California-based Swift Navigation is partnering with Deutsche Telekom, an integrated telecommunications company based in Bonn, Germany. The partnership brings the precise positioning of Swift’s Skylark Cloud Corrections Services to Telekom’s comprehensive communications infrastructure via its new Precise Positioning product offering.
The Precise Positioning service is available across the United States and Germany, with expansion across Europe underway.
Autonomous applications. Autonomous applications, which rely on positioning accuracy, include self-driving cars, rail, autonomous robotic machine navigation, autonomous flight for unmanned aerial vehicles, last-mile delivery logistics, construction safety, and shared mobile positioning.
Swift and Telekom’s lane-level accurate Precise Positioning is specifically designed for level 2 and 3 automotive applications including advanced driver-assistance systems (ADAS), such as lane assist, highway autopilot, cellular vehicle-to-everything (CV2X) communications and lane level directions.
Standard GNSS positioning is accurate to three to five meters — unsuitable for autonomous systems. For higher levels of autonomous capability, high-precision localization is required to deliver accuracy down to the centimeter. This partnership brings the <10-centimeter accuracy of Swift’s precise positioning solution to Telekom customers.
Precise Positioning is a wide area, cloud-based GNSS corrections service that delivers real-time high-precision positioning to autonomous vehicles. Built from the ground up for autonomy at scale, the Precise Positioning service enables lane-level positioning, fast convergence times and high integrity and availability required by mass market automotive and autonomous applications.
Image: Swift
Hardware-Independent. The service is hardware-independent, allowing customers to choose their GNSS sensor ecosystem. It delivers a continuous stream of multi-constellation, multi-frequency GNSS corrections for a high-availability service that combines lane-level accuracy and world-class integrity at a continental scale.
“Swift Navigation is excited to continue our work with Telekom to bring Swift’s precise positioning GNSS expertise to Telekom’s broad customer base,” said Timothy Harris, co-founder and CEO at Swift Navigation. “This partnership is just the beginning of our joint service offering for autonomous vehicles across the EU.”
“Precise Positioning opens the doors to true autonomous mobility. Precise, safe and in the future also cross-national,” said Hagen Rickmann, responsible for business customers at Deutsche Telekom. “We are thus offering our customers an easy entry into the autonomous future. And we’re not just thinking of self-driving vehicles: The flexible offer is also suitable for use with drones and is even of interest to crane operators on construction sites.”
For ease in testing and integration, Swift and Telekom have created a Precise Positioning Evaluation Kit. The kit includes two workshops (onboarding and result review), testing hardware and software to connect to the Precise Positioning network for a three-month evaluation period and is available to purchase.
RoboSense is offering the solid-state lidar RS-LiDAR-M1Simple (Simple Sensor Version), which is less than half the size of the previous version at 4.3 x 1.9 x 4.7 inches (110 x 50 x 120 millimeters).
It is equipped with enhanced hardware performance virtually equal to the serial production version provided to OEMs. The main body design of this automotive-grade solid-state lidar is finalized and ready for shipment.
The RS-LiDAR-M1Smart main body is embedded with an artificial intelligence (AI) perception algorithm that takes advantage of lidar’s potential to transform conventional 3D lidar sensors to a full data analysis and comprehension system, outputting semantic-level structured environment information in real time to be used directly for autonomous vehicle decision making.
The RS-LiDAR-M1 family has the performance advantages of traditional mechanical lidar, simultaneously taking into consideration requirements for the mass production of vehicles.
The RS-LiDAR-M1Smart Features
Adapts to complex traffic conditions.
Supports multiple driving scenarios.
Supports dense traffic flow, such as mixing pedestrians and vehicles in intersections during peak hours.
Comprehensive perception of a wide range of dynamic, static and background objects.
Achieves semantic-level prediction for 3D point clouds.
Handles the challenges caused by two-wheel vehicles (motorcycles, bicycles, etc.) and pedestrians who do not follow traffic rules.
Over-segmentation and under-segmentation are fixed based on the clustering algorithm. The robustness against sparse point clouds ensures the integrity of object detection.
Outputs two redundant channels of data: the original point cloud and the object list. The two channels of data are redundant to provide vehicles with a wide range of sensing results, including dynamic and static and inside and outside the road.
Livox Technology Company has introduced two high-performance, mass-produced lidar sensors, the Horizon and Tele-15, which feature a new scanning method that offers improved sensing performance at a low cost.
The lidar sensors are aimed at L3/L4 autonomous driving, smart cities, mapping, mobile robotics and more.
“The growth potential of the lidar industry has been hindered for too long by ultra-high costs and slow manufacturing rates,” said Henri Deng, global marketing director at Livox. “Livox seeks to change this by providing access to high-quality lidar systems that are easily integrated into a wide array of different use applications. Through our technology, we hope to be the catalyst for the rapid adoption of lidar in the quickly growing industries of autonomous driving, mobile robotics, mapping, surveying and more.”
The environment scanned by a Livox sensor increases with longer integration time as the laser explores new spaces within its field of view (FOV). A Livox Mid-40 or Mid-100 sensor generates a unique flower-like scanning pattern to create a 3D image of the surrounding environment.
Horizon point cloud sample of crossroads with a pedestrian crossing the street. (Image: Livox)
Image fidelity increases rapidly over time. In comparison, conventional lidar sensors use horizontal linear scanning methods that run the risk of blind spots, causing some objects in their FOV to remain undetected regardless of how long the scan lasts.
The non-repetitive scanning method of the Livox lidar sensors enables nearly 100% FOV coverage with longer integration time.
The Horizon and Tele-15 are high-performance lidar sensors designed for L3/L4 autonomous driving applications. The Horizon has a detection range of up to 260 meters with a horizontal FOV (HFOV) of 81.7° which can cover four road lanes at a distance of 10 meters. Its FOV coverage ratio is comparable with a 64-line mechanical lidar at the integration time of 0.1 sec. Using five Horizon units enable full 360° coverage.
Made for advanced long-distance detection, the Livox Tele-15 offers the compact size, high-precision and durability while vastly extending the real-time mapping range. The Tele-15 can scan 99.8% area within its 15° circular FOV at 0.1s.
The Tele-15 can successfully detect an object up to 500 meters away. As a result, Tele-15’s performance allows autonomous driving systems to detect remote objects well in advance, providing more reaction time even at high speeds.
Aircraft throughout Europe are guided by EUROCONTROL, which will have access to ADS-B data through Aireon. Here, a plane lands at Schiphol Airport in The Netherlands. (Photo: Sjo/iStock Unreleased/Getty Images Plus)
Aireon and EUROCONTROL have signed a 10-year agreement to integrate space-based ADS-B data into their air traffic management processes across EUROCONTROL’S 41 Member States and two Comprehensive Agreement (CA) States.
The space-based automatic dependent surveillance-broadcast (ADS-B) data will enhance aircraft management capabilities, contributing to improve predictability, capacity, environmental impact supporting sustainable growth throughout the European region.
It will also support other applications, such as crisis management, contingency management, environmental monitoring, performance monitoring and expanded datasets for post-analysis, traffic statistics and safety-related assessments.
Spanning 43 countries from Turkey to Ireland, Finland to Portugal, EUROCONTROL’s aircraft management states encompass over 11.5 million square kilometers of terrestrial airspace, as well as part of the airspace over the North Atlantic, Mediterranean and Baltic.
Aireon data will be integrated into the EUROCONTROL’s enhanced tactical flow management system (ETFMS), which provides data to European aviation stakeholders, regardless of operational borders, in real time.
Space-based ADS-B data will enrich ETFMS’s complex traffic demand and slot allocation calculations, which currently rely on ground-based surveillance data and flight plan processing systems. As a result, Aireon’s data will support Europe’s primary flow management system to be more accurate in its trajectory predictions and unlock an otherwise unavailable operational capacity.
“With Aireon’s high-integrity, high-quality data, the EUROCONTROL network manager will have the ability to work with information from beyond the European airspace,” said Eamonn Brennan, director general, EUROCONTROL. “Full integration of Aireon space-based ADS-B data will allow us to be more accurate in our trajectory predictions and ensure higher levels of safety, predictability and efficiency in our flow management operations. This partnership is the latest development in our effort to ensure European airspace is one of the most dynamic and efficient in the world.”
EUROCONTROL. Having been nominated as the Network Manager by the European Commission until the end of 2029, EUROCONTROL is driving a coordinated and technologically advanced approach to the challenges faced by the European air traffic network.
Helping address the improvements that are needed in operations, cybersecurity, service provision, crisis management, airspace design, utilization and more, EUROCONTROL provides support and expertise to air navigation service providers (ANSPs), airlines, airports and military partners in the region to help make European aviation, safe, synchronized, efficient and environmentally friendly.
Aerion. In 2019, the European Aviation Safety Agency (EASA) certified Aireon as the first provider of aircraft surveillance-as-a-service. Additionally, Aireon has the only global, single-source dataset available to the industry.
For EUROCONTROL, this means that once the service is integrated into its systems, it will have unprecedented visibility into the full picture of aircraft arriving, departing and crossing over Europe over an area of six flight hours and 3,000 nautical miles around EUROCONTROL Member States.
“EUROCONTROL is a leader in air traffic flow management. They are the first customer to use Aireon data well beyond their own area of responsibility. This will enable them to maximize the effectiveness of their processes and procedures by including long-range arrivals and neighboring States into their capacity and demand measures,” said Don Thoma, CEO, Aireon. “EUROCONTROL recognizes the global value in connecting ANSPs through a common, high-fidelity, global data source that provides situational awareness of actual aircraft position information. We look forward to the benefits all EUROCONTROL customers will see in the near, medium and long-term.”
Aireon’s data will also be integrated in EUROCONTROL’s new system called iNM, which will implement incremental updates to all of EUROCONTROL’s operational systems and digital infrastructure in the course of this decade.
Stan servicing vehicles at the Lyon Airport. (Photo: Stanley Robotics)
Stan incorporates the Trimble BX992 dual-antenna enclosure for accurate, available and reliable localization
The Stanley Robotics team has called on Trimble to equip Stan, its autonomous parking and valet robot, with accurate localization.
To achieve centimeter-level localization, Stanley Robotics needed to combine perception algorithms and intelligent management software with reliable GNSS technology.
“The robot must move fast to handle high traffic flow and precisely to park cars as densely as possible,” said Anthony Troublé, robot team manager at Stanley Robotics. The team selected the Trimble BX992 dual-antenna enclosure and two Trimble AV59 GNSS antennas.
The BX992 is installed inside the robot and the two antennas are mounted on the robot’s head with maximum separation between them. For the robot to attain centimeter-level localization, a Trimble BX992 base and a Trimble Zephyr antenna are installed at the drop-off cabins where customers leave their cars until robots move them to a more permanent location.
The Trimble BX992 base broadcasts real-time kinematic (RTK) corrections over a Wi-Fi link to the robots.
What Stan Does
Photo: Stanley Robotics
With the Stan robotic valet, passengers no longer waste time looking for a free space or trying to locate their vehicle, according to Stan’s creators. After booking their parking space in just a few clicks on the Lyon Airport website, passengers drop off their vehicle in dedicated cabins and make their way to the terminals using the shuttle bus located just a few steps away.
The robot takes care of the car, parking it in the secure car park. When they return, passengers pick up their vehicle, which is waiting for them in one of the cabins.
“The service offers security, simplicity and time savings. With this new technology, parking becomes a no-fuss experience that takes only a few minutes of passengers’ time, leaving them free to travel in a relaxed state of mind,” Stanley Robotics said in a press release.
The system also constitutes a new way of arranging vehicles in a car park and makes excellent use of space since cars can be parked in dense blocks.
In addition, the robot uses two lidar scanners and four cameras. Stan relies on lidar-based simultaneous localization and mapping (SLAM) techniques to locate the robot and build a map. The lidar-based SLAM system is always running and is fused with the GNSS localization and odometry.
“The lidar is mostly critical in the cabins where the GNSS availability and reliability is not sufficient,” Troublé said. “The full integration with our localization system, especially the transition from indoor-to-outdoor when the robot enters a cabin was a challenge. We have tuned and improved our localization fusion algorithm to get the best out of each component and deliver a consistent confidence index.”
Stan is equipped with three levels of safety to ensure operational effectiveness.
First, Stanley Robotics continuously monitors the accuracy, availability and consistency of the RTK GNSS, SLAM and odometry localization signals. “If these signals are too inconsistent or if the overall confidence is too low, the robots are stopped and a site supervisor is alerted,” Troublé said.
Further, the site is monitored through lidars and cameras on the robot to prevent any collision with obstacles.
Finally, a trained Stan maintenance worker is assigned to every parking lot. These individuals wear a safety badge. Every robot is equipped with a safe-stop feature that will trigger if the operator gets within a defined proximity to the robot.
The first outdoor car park managed by robots opened to the public in 2018 at Lyon Saint-Exupéry airport. Since testing started in 2017, four Stan robots are now fully operational in the Lyon Saint-Exupéry airport car park, which can accommodate up to 500 vehicles.
Stanley Robotics announced in January 2019 that they will open 2,000 spaces at Lyon in the summer of 2020. The airport is looking to eventually expand this system to up to 6,000 spaces in total.
In 2019, Stanley Robotics signed a contract with Gatwick Airports, the first U.K. airport to use robots that valet park passengers’ cars. The Stanley Robotics team is gearing up to begin work at another airport to be announced soon.
Robotic Research LLC, a leading provider of autonomy and robotic technologies, will begin testing fully autonomous low-speed shuttles that are totally unmanned in the second quarter of this year.
Current commercial applications of low-speed shuttles use onboard safety attendants to monitor the safety inside and outside the vehicle. Robotic Research plans to start testing without onboard attendants.
The first step is to have the attendants in fixed on-site locations, with the future goal to move attendants to an offsite safety monitoring facility.
“Through our work with the U.S. government over the past four years, we have already demonstrated that fully autonomous trucks are a reality. We are committed to making our shuttle and bus manufacturing partners successful by accelerating state-of-the-art technologies for unmanned vehicles ahead of regulatory agencies’ progress,” said Alberto Lacaze, president of Robotic Research.
“The level of safety certification and redundancy necessary to drive fully autonomous vehicles is a significant undertaking that needs to be designed from the top down. Just adding more ADAS is not a reasonable or cost-effective pathway to full autonomy,” Lacaze said. “The advancements driven by the Robotic Research team will provide a product that significantly reduces the cost of operation and therefore improves market size.”
Current local, state and federal regulations for most commercial shuttle operations require the safety attendant to be inside the cab of the vehicle. However, many transit operators are seeking to change these regulations to allow remote attendants to oversee system safety operations. The change is integral to the viability of low-speed shuttles, which are an innovative solution to the first/last mile problem, which is the distance between a traveler’s origin or destination, and a transit station or stop.
Robotic Research has been developing and testing unmanned, autonomous operations for a wide range of vehicles for nearly a decade. The company currently provides autonomy kits that fully automate logistics convoy trucks for the U.S. government and several of its allied nation partners. Nearly 100 trucks have already been delivered. The tests for these vehicles have included operations with no safety attendants on board, with a single operator monitoring three unmanned vehicles.
Robotic Research’s AutoDrive autonomy kit is platform agnostic and can be retrofitted to vehicles of all sizes, from small, portable robots to large trucks and buses. The system provides autonomous functionality on surfaces ranging from urban-improved roads to off-road terrain, all while the vehicle is collecting and analyzing data to better enhance the future of autonomous vehicles and transportation.
Robotic Research’s technology provides automation to one of the largest international shuttle providers as well as to the largest U.S. manufacturer of commercial buses. The company’s AutoDrive kit also supports various autonomy programs in commercial and government sectors and is currently operating in communities and cities around the globe, including 30 states and four continents.
On Feb. 12, President Donald Trump signed an Executive Order establishing a comprehensive national policy to promote the responsible use of positioning, navigation and timing (PNT) services by the federal government.
The order directs federal agencies to take steps to reduce disruption of critical infrastructure that relies on PNT, including GPS. It also directs critical infrastructure owners and operators to strengthen their systems’ resilience.
Markets affected include including the electrical power grid, communications infrastructure and mobile devices, all modes of transportation, precision agriculture, weather forecasting and emergency response.
The federal government will engage both the public and private sectors to identify and promote responsible use of PNT services, with the goal of ensuring that “critical infrastructure can withstand disruption or manipulation of PNT services.”
“Because of the widespread adoption of PNT services, the disruption or manipulation of these services has the potential to adversely affect the national and economic security of the United States,” the order states. “To strengthen national resilience, the Federal Government must foster the responsible use of PNT services by critical infrastructure owners and operators,” the order reads.
PNT Profiles
The Commerce Department is tasked with developing PNT profiles, due a year from today, for PNT-dependent systems, networks and assets. The profiles will be developed through consultation with the private sector.
The profiles will also:
identify appropriate PNT services;
detect the disruption and manipulation of PNT services; and
manage the associated risks to the systems, networks and assets dependent on PNT services.
The profiles will be reviewed and updated every two years.
Reaction to the Order
Reacting to the Executive Order on PNT, J. David Grossman, executive director of the GPS Innovation Alliance (GPSIA), stated:
“The GPS Innovation Alliance (GPSIA) welcomes today’s Executive Order recognizing the critical economic and societal benefits of GPS and other Global Navigation Satellite Systems (GNSS). Resiliency is among the core attributes that have made GPS the gold standard for delivering positioning, navigation, and timing (PNT) functions to our military as well as a wide range of other sectors, including transportation, agriculture, electricity, and finance. Today’s Executive Order represents a crucial next step in ongoing efforts to maintain the security, robustness, and redundancy of PNT capabilities, including GPS, that millions of Americans rely on every day. GPSIA looks forward to working with key government stakeholders to support the implementation of this effort.”
The Department of Transportation stated,
“Our challenge is to enable increased resilience across our transportation systems and ensure the traveling public and freight transporters experience an increased level of safety and efficiency without the possibility of interference caused by loss or manipulation of PNT.
Department of Homeland Security Acting Secretary Chad F. Wolf said,
“From mobile phone applications to automobile navigation, our digital, interconnected society is dependent every day on PNT services.That is why it’s critically important that PNT services remain properly functioning as a major component of the nation’s critical infrastructure. By adopting responsible use of PNT services, the federal government and owners and operators of critical infrastructure can contribute meaningfully to national resilience and ensure the continuous, uninterrupted delivery of services to the nation.”
A key feature of a new high-accuracy GNSS correction service
Innovation Insights with Richard Langley
INTEGER VITAE SCELERISQUE PURUS. So wrote the Roman poet Horace at the beginning of one of his odes — one which, incidentally, was sung by college choirs at one time. It is usually translated as “upright of life and free from wickedness” and is just about the only common Latin quotation in which we find the word “integer.”
Besides upright, the word can be translated as unimpaired, perfect or whole. It is this latter meaning that the English mathematician Thomas Digges appropriated to describe whole numbers. The modern mathematics definition of the set of integers includes the additive inverses of the whole numbers plus zero. We have to worry about the integer nature of carrier-phase ambiguities when trying to achieve high-precision GNSS positioning but that is a story for another day.
The Latin word integer is the root of the English word integrity. In everyday speech, integrity means the quality of being honest or trustworthy (and having strong moral principles). But it is also used to describe something that is unimpaired or uncorrupted, especially in regard to electronic data such as that provided by a navigation system.
As I wrote in an Innovation column back in 1999, “The performance of any navigation system is characterized by its accuracy, availability, continuity, and integrity. From a safety point of view, integrity is arguably the most important factor. Without some assurance of a system’s integrity, we have no way of knowing whether the information we receive is correct: How are we to know whether a navigation system is actually achieving its advertised accuracy and not misleading us with faulty information?” Navigation systems that provide safety-of-life services must ensure a very high level of integrity. For example, the Wide Area Augmentation System (WAAS) continuously assesses the integrity of GPS satellite signals as well as its own corrections, warning WAAS users when a failure is encountered within about 6 seconds of failure. This helps to ensure that aircraft do not use misleading data that could potentially create hazards.
And now, high-precision GNSS positioning technology using real-time augmentation is being adopted for autonomous applications in the automotive, rail, aviation and marine industries. These applications need high integrity in their position determinations in addition to high accuracy. As with the pioneering non-autonomous aviation use, augmentation services for the new market will need to monitor many aspects of their service to ensure a high level of integrity including the high-end data processing algorithms, real-time data transmission, end-to-end encryption, and functional safety assurance. This will be a challenging task that will require a multi-disciplinary approach, deep understanding of GNSS error modeling and risk assessment.
In this month’s column, we look at the design, construction, operation and performance of the first safety-critical, high-accuracy augmentation service created specifically for autonomous applications.
In addition to the need for high accuracy, the adoption of high-precision GNSS positioning technology for autonomous applications in the automotive, rail, aviation and marine industries has brought with it the need for high integrity and reliability. GNSS integrity concepts had their beginning in safety-critical applications in the aviation and marine industries, which have used GNSS to provide absolute position for precision runway approach, enroute navigation, port approaches, open sea and coastal waterway navigation.
For precision GNSS users (those using precision or high-end equipment) in the surveying, construction and agriculture industries, the focus has primarily been on accuracy. Over the past decade, real-time networks have been developed to offer sub-2-centimeter performance to end users. Although some integrity information has been provided, it has often been in the form of disturbance indices that network operators can use to inform users of suspected down time or periods of poor performance. But the information lacks a functional safety component. Additionally, this information has not typically been integrated in real time into position engines to aid in the generation of reliable integrity parameters for the end users.
Although GNSS does have limitations, particularly in urban environments, GNSS equipment is one of the few sensor types available to system integrators that can provide absolute position in autonomous applications.
This realization — combined with the further miniaturization, lower power consumption and expansion of inexpensive multi-frequency, multi-constellation GNSS chips capable of real-time-kinematic- (RTK-) style processing — has made the adoption of GNSS for mass-market applications very appealing.
Most mass-market applications don’t have the same accuracy requirements that drive the professional high-precision market. TABLE 1 summarizes applications that can benefit from a high-precision GNSS correction service. In most cases, decimeter-to-meter-level accuracy is typically acceptable. Reliability becomes more critical for these applications.
Table 1. Applications that can benefit from a high-precision GNSS service with integrity. (Data: Sapcorda)
The integrity demand, which we define as the degree of difficulty an application poses to the integrity monitoring system, is based on the required accuracy, availability, failure rate and continuity requirements of the application. Applications with a high integrity demand pose the most difficult challenges.
With the spread of autonomous applications in various areas, the likelihood of liability and legal cases being decided based on PVT data provided by the systems is high. This eventuality brings with it a need for a non-proprietary open standard for ensuring consistent implementation of the integrity information and functional safety along with the separation of end-user and provider responsibility. In this article, we describe the requirements and concepts for a high-precision GNSS correction system with high integrity.
SYSTEM OVERVIEW
Our Sapcorda correction service provides high-precision GNSS correction data on a continental scale. Its core component is an underlying tracking network of reference stations used to generate the precise corrections. The reference stations operate in real time and continuously transmit their data to the data control center. The data control center processes the data, computing orbit, clock, instrumental bias and atmosphere corrections and integrity information, and then encrypting the data before broadcasting it to the end user (see FIGURE 1).
The corrections are broadcast in the Safe Position Augmentation for Real Time Navigation (SPARTN) format developed by a consortium of GNSS manufacturers and service providers, via two communication channels, L-band and the internet. The data is then received by the end users who must decrypt it before it is used in processing. The SPARTN correction format consists of a set of messages that broadcast the GNSS corrections in a state-space representation. With our network, Sapcorda can offer a high-accuracy positioning service with fast convergence. An example of positioning performance for a monitoring station in Sapcorda’s European network coverage area is shown in FIGURE 2. The typical accuracy level is close to that of traditional network RTK services.
FIGURE 2. Horizontal position performance for a monitoring site in Europe using Sapcorda’s high-precision service. (Image: Sapcorda)
The system provides coverage for both North America and Europe as shown in FIGURE 3. Unlike traditional local or regional network RTK systems, Sapcorda’s network provides seamless coverage on the continental scale and operates in broadcast-only mode.
The integrity of a system can be described as the trustworthiness of the positions generated by the position engine. Trustworthiness is defined by the protection level associated with a given solution. Many of the concepts related to GNSS integrity originated from the development of the Wide Area Augmentation System (WAAS). The integrity concept was formalized by the Stanford Integrity Diagram, which outlines the key concepts related to integrity. TABLE 2 defines the terminology surrounding the integrity concept.
Table 2. Integrity terms. (Data Sapcorda)
The integrity risk is the probability that a user will experience a position error larger than the alert limit without an alarm being triggered. When this occurs, the user is in a potentially dangerous situation as the system is providing dangerously misleading information to the user, who is unaware.
The protection levels are computed based on the expected behavior of the error sources encountered in a GNSS positioning system. If the protection level is less than the system’s alert limit, then the system is operating within its normal bounds. If the error sources are not properly monitored or quantified, protection levels become optimistic. This occurs when the true position error, which is typically unknown, exceeds the protection level supplied by the system. When this situation occurs, it is labeled hazardously misleading information (HMI) because the system may believe that its position is more accurate than it truthfully is. If the true position error remains less than the alert limit, then this is classified as misleading information. As the true position is not beyond the alert limit, the operator/system can continue to rely on this information without being in a potentially dangerous scenario.
To define the true integrity risk of the system, it is necessary to understand its error sources, threat models, frequency of occurrences and potential failure modes. Many threats could render a correction service unavailable, including hardware failures, data outages or software bugs, atmospheric anomalies and satellite failures. The following section describes these threats along with the capabilities used for monitoring them.
Error Sources. The primary error sources in high-precision GNSS positioning are described in TABLE 3.
Table 3. GNSS network error sources, their magnitude and mitigation approach. (Data Sapcorda)
Although not mentioned in this table, additional error sources include site displacement effects such as solid earth tides, ocean tide loading and polar tides; carrier-phase wind-up at both the receiver and satellite; and satellite and receiver antenna phase-center variations and relativistic delays. These effects must be consistently modeled at both the server and the end-user for centimeter-level positioning.
Based on the error sources described in Table 3, it is necessary to convert this information into a format that can be used by the position engine to derive protection levels for each solution. How the final protection level is derived by a position engine is not within the scope of this article. For this, several approaches can be used including carrier-phase-based receiver autonomous integrity monitoring (CRAIM), solution separation and others.
The following equation can be used to describe the overall error contribution for each measurement:
where
is the total uncertainty for satellite i
is the uncertainty of the ionosphere model
is the uncertainty of the troposphere model
is the uncertainty of the combined orbit, clock and bias (ephemeris) corrections
is the uncertainty of the measurements in the given environment
The terms , and are derived from the real-time reference network operator while the term must be computed by the end-user receiver. This final term is perhaps the most difficult to determine, particularly for kinematic environments, as the value is highly dependent on antenna quality, multipath and measurement quality.
PERFORMANCE AND RESULTS
We processed 24 hours of data at three stations covered by Sapcorda’s European network and within the red circle shown in FIGURE 5.
FIGURE 5. Location of stationary testing carried out within Sapcorda’s European network. (Image: Sapcorda)
The test stations were situated in an open-sky environment with high-quality geodetic antennas and receivers. The position results and protection levels were derived from Sapcorda’s own position engine.
FIGURE 6. Integrity plots for the horizontal error and protection levels for three stations within Sapcorda’s European network coverage area.(Image: Sapcorda)
FIGURE 6 shows the horizontal component integrity plots for the three stations. The protection levels are computed for the five-sigma level. In all three examples, the protection level can properly bound the horizontal position error. In terms of the measured accuracy, the typical performance observed at the three stations is between 3 and 7 centimeters for the 95th percentile.
In addition to the stationary testing, two kinematic trials were carried out in cooperation with a system integrator. The integrator setup consisted of a commercial RTK receiver and position engine being fed with SPARTN corrections. The equipment was mounted onto the vehicle used for the tests. Both tests were carried out in an urban environment, which introduced measurement outages due to trees, overpasses and urban canyons. FIGURE 7 shows the area in which the kinematic trails were carried out, as well as some of the urban conditions with which the system had to contend.
FIGURE 7. Location of kinematic trials using Sapcorda’s North American correction service and examples of the environment encountered during the testing. (Image: Sapcorda)
FIGURES 8 and 9 show the position performance and integrity plots for the two kinematic trial scenarios. The reference trajectory was computed using a short baseline post-processed kinematic solution computed with a third- party application. The typical accuracy of the Sapcorda-enabled solution was on the order of 2 to 4 centimeters, while the maximum error was 10 centimeters. In both cases, the protection levels were able to properly bound the horizontal position error. Figure 8 shows an area of increased position error, which occurs around the 22.6- to 22.7-hour mark of the day. This period coincides with the image in the bottom right of Figure 7, where the vehicle passes into a difficult environment with overhead trees and walkways, as well as significant shading from a tall building. Even in this type of environment, the protection levels were able to properly bound the horizontal position error.
FIGURE 8a. Horizontal position performance for kinematic trial #1. The red line indicates the 1-sigma error of the position engine. (Image: Sapcorda)FIGURE 8b. Horizontal position performance for kinematic trial #1: The 5-sigma integrity diagram. (Image: Sapcorda)FIGURE 8b. Horizontal position performance for kinematic trial #1: The 5-sigma integrity diagram. (Image: Sapcorda)FIGURE 9b. Horizontal position performance for kinematic trial #2: The 5-sigma integrity diagram. (Image: Sapcorda)
In addition to the position performance, re-initialization time plays a critical role for precise positioning systems operating in difficult environments. Due to the regular outage and signal blockages, which occur in urban environments, the re-initialization time is critical to providing high availability. Traditional precise point positioning (PPP) systems, even those that perform ambiguity resolution, can take anywhere from 5 to 20 minutes to re-initialize and achieve an acceptable accuracy level (typically 10 centimeters) after a complete outage. Researchers in both academia and industry have developed several methods to reduce this time by “bridging the gap” after outages.
However, these approaches rely on assumptions about either the vehicle trajectory or the stability of the ionosphere before and after outages. The impact of these assumptions on overall integrity have not been adequately studied. Systems that rely on inertial measurement units (IMUs) to constrain the position after an outage introduce a dependency between what should be two independent sensors in the overall system.
FIGURE 10 shows the re-initialization time of the integrator’s position engine when using Sapcorda’s correction service. In this case, the re-initialization time is computed as the time it takes to return to RTK-ambiguity-fixed mode as indicated in the position engine output after an outage. Results based on comparisons against short-baseline RTK positioning showed typical accuracies below 10 centimeters upon re-initialization. In this definition, the time of the outage is included in the overall re-initialization time. In nearly all of the 42 occurrences, the time to re-initialize is less than 10 seconds. This is sufficient to allow an IMU to provide position updates during the GNSS outage.
FIGURE 10. Re-initialization time of the integrator’s position engine enabled by Sapcorda’s correction service. (Image: Sapcorda)
SYSTEM DESIGN CONSIDERATIONS
In addition to understanding GNSS error sources and performance, it is also important to consider the integrity of the entire system. This includes software development processes, hardware selection, data communication standards and security.
Software Design
Aspects needing to be addressed include:
Software Coding Standards. As software is used more and more in safety-critical scenarios, standards have been developed to minimize common errors and failures. Some standards relevant for safety-critical applications development include International Organization for Standardization (ISO) standard 26262 and Motor Industry Software Reliability Association (MISRA) C/C++ coding standards. Many of these standards can be automated via the static analysis tools described below.
Functional Safety. The objective of this analysis is to understand the possible failure modes of a system, how likely they are to occur, and how to mitigate their risk. Several methods can be applied for functional safety analysis. One such approach is failure mode effect analysis (FMEA). In general, functional safety analysis is a complex task requiring a wide range of experience and expertise. Understanding how design or feature choices impact overall failure modes is also critical for simplifying the number of cases and overall system complexity.
Test Coverage. Unit tests provide the fundamental verification that a function can perform its expected task. Coverage analysis tools provide insight into which sections, paths and combinations are being tested. Various metrics are possible, including:
statement coverage: measures the number of executable lines of code that are evaluated
branch coverage: measures which code paths are being evaluated (for example, if statements, both true and false must be covered)
modified condition/decision coverage (MC/DC): in addition to checking all branches, all combinations of branches must be considered.
The degree of effort to meet target coverage metrics greatly varies based on the type of metric chosen.
Code Quality Metrics. Code quality metrics attempt to reduce the complexity of functions and methods in the software. Code quality metrics may include:
cyclomatic complexity scores
establishing the maximum number of control statements within a function
establishing the maximum number of lines or methods called within a single function.
Static Analysis. Static code analysis provides an examination of source code prior to execution. It can detect common implementation issues such as divide-by-zero errors, bounds overrun, poorly defined loops or control statements, among others. Most commercial products provide support for MISRA C/C++ guidelines and other best practices for safety-critical applications.
Automated Testing. Test automation is critical for monitoring performance changes and ensuring high-quality code changes. Critical scenarios such as leap-second changes, week rollovers and ephemeris failures can be logged and then used as part of the automated test plan. And, as bugs emerge, adding additional test scenarios for these is also beneficial.
Data Communication Protocol
One must also consider several aspects related to the transmission of the correction service to users.
Open Source. A standardization of an open-source data communication protocol for mass-market applications allows for a receiving system to employ multiple corrections from more than a single specific provider without requiring independent functional safety requirements. This can provide a much higher level of redundancy than is possible when depending on only a single service provider.
Integrity and Functional Safety. To properly quantify the protection level, it is necessary to provide quality information about the corrections being provided by the service. Employing “do not use” flags ensures users drop satellites that may be unhealthy or performing poorly. General system status messages identifying the cause of a failure are also critical for proper separation of issues between server and recipient.
Encryption and Anti-Spoofing. As the use of GNSS expands, the threat of spoofing has become more significant. Data message encryption must be robust and resilient to protect the user of the data against external threats.
Self-Contained and Repeatable. Replication of events is important for safety-critical applications. A message format used for such applications should be self-contained and not rely on any external sources for factors such as initialization or the expansion of data. This may include the expansion of time-tagged data, or limiting the expansion of ephemeris to a specific Issue of Data Ephemeris (IODE).
SUMMARY
High-precision GNSS correction services for applications requiring both accuracy and integrity will continue to grow. To meet these demands, GNSS correction services that previously focused on accuracy as their primary goal must begin to work toward providing adequate integrity information to provide reliable positions and protection levels. This requires a multidisciplinary approach to achieve an in-depth understanding of GNSS error sources, integrity concepts and functional safety.
End users will benefit from the clear separation of the server and recipient responsibilities and through an open communication standard that facilitates the use of multiple correction service providers and is developed with safety and integrity at its core.
The adoption of formal safety practices, including software development strategies to reduce risk and mitigate errors, is also critical in achieving a reliable and safe high-precision correction service.
ACKNOWLEDGMENT
This article is based on the paper “Integrity for High Accuracy GNSS Correction Services” presented at ION ITM 2019, the 2019 International Technical Meeting of The Institute of Navigation, Reston, Virginia, Jan. 28–31, 2019.
LANDON URQUHART is the R&D engineering manager for Sapcorda Services Inc., with offices in Berlin and Hanover, Germany, and Scottsdale, Arizona, USA. He obtained his M.Sc.E. from the Department of Geodesy and Geomatics Engineering at the University of New Brunswick (UNB), Fredericton, Canada. His research interests are GNSS correction services for mass-market applications.
RODRIGO LEANDRO is the chief technology officer at Sapcorda Services in Scottsdale. He holds a Ph.D. in spatial geodesy from UNB. Dr. Leandro has been active in GNSS R&D for more than 15 years and has served in engineering leadership roles in various companies in the GNSS industry.
PAOLA GONZALEZ is a product engineer at Sapcorda Services and is based in Hanover. She completed her B.Sc. in geodesy at Zulia University in Maracaibo, Venezuela, and her master’s degree in geomatics at Karlsruhe University of Applied Sciences in Karlsruhe, Germany. In the past few years, she has been working in the GNSS industry, focusing mostly on performance analysis, evaluation and verification of different equipment, software and services.
FURTHER READING
• Authors’ Conference Paper
“Integrity for High Accuracy GNSS Correction Services” by L. Urquhart, R. Leandro and P. Gonzalez in Proceedings of ITM 2019, the 2019 International Technical Meeting of The Institute of Navigation, Reston, Virginia, Jan. 28–31, 2019, pp. 543–553, https://doi.org/10.33012/2019.16709.
• GNSS Integrity
“GNSS Position Integrity in Urban Environments: A Review of Literature” by N. Zhu, J. Marais, D. Betaille and M. Berbineau in IEEE Transactions on Intelligent Transportation Systems, Vol. 19, No. 9, September 2018, pp. 2762–2778, doi: 10.1109/TITS.2017.2766768.
“Carrier Phase-based Integrity Monitoring for High-accuracy Positioning” by S. Feng, W. Ochieng, T. Moore, C. Hill and C. Hide in GPS Solutions, Vol. 13, No. 1, January 2009, pp. 13–22, doi: 10.1007/s10291-008-0093-0.
“New Tools for Network RTK Integrity Monitoring” by X. Chen, H. Landau and U. Vollath in Proceedings of ION GPS/GNSS 2003, the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, Sept. 9–12, 2003, pp. 1355–1360.
“The Integrity of GPS” by R.B. Langley in GPS World, Vol. 10, No. 3, March 1999, pp. 60–63.
• Satellite-Based Augmentation Systems
“Satellite Based Augmentation Systems” by T. Walter, Chapter 12 in Springer Handbook of Global Navigation Satellite Systems, edited by P.J.G. Teunissen and O. Montenbruck, published by Springer International Publishing AG, Cham, Switzerland, 2017.
Minimum Operational Performance Standards for Global Positioning/Satellite-Based Augmentation System Airborne Equipment, RTCA/DO-229E, prepared by SC-159, RTCA Inc., Washington, D.C., Dec. 15, 2016.
“The Stanford – ESA Integrity Diagram: A New Tool for The User Domain SBAS Integrity Assessment” by M. Tossaint, J. Samson, F. Toran, J. Ventura-Traveset, M. Hernandez-Pajares, J.M. Juan, J. Sanz and P. Ramos-Bosch in Navigation, Journal of The Institute of Navigation, Vol. 54, No. 2, Summer 2007, pp. 153–162.
“Validation of the WAAS MOPS Integrity Equation” by T. Walter, A. Hansen and P. Enge in Proceedings of the 55th Annual Meeting, The Institute of Navigation, Cambridge, Massachusetts, June 28–30, 1999, pp. 217–226.
“WAAS MOPS: Practical Examples” by T. Walter in Proceedings of NTM 1999, the 1999 National Technical Meeting of The Institute of Navigation, San Diego, California, Jan. 25–27, 1999, pp. 283–293.
• Jamming and Spoofing
“Interference” by T. Humphreys, Chapter 16 in Springer Handbook of Global Navigation Satellite Systems, edited by P.J.G. Teunissen and O. Montenbruck, published by Springer International Publishing AG, Cham, Switzerland, 2017.
• Ionospheric Threats
“Ionospheric Impact on GNSS Signals” by N. Jakowski, C. Mayer, V. Wilken and M.M. Hoque in Física de la Tierra, Vol. 20, 2008, pp. 11–25.
“Ionospheric Disturbance Indices for RTK and Network RTK Positioning” by L. Wanniger in Proceedings of ION GNSS 2004, the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation, Long Beach, California, Sept. 21–24, 2004, pp. 2489–2854.
On a test track in Sweden, a truck successfully merged between two cars driving alongside it in a fully automated maneuver. The live demonstration took place at the AstaZero test site near Borås, Sweden, on Nov. 21, 2019, showing automotive industry experts how well the automated merging solution performed.
The Fraunhofer Institute for Integrated Circuits IIS and project partners RISE, Scania, Waysure, Ceit-IK4, Baselabs and Commsignia are taking part in an EU-funded project PRoPART, which stands for Precise and Robust Positioning for Automated Road Transports.
Vehicles on the road already perform certain steps on behalf of the driver, such as parking. Together with its project partners, the Fraunhofer IIS has developed a precise and robust position determination system for use in autonomous trucks as part of PRoPART.
Autonomous driving is about interactions among vehicle systems, connecting vehicles and equipping them with precise and robust navigation solutions. The challenge is to ensure that different automated driving systems deliver precise and reliable positioning information.
Using GOOSE technology
With its GOOSE GNSS receivers, Fraunhofer IIS provides highly accurate and reliable positioning to the PRoPART project. The GOOSE can bridge signal interruptions for short periods of time, potentially obviating the need for the driver to intervene at all.
In conjunction with GNSS, developers are using a combination of sensors such as radar and cameras in the vehicle. Supplemented by reference stations along the route, the combination of GNSS and sensor data enables highly available position solutions up to the decimeter range.
“This is a key step on the road to autonomous driving,” explained group manager for precise GNSS receivers Matthias Overbeck, Fraunhofer IIS. “It’s about ensuring the merging maneuver is precise and avoiding accidents — something we can achieve only with highly accurate and reliable positioning technology.”
GOOSE platform. (Photo: Fraunhofer IIS)
Spoofing protection
These days, a variety of electronic systems for providing satellite navigation signals are available and are often used to generate fake positions for gaming apps on smartphones. Such systems could disrupt satellite receivers while remaining undetected.
GOOSE makes use of the Galileo Open Service Navigation Message Authentication (OS-NMA), which is not officially available until 2020. OS-NMA transmits encrypted keys on the Galileo satellite signals that make it extremely difficult to fake a position, thus ensuring that reliable positioning information can be provided to vehicles in the future.
Sapcorda Services GmbH has released its SAPA (Safe And Precise Augmentation) Premium GNSS positioning service.
The SAPA service enables mass-market GNSS devices to operate with increased accuracy and reliability across Europe and the continental United States. The service’s technology unlocks advanced performance with instantaneous sub-decimeter position accuracy for devices used in all market applications.
SAPA is delivered using the open industry-recognized SPARTN format, which allows efficiently delivery of the correction data via internet and satellite broadcast. “When using our service, users across Europe and the United States can experience homogeneous, gap-free, advanced positioning performance with any GNSS hardware designed for high precision positioning,” CTO Rodrigo Leandro said.
The SAPA service is tailored for mass-market applications including innovative mobility solutions, IoT applications, and traditional markets such as maritime.
SAPA was designed from ground up to support safety-critical applications such as autonomous driving.
SPARTN (Safe Position Augmentation for Real-Time Navigation) is a high-accuracy, open- and free-to-use GNSS format tailored for broadcast distribution in mass-market applications.
Sapcorda Services GmbH is a GNSS service provider focusing on the emerging high-precision GNSS mass markets. The company has designed its technology and service offering to serve high volume automotive, industrial and consumer markets.
At ION GNSS+ in September, I met with Nunzio Gambale and Paul Benshoeff of Locata. They were excited to share their news about the timing tests conducted at White Sands Missile Range by the U.S. Air Force’s 746th Test Squadron.
In the January issue, we share the results of the tests. The two also showed me and Matteo Luccio, our contributing editor, a YouTube video highlighting another Locata project: guiding 100-ton robots around the Ports of Auckland, New Zealand.
The robots are straddle carriers, giant mechanisms that are usually driven by a human. The carriers move and sort the shipping containers as they arrive from ships and leave via truck or train.
In the new setup, Locata has made possible the elimination of the human element with nanosecond-precision tracking.
Tom Scott, a former Sky One television host and now host of a series of YouTube shows, highlighted the robotic system in April 2019 on his “Amazing Places” channel.
Screenshot: Tom Scott video
Compared to manned straddle carriers, the automated straddle carriers (A-STRADs) are able to stack the containers closer, higher and work more steadily, increasing the capacity of the limited land space at the port. The A-STRADs can stack containers with the accuracy of a few centimeters.
The automated system also allows stack shuffling, so that wear and tear on the asphalt is spread more evenly and requires fewer repairs.
The Locata local positioning system uses synchronized transmitters installed around the port, with two antennas on each straddle carrier using the lightspeed delay from each transmitter to find exact position. “They don’t just look at the timing signal itself, they track the phase of each transmitter’s carrier signal,” Scott explained.
Photo: Christian Johnson/University of Mississippi
As University of Mississippi (UM) students resume classes for the spring semester, they are sharing the campus’ sidewalks with a fleet of robots that can deliver meals at the push of a button.
Starship Technologies has launched robot food delivery services at the university, the first in the Southeastern Conference to have autonomous delivery robots.
Beginning Jan. 22, Ole Miss students, faculty and staff can access the Starship Deliveries app (iOS and Android) to order food and drinks to be delivered anywhere on campus, within minutes from any of the 30 robots serving UM. The service will work in conjunction with student meal plans.
“Ole Miss Dining is focused on the continued utilization of advanced technology to enrich the student, faculty and staff dining experience,” said Chip Burr, resident district manager of Ole Miss Dining Services. “We are excited about the expansion of our mobile ordering operation and the new opportunities this partnership creates.”
The robots use a combination of sophisticated machine learning, artificial intelligence and sensors to travel on sidewalks and navigate around obstacles. The computer vision-based navigation helps the robots to map their environment to the nearest inch. They can cross streets, climb curbs, travel at night and operate in both rain and snow.
A team of humans also can monitor their progress remotely and take control if needed.
By making food and drink more accessible, the Starship robots save time and reduce stress, aiming to make the busy lives of the Ole Miss community a little easier, Burr said.
Items can be ordered from Starbucks, Chick-fil-A, McAlister’s, Panda Express, Which Wich, Qdoba, Einstein Bros. Bagels, Raising Cane’s, Steak ‘n Shake, Freshii, Papa John’s and Sambazon. After choosing their items, users select their location by dropping a pin on the campus map where they want their food delivered.
The app allows users to watch the robot’s journey in real time through an interactive map. Once the robot arrives, the user will receive an alert and can meet the robot and unlock it through the app.
The delivery usually takes just minutes, depending on the menu items ordered and the distance the robot must travel. The robots can carry up to 20 pounds.
Starship Technologies operates commercially on a daily basis around the world. Its robots have traveled more than 350,000 miles and completed 100,000 autonomous deliveries.
“We’re honored to be able to help make lives a little bit easier for Rebels across the Ole Miss campus by offering the world’s leading autonomous delivery service,” said Ryan Tuohy, senior vice president of business development at Starship. “Whether it’s getting breakfast delivered in the morning or having a late-night snack, our robots are here to serve students, faculty and staff at all times of the day.”
