Carlson Software is now offering its next-generation multi-frequency, multi-GNSS BRx7 smart antenna.
The BRx7 is a full redesign of Carlson’s flagship GNSS receiver, delivering high-level specifications, performance and value for surveyors, contractors, engineers and GIS professionals.
Weighing 2.8 pounds with batteries, the BRx7 saves time and increases productivity by accurately compensating for tilt. It comes standard with dual, hot-swappable batteries for 11+ hours of uninterrupted efficiency. The BRx7 provides 800+ channels, 8gb of memory, and is designed with a rugged, compact IP67-rated housing.
Best-in-class RTK performance is provided by the Athena GNSS engine, supporting multi-frequency GPS, GLONASS, BeiDou, Galileo, QZSS, IRNSS and Atlas L-band capability. In addition, the BRx7 uses proprietary SureFix technology to provide a high-fidelity quality indicator of the RTK solution, allowing users an extremely high confidence in their current accuracy.
The BRx7 provides RTK baselines up to 50 km with fast acquisition times when used with Carlson Listen-Listen, as well as UHF, spread spectrum, cellular, Bluetooth and Wi-Fi wireless communication.
Well-suited to a variety of operating modes, the BRx7 can be deployed as a powerful base with additional access to BeiDou phase 3 satellites in a base-rover setup, or as a lightweight, powerful network rover.
“The BRx7 represents the next generation of GNSS technology,” said Butch Herter, Carlson’s director of hardware development. “Through this total redesign in partnership with our manufacturer, Hemisphere GNSS, we’ve brought the technology and functionality above the competition while retaining the ease-of-use, durability, and superior support that Carlson is known for.”
The smart antenna comes with a dual-band radio module that is capable of both 400 MHz and 900 MHz operation. This allows for the long range capability of the UHF 400 MHz signal plus the ability to switch to the 900 MHz frequency-hopping spread spectrum (FHSS) signal for better performance in noisy radio environments.
The BRx7 introduces a new INS-based sensor-fusion platform to support enhanced tilted pole measurements for land survey applications. This new design allows for easy calibration, is immune to magnetic interference, and is extremely reliable in virtually any environment.
“The BRx7 represents the advanced technology, durability, and ease-of-use that our customers have come to expect,” said Bruce Carlson, founder and president of Carlson Software. “By redesigning this system from the ground up, we are offering our customers both unparalleled performance and versatility, but also a value that’s unbeatable in the market today.”
Thirty years ago, more than a decade before most people had even heard of GPS, receiver manufacturers and surveyors were already improving on it by providing and using correction services to compensate for errors in the system—including clock drift, orbit errors, signal errors, atmospheric errors and multipath.
Today, dozens of public and commercial correction services enable users to achieve accuracies of decimeters, centimeters or even millimeters. Also, many GNSS processing services correct measurements taken in the field using data from reference points. Increasing positioning accuracy has become the cornerstone of modern GNSS practice.
The current boom for correction services is driven mostly by the demand for high accuracy from the automotive industry (including the development of self-driving cars), as well as smart consumer devices and various forms of automation. Automotive companies and telecoms are deploying infrastructure around the globe to provide centimeter-level positioning. GNSS satellites also can transmit corrections directly, as the Japanese CLAS service from the QZSS constellation does, and Galileo’s High-Accuracy Service (HAS) soon will. To compensate for receiver-side issues — multipath, jamming and spoofing — some GNSS receivers also incorporate advanced positioning algorithms.
Clock and orbit errors are specific to each satellite; they do not depend on the position of the receiver. But atmospheric errors are introduced when the signal travels from the satellites to the user. Reference stations (base stations) of GNSS receivers installed at fixed and precisely surveyed positions provide corrections that compensate for both sets of errors to the rovers carried by field crews. When connected, reference receivers spread over a geographic area form reference networks, such as that of continuously operating reference stations (CORS). Achieving maximum accuracy requires initializing the receiver, which can take a few seconds to several minutes, depending on the type of corrections.
Established and new methods
Two established methods have been used for decades.
Real-time kinematic (RTK). In RTK, a receiver obtains correction data from a single base station or a local reference network in the same area.
Precise point positioning (PPP). While accessible from anywhere in the world, receiver initialization for PPP can take up to 30 minutes. Also, a few PPP correction services only provide corrections for satellite clock and orbit errors and not for atmospheric errors, limiting users to a lower accuracy level than with RTK.
Hybrid PPP-RTK. In recent years, new methods have emerged. Hybrid PPP-RTK combines near-RTK accuracy and quick initialization times with the global access of PPP. It relies on a network of reference stations within about 150 kilometers of each other. The stations collect GNSS data and calculate both satellite and atmospheric correction models. The network then broadcasts these corrections via internet, satellites or cellphone towers to subscribers, who can use them to achieve sub-decimeter accuracy.
Each of these methods has advantages and disadvantages (see table 1). RTK, which relies on communication between the user and the local correction service, provides centimeter accuracy over small areas. PPP-RTK and PPP broadcast corrections and require a lighter infrastructure, making them scalable for mass-market and industrial applications. The new services are cheaper and more user-friendly than traditional correction services.
TABLE 1: Differences of various correction methods. (Chart: Septentrio)
CORS/VRS
Traditional reference networks — often called CORS or virtual reference station (VRS) networks — have long been a source of differential GPS (DGPS) and RTK corrections, mainly for surveying and mapping applications, which require high accuracies.
“Most CORS in the United States are strictly for providing high-accuracy correction data to GNSS users who need to know their position to less than an inch,” said Alex Ngu, applications engineer at Trimble. “However, some — like Utah’s TurnGPS network and the North Carolina Geodetic Survey (NCGS) — have considered dabbling in using them to double up for weather monitoring.” In some regions, such as Japan and Washington state, CORS are also used to study plate tectonics and provide early warning of earthquakes.
CORS receivers often operate in remote locations and may be powered by solar panels. Therefore, they require low power consumption and the ability to configure, run and update remotely. They also need to archive on-board measurements and withstand harsh environments.
Changes in the market
As the market for GNSS corrections changes, so does the role of CORS networks. They are increasingly used for industrial automation that needs centimeter accuracy, including construction and agriculture. “Now, due to the growth in autonomous systems, such as autonomous cars, people are looking at corrections in a completely different way and with more focus on mass markets,” said Gustavo Lopez, market access manager at Septentrio. Septentrio lets customers choose which correction service to use.
“CORS/VRS networks will keep focus on performance and on adding constellations and signals, but nothing major is expected to happen in these traditional systems,” Lopez said. They will continue to exist because they focus on centimeter-level accuracy for survey, construction, mining, machine control and precision agriculture. “What will really change the market are these new services with 10-cm to 20-cm accuracies, which also offer a new way of delivering the data, namely broadcasting rather than using two-way communication methods.” This helps with adoption by emerging applications, Lopez said.
He predicts that applications needing 10- to 50-centimeter acurcy will migrate to cheaper services, including new consumer applications, advanced driver-assistance systems (ADAS), professional applications such as robotics, UAVs, logistics and internet of things (IoT) applications.
Mobile technologies adopting dual-frequency chipsets also will need correction services. “We will see more and more telecoms interested in providing GNSS corrections as a service, as is already the case in Asia and Europe,” Lopez said. “A few CORS/VRS networks will try to capture part of this emerging applications market by reusing their technology or partnering with other companies to provide a more transparent solution.”
One might think that the rapid expansion of the market for corrections would make it possible for traditional CORS networks to make 1-cm accuracy available at a much lower price. The roadblock is high infrastructure costs, Lopez explained. CORS/VRS networks are expensive to maintain because they require a high density of stations. New services that use broadcasting technology and PPP-RTK positioning modes rely on less dense networks.
New uses for old CORS
A key benefit of a VRS is that performing RTK positioning across the area it covers does not require guarding a separate GPS base station. Using VRS, the CORS network acts essentially as a continuous reference station within the entire network, enabling RTK positioning using a single rover in the field.
Randy Osborne, VRS network manager at Louisiana State University’s Center for GeoInformatics, reports a growth in new applications beyond surveyors. VRS expanded to precision agriculture, and then into applications such as lidar and UAVs. “We are also seeing strange applications that we never thought of. For example, plumbing companies use it to navigate underground from a truck that has a position on the network, and then they vector from the truck underground into pipelines,” Osborne said. Subscribers also include companies performing survey work for fracking and petrochemical projects.
OSR vs. SSR
Most GNSS correction services are based either on the observation state representation (OSR) or on a state space representation (SSR) of the errors. OSR and SSR use different techniques, delivery mechanisms and core technologies.
OSR. Legacy GNSS correction service providers supply OSR correction services; examples are RTK and networked RTK (RTN). They rely on transferring corrected GNSS observations from the nearest reference station to the rover using a standardized format. They focus on a geographic region and target surveying, machine control and precision agriculture, providing centimeter-level accuracy up to about 30 kilometers of the nearest reference station. Because these services require bi-directional communications and large bandwidth, it is hard to ramp them up for mass-market applications.
SSR. By contrast, new players in the market for correction services, as well as some of the larger legacy ones, provide SSR correction services. SSR uses a network of reference stations to model major errors over large areas. They then transfer this model to the rovers, which create local error models and apply them to their GNSS observations. Depending on the service, accuracy ranges from less than 5 cm to 20 cm, convergence times from 10 seconds to 30 minutes, and coverage from continental to global. Because SSR corrections are broadcast, they can be more easily distributed through internet connections and L-band satellite channels. Because all the rovers rely on the same stream of GNSS correction data, SSR services work well for mass-market applications. The growth in SSR technology is driven mainly by the needs of the automotive industry but is sufficiently generic for adoption in other markets.
The challenge of vertical accuracy
A CORS receiver stands atop the Old River Auxiliary Control Structure, a floodgate system in a branch of the Mississippi in central Louisiana. (Photo: Trimble)
While OSR and SSR have comparable accuracies on a horizontal plane, they differ greatly in their vertical accuracy and initialization times, Osborne said. “When we look at CORS for active control and positioning in the National Spatial Reference System, we are mainly trying to get a handle on the vertical part, as it is the hard problem to solve,” he said.
High-precision vertical accuracy is a challenge for any GNSS-based method. Conventional surveying is still the gold standard. With differential leveling, like with digital levels, results in millimeters are possible. Post-processed GNSS, using data from a good geometry of CORS or base data, can yield results under 2 cm vertical, as can real-time OSR methods like RTK and RTN. SSR solutions, like PPP and hybrids, are presently achieving 5 cm at best. An Achilles heel for SSR vertical solutions is the lack of data for localized sources of error, like tropospheric conditions. Semi-dense networks of CORS can feed ionospheric data to speed PPP convergence, but not the level of tropospheric data needed to match the vertical results that OSR and conventional methods can.
Trimble
Trimble GNSS base-station receivers have been used for 40 years on every continent, according to the company. Today, products in use as CORS stations typically are Alloys, NetR9s and NetR5s. The company operates more than 300 networks worldwide, incorporating more than 5,000 CORS receivers.
Trimble offers a full spectrum of solutions, services and subscriptions related to CORS networks. They range from supplying CORS software, hardware and services, to providing network management services to run a secondary backup system for a network, or even operating a network on behalf of its owner. For those who just want a high-accuracy correction to support their surveying, GIS or machine guidance and control work, “Trimble operates one of the largest CORS networks in the world to which users can subscribe — Trimble VRS Now, Trimble RTX and OmniSTAR services,” Ngu said.
Feature photo:
In Long Beach, California, correction services support the 250-foot-high Gerald Desmond Bridge project. Trevor Rice (left), president of D. Woolley & Associates, joins Kimberley Holtz, director of survey, Port of Long Beach. (Photo: Trimble)
Tersus GNSS Inc. has released the BX40C RTK board to support its series of GNSS boards and provide highly accurate and fast positioning services.
Powered by the company’s new ExtremeRTK GNSS technology, the BX40C board can support multi-constellation and multi-frequency all-in-view satellite tracking.
The Tersus BX40C is a compact GNSS real-time kinematic (RTK) board with full constellation tracking for providing centimeter-level accuracy positioning. It can be integrated with autopilots and inertial navigation units to meet various developing requirements. It is suitable for high-precision positioning, navigation and mapping.
“Tersus has been proud of its BX-series RTK boards, and today we added a new member to the series by launching the new BX40C board,” said Xiaohua Wen, founder and CEO of Tersus GNSS. “The BX40C is with enhanced positioning accuracy and constellation tracking, even in harsh environments, the BX40C board can still control deviation within 3-centimeter in surveying and mapping applications. It supports 576 channels and can achieve centimeter-level position accuracy easily. We are excited to see how BX40C strengthens our product portfolio and technology competence to make a great effort in this industry.”
The BX40C board supports multiple constellations and frequencies to improve the continuity and reliability of the RTK solution — even in harsh environments. In-built 4GB memory makes data collection easy, the company said. It is compatible with other GNSS boards in the market via flexible interfaces, smart hardware design and commonly used log/command formats.
Xsens, manufacturer of motion-tracking modules, has launched real-time-kinematic (RTK)-compatible motion trackers. The development is designed to bring centimeter-accurate positioning within reach of a new generation of affordable commercial devices.
The RTK extension to conventional satellite positioning signals reduces the maximum positioning error from around ±1 meter in standard commercial GNSS receivers to typically ±2 centimeters. Companies developing innovative new products in non-military markets such as smart farming, autonomous vehicles and coastal maritime equipment have been keen to take advantage of high-precision RTK capability to enable new applications and more automated functions, according to an Xsens press release.
The MTi-680G is a new product in the Xsens MTi 600-series. The MTi-680G, an integrated GNSS/inertial navigation system (INS) module, features an integrated RTK GNSS receiver, as well as providing synchronized 3D attitude (tilt, inclination) and heading outputs.
The new MTi-680G also features upgraded firmware that substantially accelerates the module’s internal signal processing compared to non-RTK modules. Synchronizing the global position coordinates with the module’s attitude, heading and velocity outputs, the MTi-680G can provide a comprehensive positioning and navigation output for any carrier device, including of devices such as drones that move at high speed, at a maximum output data rate of 400 Hz.
The RTK-enabled module also offers these features:
Precise factory calibration of every production unit
High immunity to magnetic interference
Adaptive firmware operation to optimize performance in various types of scenario
Easy-to-use, free MT Software Suite developer tools to accelerate integration into end-product designs
Out-of-the-box operation with Xsens’ MTi development kits
“Centimeter-accurate positioning at an affordable price for commercial applications — this is the promise of the new RTK-compatible MTi-680G product,” said Boele de Bie, Xsens CEO. “From seed-sowing agricultural robots to autonomous cargo ships, a whole new generation of applications is now possible thanks to the centimeter-level accuracy of the MTi-680G’s position measurements.”
Klau Geomatics has launched MakeItAccurate, a global GNSS data correction and processing service.
MakeItAccurate takes data from any GNSS receiver on drone or survey equipment and makes it accurate. Users can now achieve centimeter (cm)-level accuracy without the need for base stations, real-time kinematic (RTK) links, data from Continuously Operating Reference Station (CORS) or other external inputs.
MakeItAccurate requires only the raw GNSS data from a drone to produce a highly precise trajectory and turn the traditional autonomous 3-5m GPS accuracy to 3-5 cm anywhere in the world.
In many parts of the United States, Europe, Japan, Australia and New Zealand, absolute accuracy of 2-3 cm XYZ will be achieved. In these areas, the KlauPPK processing engine applies sophisticated hybrid PPK/PPP algorithms, merging global PPP clock and orbit corrections with many distant CORS stations to achieve this high absolute accuracy.
The service enables enterprise drone operations to achieve high accuracy across their entire global operations with one repeatable workflow.
Sectors such as insurance, telecommunications and utilities can scale their operations without additional survey expertise and site-specific data constraints. The same process works for multiple operators on thousands of sites enabling consistent, high accuracy every time, the company said.
MakeItAccurate supports data from all GNSS manufacturers. Native support for DJI M 210v2 RTK or Phantom 4 RTK drones returns precise camera positions with centimeter-level accuracy. Other drones using external PPK GNSS products also can achieve highly accurate kinematic trajectories and camera coordinates.
A MakeItAccurate application programming interface (API) is available to push raw GNSS data to the processing engine and return highly accurate coordinates, with full reporting on the accuracy achieved for the entire trajectory or each camera event. GNSS hardware manufacturers can offer a custom service to add value to their products. Software developers offering artificial intelligence technology, photogrammetry processing or other outcomes that benefit from high accuracy can use the MakeItAccurate API.
Gladiator Technologies’ low-noise inertial sensor and systems technology coupled with Velox high-speed processing are now integrated with a 72-channel GNSS receiver to provide compact GNSS/inertial navigation systems (INS) for accurate position, velocity and attitude.
The feature set was carefully selected to suit several positioning, navigation and timing (PNT) applications including flight control, navigation and stabilization for imaging, platforms and antennas.
The high-performance LandMark 60 INS/GPS and compact LandMark 005 INS/GPS both feature advanced sensor-fusion technology, combining GNSS position data with Gladiator Technologies’ low-noise, high output inertial sensors as well as barometric pressure and magnetometers.
Both products feature Gladiator Technologies’ proprietary Velox processing technology and extended Kalman filter (EKF), enabling precision position information during short-term GPS outages.
Velox Technology combined with the new EKF enable the LandMark INS/GPS products to have accuracy of less than 2 nautical miles per hour during short-term GPS outages.
The LandMark 60 INS/GPS is the top performing unit with +/- 0.3° heading accuracy and pitch/roll angle measurements of 0.1°. It is also available with an option for a real-time kinematic (RTK) GPS receiver.
The small and robust LandMark 005 INS/GPS is less than 35 square centimeters and is suitable for space-constrained applications that require a high standard of INS/GPS performance.
“Our low-noise sensor inputs to the EKF are enhanced by an adaptive estimation algorithm,” said Lee Dunbar, chief software architect. “This, along with extended precision for the nonlinear solution integrator, maximizes the accuracy of position, velocity and attitude. Customer configurable EKF parameters are present to allow optimization for their applications.”
“Leveraging our inertial capability into a complete INS/GPS package was a natural progression for our product line,” said Eric Yates, Gladiator Technologies’ new business development manager. “With the LandMark 005 INS/GPS and LandMark 60 INS/GPS we’re offering an exceptional MEMS-based INS/GPS that fits in the palm of your hand.”
Why do we keep hearing about unmanned aircraft all the time, almost everywhere? Fortunately, the buzz has gone beyond next-door neighbors flying dangerously close to your roof or hovering annoyingly around a living room window, and incidents of UAV incursions shutting down airports seem to be getting fewer — improved enforcement and higher penalties may be slowing down these incidents.
Now, UAV users are taking on productive, innovative tasks that couldn’t previously be done, or finishing projects surprisingly quickly and more affordably than ever before, with drones built or adapted for new applications. And equipment manufacturers are creating new sensors customized for use on drones.
Commercial, integrated GNSS/inertial sensors are available that have extremely high performance — previously only available with expensive mil-spec electronics — but in lightweight, small packages, supported by real-time kinematic (RTK), precise point positioning (PPP) corrections or post-processed kinematic (PPK). UAVs carry still, video and multi-spectral cameras generating automatically geocoded outputs, ready for post processing into multi-layered formats — virtually everything a customer could ever dream of having. And lidar sensors enable drones to build accurate models of everything they overfly.
Drones originated largely with military forces. Originally used for forward intelligence gathering, UAV tasks have multiplied and substantially expanded in scope.
Commercial industries were quick to realize the benefits. Before drones, the cost of many tasks done manually would be prohibitive and too time-intensive. Fast, affordable data collection now allows us to quickly tackle and solve many problems.
UAVs can pre-survey large, previously inaccessible tracts of difficult terrain, collect detailed visual representations of entire cities, monitor and support crop growth, or even survey underwater terrain using lidar. UAVs provide crop-growing support by flying autonomous patterns and spraying fields with pesticides or fertilizer. They also are being called into service to spray villages with disinfectant to control the spread of coronavirus, and to survey England’s beaches to monitor coastal erosion.
Topcon Positioning Group is offering a new Thermal Mapper for asphalt paving. It is designed to monitor temperature segregation to prevent future problems and measure performance, as well as provide accurate compliance reporting — all with real-time kinematic (RTK) positioning accuracy.
The mapper records temperature readings behind an asphalt paver as the paving is in progress and provides a visualization to operators in real time of whether the mix falls within a predefined temperature range, and if any segregation is limited within specifications.
“If too much segregation occurs, roads will soon develop major problems. The mapper quickly tells operators if the mix is stable or if moderate or severe temperature variation is occurring. If the readings are unacceptable, operators can adjust for more efficient and accurate project outcomes,” said Murray Lodge, senior VP of construction. “The system’s sensors also bring to the market the first thermal mapping system with RTK GPS positioning for more accurate results than conventional methods.”
The system also creates data reporting files to download for applications such as U.S. Department of Energy compliance through an interactive Pavelink module, the Topcon cloud-based logistics application for asphalt paving.
“We are excited about where Topcon is taking the paving industry with the different solutions we are bringing to market. From SmoothRide, where we scan the existing road to determine the optimal design for variable depth milling and paving to the newly released Pavelink system, we are focused on improving paving.
“Pavelink allows contractors to monitor the entire paving workflow from the batch plant, mixing plant, trucks, to the paver, to the rollers. By connecting the entire process, it allows the contractor to have full control over their projects in real time and make adjustments along the way, instead of after the fact as is so often done with conventional methods. Now, bringing in the heat sensor system into that workflow, we are giving contractors more resources to meet the specifications demanded today.
“It is part of our commitment to revolutionize the planning and management of the asphalt paving process with real-time visibility throughout the project lifecycle,” Lodge said.
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.
Rooftop view of the central parts of Aarhus with the harbor area and the sea in the background. (Photo: DTU Space)
A testbed in an active urban center can show real-world effects on GNSS as an aid for developing autonomous systems for green mobility, smart-city applications or transportation, to name a few.
Sited in Denmark, the 600-square-kilometer Testbed in Aarhus for Precision Positioning and Autonomous Systems (TAPAS) covers both a densely populated city center and suburbs, a large industrial harbor and parts of Aarhus Bay. Aarhus is the second largest city in Denmark with a population of 350,000 people.
The GNSS antenna at TAPAS station TA01. (Photo: DTU Space)
Based on RTK methodology, TAPAS is a sound ground-based testbed to support, test and validate technological developments with a need for fast, efficient, flexible and reliable precision positioning. It is designed as a geodetic innovation platform, with both physical and virtual networks providing positioning to the centimeter (cm) level.
Autonomous systems within transportation, agriculture and environmental monitoring constitute a large growth area for businesses and governments. Automated vehicles, drones and vessels are linked closely to geodetic infrastructure and communications networks such as 5G. TAPAS provides developers in these fields with opportunities to observe GNSS in urban canyons and under canopies, as well as challenges for coastal marine applications. The testbed is available for third-party research projects, and testing of ideas, initiatives and concrete prototypes.
TAPAS is fully funded and owned by the Danish Agency for Data Supply and Efficiency (SDFE), the Danish agency for geodesy and geographical data. TAPAS is developed by the National Space Institute at the Technical University of Denmark (DTU Space), and is supported by the city of Aarhus. The TAPAS testbed was established partly because of Denmark’s National Space Strategy, which points to the new technological development within positioning, as well as possibilities for use of Galileo, the European GNSS, to the benefit of as many citizens as possible.
In this article, we review the TAPAS testbed, including design and installation of the GNSS reference stations and the data-processing center, as well as initial performance testing carried out by DTU Space.
Network of GNSS Reference Stations
The network of TAPAS stations in and around the city of Aarhus in Denmark. (Map: DTU Space)
The basic component of TAPAS is high-accuracy carrier-phase-based GNSS positioning using the network RTK methodology, which can provide real-time position accuracies for the end user down to the cm level.Essentially, TAPAS is based on a network of 11 GNSS reference stations as well as data communication infrastructure, a central processing facility with a data server, processing software and data storage.
TAPAS was designed to provide real-time position uncertainties for objects in motion within 1 cm in three dimensions (1 cubic cm), for end users with modern GNSS equipment. A dense network of GNSS reference stations was originally designed with stations 5 km apart in the city center and up to 10 km apart in the suburbs.
Because suitable locations had to be found, in the final network distances range from 4.1 km to 22.3 km, with the longest distances across the water to station TA04 (see the network plot in the graphic above).
Stations TA01, TA03, TA05, TA06 and TA08 are in the city center. Stations TA02 and TA04 are across Aarhus Bay, ensuring coverage for marine applications and contributing to more robust positioning near the sea and in the harbor area around station TA01.
TAPAS Stations
The TAPAS GNSS reference stations are equipped with the newest generation of GNSS receivers and antennas capable of tracking all available signals from the GPS, GLONASS, Galileo and BeiDou systems. The stations also have an antenna splitter, power supply, fuse box, programmable logic controller (PLC) for monitoring and control, trustgate, modem and uninterruptible power supply with battery pack (Figure 1). All units were integrated in the cabinets and tested in the lab before installation The stations are modular and flexible for future iterations and updates.
The receivers can be accessed remotely via a VPN line to a web interface for monitoring, changing settings or firmware updates. All TAPAS stations transmit data to servers at DTU Space where the data is used for estimation of RTK corrections. Also, data is transmitted to servers at the SDFE for storage and backup (Figure 1).
Figure 1. Design schematics of the TAPAS stations. (Image: DTU Space)
After installation in the fall of 2018, GNSS data quality was verified for each station by estimating preliminary positions and analyzing data quality. Also, signal strength as given by the carrier to noise ratio (C/N0) of the received signals was analyzed and plotted with 24 hours of data from each of the stations (Figure 2).
Network Real-Time Kinematic (RTK)
Data from the TAPAS stations streams in real time to the Central Processing Facility (CPF) operated at a dedicated server at DTU Space in Lyngby, North of Copenhagen. The GNSS observations are processed using the GNSMART 2 software from Geo++, where corrections for network RTK positioning are estimated. The corrections are estimates for errors affecting the GNSS positioning, such as inaccuracies in satellite positions and clock drift parameters as well as ionospheric and tropospheric effects. The dense network of reference stations in TAPAS will assure that corrections for the atmospheric effects will be of very high quality.
For estimation of the RTK corrections, standard software settings are used. All corrections are estimated by a state space representation (SSR) technique, where error sources are modeled individually. This means TAPAS can deliver both RTK corrections and corrections for precise point positioning (PPP).
TAPAS corrections are generated in the RTCM format and output using the NTRIP protocol. Registered users can access the corrections through the internet via an NTRIP caster. On the user side, the TAPAS corrections are applied in the positioning process of a GNSS receiver. To make full use of the TAPAS data, user equipment should be capable of tracking carrier-phase-based GNSS data and applying the TAPAS correction data supplied in the RTCM version 3.x format.
An example of a use of TAPAS is provided in the photo in Figure 9 below where the authors of this article tested the position accuracy of TAPAS for a typical land surveying task, using a Septentrio Altus APS3G receiver with an allegro2 controller unit for RTK positioning. The user’s GNSS equipment can, however, be many other different types and makes of GNSS antennas and receivers, and the equipment can be installed on many different platforms for instance in vehicles, on drones, in robots etc.
Geodetic Basis
When determining positions with uncertainties at the 1-cm level, it is important to be aware of the geodetic reference frame used for the positioning. In this case, coordinates for the TAPAS stations have been estimated by DTU Space, using Bernese GNSS software, in the national Danish reference frame which is a realization of the European Terrestrial Reference System (ETRS).
When applying corrections from the TAPAS caster in the positioning calculations at the user side, positions will be obtained within the same reference frame (coordinate system). In this case, where the national geodetic reference frame is used, this means that the user will obtain positions compliant with maps, charts and other types of geodata geo-referenced in the same coordinate system.
For 3D positioning, the Danish geoid model must be applied on the user side to obtain heights relative to mean sea level in the national Danish Vertical Reference (DVR90).
It is possible to configure the setup of the central processing facility using another reference frame for TAPAS given that precise coordinates for the TAPAS stations can be provided in the given reference frame. Future work with TAPAS can involve the use of dynamic geodetic reference frames and transmission of coordinate transformation parameters to the users.
Performance Testing
After the stations were installed, DTU Space conducted performance testing, including testing data communication between the TAPAS stations and the TAPAS server, analyses of data completeness from the TAPAS stations, and field tests carried out after the network RTK processing had become sufficiently stable.
Performance test in static mode. In February 2019, a static mode test took place in a park-like area within the three innermost stations. Two different high-accuracy survey-grade RTK-receivers were used for the field test. RTK positions were estimated at 1 Hz for 30 minutes. For each minute, an average position was calculated based on the 60 observations, and for each of the minute-bins the standard deviation with respect to the reference position was computed.
Test location indicated with purple circle in the network plot. (Image: DTU Space)Altus APS3G unit mounted at the test location. (Photo: DTU Space)
The results are shown in the plots below, where standard deviations are provided for each epoch (i.e., for each bin of 60 seconds).
Standard deviation in meter for each 60 second with GNSS receiver Altus NR3 (left) and Altus APS3G (right). Results provided in meter. (Images: DTU Space)
In the plots, results are provided for the vertical (red), the horizontal (blue) and the 3D position (green). Results of using the two different receivers are comparable, and focusing on the 3D solutions the largest standard deviation is 1.6 cm which is for the fourth epoch with receiver APS3G. Most of the 3D results shown in the plots are better than 1 cm.
The same test was carried out using a dual-frequency non-survey-grade receiver developed for machine control and autonomous vehicle applications. This receiver was connected to the same antenna mounted on a tripod. Results of using this receiver in static mode are shown in the plot below. In this case, the 3D results are all better than 3.1 cm, and many of the 3D results are better than 1 cm in this open test area.
Standard deviation for each 60 second with GNSS receiver u-blox F9P dual frequency (DF). Results provided in meter. (Image: DTU Space)
Performance test in kinematic mode. In the same area used for the static test, a kinematic test was carried out with the same three receivers.
The test was performed using a camera dolly and by placing approximately 10 m of rail on the ground. The camera dolly was pulled back and forth along the rail, a setup that provided a stable trajectory for testing positioning performance while the GNSS antennas were moved slowly and smoothly. A rigid bench, where the GNSS antennas could be mounted, was constructed and installed on the dolly. The three GNSS receivers with antennas were mounted on the bench, and the dolly was pulled back and forth along the tracks 10 times.
Kinematic Test: Camera dolly with GNSS equipment pulled along tracks. (Photo: DTU Space)
For each 1-meter section of track, the standard deviation of the differences with respect to the reference trajectory of the 10 repetitions was calculated. Results for the two survey-grade receivers are shown in the plots in Figure 3. All of the 3D standard deviations are better than 1 cm for both survey-grade receivers.
Figure 3. Kinematic test results are provided for the vertical (red), horizontal (blue) and 3D (green) positions. (Image: DTU Space)
The non-survey-grade dual-frequency receiver also was mounted on the test bench, and the results of using this receiver are shown in the plot below. With this receiver, the 3D results are below 2.1 cm for all sections of the trajectory, except for the first meter, a deviation that may have been caused by issues with initialization of the test.
Binned standard deviation of 10 repetitions with GNSS receiver u-blox F9P dual frequency (DF). Results provided in meter. (Image: DTU Space)
These tests show that it is possible when using TAPAS to obtain position solutions at the cm-level in open areas in both static and kinematic mode.
Performance test in dynamic mode. In November 2019, DTU Space carried out a performance test of TAPAS in dynamic mode, using a car with roof-mounted GNSS equipment. The car was driven within the TAPAS coverage area, passing through urban canyons, open streets and the harbor area. During the test, the car drove in normal Aarhus traffic, at speeds varying from zero at traffic lights up to 60 km/h on the wider roads leading into the city center.
Four different receivers were strapped in the car and connected to either a small patch antenna or a survey-grade antenna mounted on the roof. A survey-grade receiver was mounted on the roof.
Three different GNSS antennas mounted on the roof of the car used for dynamic testing. (Photo: DTU Space)
Data from the receiver was converted to KML files, which can be used with Google Earth to illustrate the quality of the positioning obtained during the drives through the city. The plot in Figure 4 shows the quality of the position solution. The best quality is obtained when the ambiguities are fixed, such as an RTK fixed solution at the cm level (green). The second-best quality is with ambiguities estimated to float values, such as an RTK float solution at the dm level (purple). Orange shows differential position solutions at the meter level when corrections for the carrier-phase data have not been obtained. Finally, a few positions were stand-alone GNSS solutions when no aiding from TAPAS was applied in the roving GNSS receiver (blue).
Figure 4. Quality of RTK positions obtained during one drive through the City of Aarhus. (Map data: Google, TerraMetrics)Photo:
The plot clearly shows, as expected, that the quality of the positions determined by the survey-grade receiver in the car is good most of the time. But it suffers in areas with narrow streets aligned with buildings or trees.
These results do not tell the actual uncertainty of the position solutions. But GNSS carrier-phase data collected with one of the receivers in the car during the drive will be post processed to serve as a reference trajectory. Upcoming analyses of the data will then reveal the uncertainty of the positions determined in real time as compared to the post-processed reference trajectory.
Test Conclusion. After the field tests, we conclude that the TAPAS testbed is able to provide correction data that makes it possible to perform GNSS-based positioning in real time in both static and dynamic mode with position uncertainties at the cm-level. Further, as we analyze the test data thoroughly, TAPAS will be able to set a tone for new research. For instance, the plot in Figure 4 provides a foundation for testing assistance procedures to gain better coverage in the most densely built areas. In this way, TAPAS will aid research into feasible infrastructure for the technologies of tomorrow, such as autonomous driving.
Outlook and Future Work
Because TAPAS is not commercial, it is possible, upon agreement with the SDFE, to make changes to the system to adapt to specific testing or development needs. Examples are removing data from some stations in the estimation of RTK correction data, installing an extra receiver in one or more stations using the antenna splitters, or making changes to the settings in data processing on the TAPAS server for shorter time intervals.
At DTU Space, plans for the testbed include further development of software for ionosphere and integrity monitoring. The station receivers can estimate total electron content (TEC) along the GNSS signal path in Earth’s atmosphere, as well as indices for ionospheric scintillation. DTU Space is researching using this output for an ionosphere monitoring service and to develop it into an integrity monitoring service for GNSS users.
Upcoming additions to the RTCM data format will support more advanced modeling of the effects of the ionosphere and troposphere, and this will allow for full benefit of the TAPAS SSR network corrections. Research on such models to be applied on the server side, as well as on the user side, will be carried out by DTU Space and tested with TAPAS as a contribution towards the integration, or hybridising, of PPP and RTK. This is also referred to as PPP-RTK positioning which is expected to be especially useful for mass market applications such as autonomous driving. When implemented in TAPAS, such solution may effectively increase the number of simultaneous users as well as use-cases for TAPAS.
TAPAS provides many opportunities for testing precision or high-accuracy applications, such as autonomous vehicles, vessels, drones and robots; location-based services requiring high accuracy on various digital platforms; and solutions for a more digitized and intelligent city environment through smart-city and green mobility initiatives.
TAPAS is prepared for the implementation of the coming 5G technologies, and station intercommunication capabilities enable testing of internet of things (IoT) technologies where precision positioning is part of the development. The testbed also provides an excellent environment for validation of new services such as the Galileo High Accuracy Service (HAS). Another area in which TAPAS can play an important role is verification and validation of future 5G-based positioning services.
The TAPAS testbed was developed with close cooperation between DTU Space and SDFE. SDFE contributors include Kristian Keller, Casper Jepsen, Henrik Olsen, Martin Skjold Grøntved, Brigitte Rosenkranz, Maria Rask Mylius and Søren Fauerholm Christensen. DTU Space contributers include Ole Bjerregaard Hansen, Finn Bo Madsen, Lars Stenseng, Daniel Haugård Olesen, Stefan Emil Steffensen, Thor Heine Snedker, Per Knudsen and Niels Andersen.
Manufacturers
The GNSS receivers at the TAPAS stations are Septentrio PolaRx5S, and the antennas are Leica AR20. For field testing, a Septentrio Altus NR3 receiver, a Septentrio Altus APS3G receiver and a u-blox ZED F9P dual-frequency receiver were used. The TAPAS station cabinets were assembled and mounted by Nordtec-Optomatic A/S. The TAPAS testbed software solution is based on the GNSMART 2 software package from Geo++ GmbH. Data analyses and processing has been carried out using the Septentrio SBF Analyser and SBF Converter, the RTKlib and the Bernese GNSS software.
Anna B. O. Jensen is senior advisor and team lead of the GNSS group at DTU Space in Denmark. She is also a part-time professor at KTH Royal Institute of Technology in Sweden.
Per Lundahl Thomsen is a chief consultant at DTU Space. He has many years of experience with management of space technology projects and is project manager for the TAPAS testbed.
Søren Skaarup Larsen is a Ph.D. student at DTU Space. Along with his GNSS studies, he runs the RTK-part of the TAPAS testbed.
Septentrio and CORE partner up to develop a GPS/GNSS receiver which will make use of Japan’s Centimeter-Level Augmentation Service (CLAS). CLAS corrections are broadcast directly via QZSS constellation to enable high-accuracy positioning across Japan.
Septentrio, a designer and manufacturer of high-precision GNSS technology, and CORE, a Japanese system integrator with extensive experience in GNSS, are jointly developing a receiver that can use the Centimeter-Level Augmentation Service (CLAS) of Japan’s Quasi-Zenith Satellite System (QZSS).
Septentrio’s multi-frequency GPS/GNSS receiver AsteRx4 will be used as a platform for the development of CLAS functionality. Septentrio receivers already track the L6 signal and can use QZSS for increased positioning availability and reliability.
CORE’s know-how will be instrumental for the deployment of CLAS on Septentrio receivers. The two companies are planning to launch their CLAS-enabled receiver in January 2020.
Japan’s CLAS is a self-augmentation GNSS correction service. Without the need for a ground link, it allows real-time kinematic (RTK) centimeter-level positioning all over Japan with convergence times of less than a minute.
It does this by broadcasting GNSS corrections directly via QZSS satellites, also known as Michibiki. These corrections are generated from the dense network of reference stations operated by Japan’s Geospatial Authority.
The two companies have also entered into a distribution contract that allows CORE to sell Septentrio high-precision positioning technology, including CLAS-capable GNSS receivers, in the Japanese market.
The new CLAS-enabled receiver will also incorporate Septentrio’s Advanced Interference Mitigation (AIM+) technology. In busy urban environments electromagnetic waves can interfere with GPS and GNSS signals.
AIM+ offers protection against such interference resulting in faster set-up times and robust continuous operation.
“QZSS Centimeter Level Augmentation Service has been limited to evaluation phase up till now. Realizing CLAS on Septentrio’s multifunctional, high-quality, cost-competitive platform allows our customers to finally use QZSS in their applications,” emphasized Takahiro Yamamoto, Director of GNSS Solution Development Center at CORE Corporation. “Galileo High Accuracy Service (HAS) is expected to start in 2020, so the demand for high accuracy GNSS receivers is also expected to increase. By complementing CORE’s QZSS technology and Septentrio’s Galileo technology, we can provide competitive products to global customers.”
“CLAS is a first-of-its-kind service which will contribute to the proliferation of high accuracy GNSS applications in Japan. Europe is also taking similar initiatives with their Galileo High Accuracy Service (HAS),” commented Neil Vancans, Director of Global Sales at Septentrio. “We are excited to enter into an agreement with CORE to enable the support of CLAS on our receivers. CORE’s expertise allows us to get the best out of CLAS and to follow new developments in QZSS evolution. Moreover, CORE’s expertise in system integration will allow us to tackle new markets in Japan.”
By Kazuma Gunning, Juan Blanch and Todd Walter, Stanford University, and Lance de Groot and Laura Norman, Hexagon Positioning Intelligence
UAV and autonomous platforms can greatly benefit from an assured position solution with high integrity error bounds. The expected high degree of connectivity in these vehicles will allow users to receive real-time precise clock and ephemeris corrections, which enable the use of precise point positioning (PPP) techniques.
Until now, these techniques have mostly been used to provide high accuracy, rather than focusing on high-integrity applications. The authors apply the methodology and algorithms used in aviation to determine position error bounds with high integrity (or protection levels) for a PPP position solution.
PPP techniques can provide centimeter accuracy without local reference stations in kinematic applications. These techniques have so far mostly been used to provide high accuracy, and it is only recently that they have been proposed to provide integrity, that is, position error bounds with a very low probability of exceeding them.
There has been preliminary work on the application of integrity to PPP, but it remains a challenge to translate the benefits of PPP to accuracy while maintaining high integrity. Most of the integrity work in PPP and real-time kinematic (RTK) has dealt more with the ambiguity resolution process under nominal error conditions and less on the integrity of the position solution under fault conditions.
The authors overview their PPP filter implementation, and describe the threat model as well as two classes of integrity algorithms: solution separation and sum of squared residuals based (also called residual-based [RB], a misnomer, as all autonomous integrity monitors are based on the residuals.)
They present data sets used to evaluate the algorithms, compare the protection levels (PLs) obtained with different algorithms, and present the results obtained with the most promising PL formulation in four different data sets: static, dynamic in open-sky conditions, dynamic in midtown suburban conditions, and in flight.
Concluding, they state: “We have formulated RAIM protection-level formulas using either solution separation or the sum of residual squares. Both formulations consist of straightforward adaptations of snapshot RAIM to a Kalman filter solution.
“For solution separation, we have shown an implementation where the computational cost of running a bank of filters is far from being proportional to the cost of one filter. Instead, we could run 50 additional filters for the cost of one.
“For residual based RAIM we have developed a set of formulas to update the sum of square residuals from one time step to the next one. Because this test statistic is exactly the same as the one used in snapshot RAIM (when we consider the problem as a batch least squares), we could use the formula that ties the slope of a fault mode to the standard deviation of the solution separation. The slope can therefore also be updated recursively.”
Finally, “we have refined the PPP filter, added one scenario (suburban driving conditions), and examined the effect of considering multiple faults in the formulation of the test statistics and the protection levels. The results are very promising: protection levels below 2 m appear to be achievable, and the computation load is lower than expected.”
