social economics. Our very individual identities consist of multiple, intersecting factors — including gender, race, ethnicity, class, and sexuality.
Analogously, this magazine covers overlapping technologies. While we focus on global navigation satellite systems (GNSS) and other positioning, navigation and timing (PNT) technologies such as inertial systems, these technologies are often embedded in larger systems that also include sensors (such as lidar, radar and cameras) and, increasingly, artificial intelligence (AI).
That is why we so often cover unmanned aerial vehicles (UAV) — which use GNSS for positioning navigation, geofencing and stabilization; use sensors to collect data; and will soon use AI for mission planning and execution — and autonomous vehicles — which use GNSS and sensors for positioning and navigation and already use AI to make driving decisions in complex environments.
Of course, UAVs are also much in the news these days:
Since the start of the Russian invasion of Ukraine, both sides have been using several hundred UAVs every day. According to the Royal United Services Institute, a British think tank, the Ukrainians are losing some 10,000 UAVs a month on the battlefield. (By way of comparison, the French army currently has a little more than 3,000 UAVs in its arsenal.)
In the United States, the number of companies granted waivers by the Federal Aviation Administration to conduct beyond visual line of sight (BVLOS) operations keeps growing, enabling them to conduct much more efficient monitoring, inspections and mapping of infrastructure.
Following a recent increase in encounters between swimmers and sharks along beaches on Long Island, New York, in July UAVs began sweeping the ocean three times a day to detect danger. On July 14, the state’s governor, Kathy Hochul, announced the allocation of $1 million to purchase 60 new shark-monitoring UAVs.
Also in July, 350 UAVs were lost during a practice light display show in Melbourne, Australia, 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, most likely due to interference with GPS signals.
On August 30, researchers in Switzerland unveiled a small AI-powered quadcopter UAV that can outfly some of the best human competitors in the world. It whipped its way around an indoor racecourse in a matter of seconds and was able to beat its human rival in 15 out of 25 races, according to the journal Nature.
From mapping coastal areas with airborne lidar bathymetry to delivering medicines, from locating lost hikers to mapping fires, from enhancing the situational awareness of first responders to monitoring invasive plant species, UAVs are quickly becoming ubiquitous and essential.
Meanwhile, in San Francisco, where autonomous vehicles are already ubiquitous, but not everyone considers them essential, an anonymous group of protesters is surreptitiously placing orange traffic cones on some of them, confusing their sensors and rendering them inoperable.
OxTS has released the xRED3000, its lightest and smallest inertial navigation system (INS) suitable for land- and air-based applications.
Combining two survey-grade GNSS receivers and OxTS’ latest IMU10 inertial technology, the xRED3000 is designed to be the GNSS/INS component for products requiring accurate localization, even in harsh environments.
The xRED3000 uses OxTS lidar inertial odometry (LIO), which takes data from a lidar in post-processing to reduce IMU drift and improve accuracy in areas with poor or no GNSS signal such as urban canyons. The technology also provides a position accuracy of 0.5 m, even after 60 seconds of no GNSS signal.
The INS is compatible with OxTS Georeferencer, a post-processing and calibration software that aims to improve the accuracy and clarity of user’s pointcloud data. It warms up to specification in three minutes, even with low-dynamic movement, increasing flight time for aerial applications and reducing the space needed for land-based warmups.
Hexagon’s Autonomy & Positioning division and Munhwa Broadcasting Corporation (MBC) have partnered to bring precise positioning to South Korea through the TerraStar-X Enterprise Correction Service. The hardware-agnostic correction service provides instant convergence and lane-level accuracy in automotive, mobile and autonomous applications.
As a leader in real-time kinematic (RTK) positioning across South Korea, MBC’s atmospheric data enhances the redundancy of Hexagon’s fast converging and reliable precise point positioning (PPP) network across the country. Through this collaboration, the TerraStar-X Enterprise service is now supported in testbeds across South Korea, China, Japan, Europe, and North America to accelerate development for advanced driver assistance systems, safety-critical applications, micromobility, industrial and smartphone applications.
“With TerraStar-X Enterprise Correction Services now available across autonomous and consumer market applications, developers can design once and then deploy that design at scale worldwide,” said Paul Verlaine Gakne, positioning services product manager at Hexagon’s Autonomy & Positioning division. “TerraStar-X Enterprise is designed to be as flexible as possible for large-scale testing and deployment.”
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.
KP Performance Antennas has launched its line of vehicle GPS antennas designed for automotive applications.
These antennas come equipped with a high gain of 28 dB and high out-of-band rejection, allowing them to capture weak signals efficiently, even in challenging environments. By minimizing signal interference and multipath effects, the technology aims to provide signal quality and stability to users in applications such as personal vehicles, commercial fleets or autonomous systems.
With waterproof and dustproof ratings of IPX6 or IP66, the antennas can withstand varying outdoor conditions, offering uninterrupted performance even in inclement weather and rough terrains. This design makes them the ideal choice for vehicle tracking, fleet management, telematics and navigation systems.
