UAV Navigation’s flight control solutions for remotely piloted air systems/unmanned aerial vehicles (RPAS/UAVs) are compatible with the Trimble UAS1 high-precision GNSS receiver. The core benefits of Trimble’s GNSS solution include centimeter-level precision and easy integration.
Image: UAV Navigation and Trimble
The light, small Trimble UAS1 receiver is less vulnerable to vibrations or temperature fluctuations, making it suitable for UAVs and RPAS. In addition, the receiver can provide real-time kinematic (RTK) positioning using a base station, enabling users to achieve higher precision for their projects.
Most UAV missions demand precision in its subsystems. The Trimble UAS1 receiver meets these requirements and includes a 336-channel high-precision GNSS engine. It tracks L1/L2 frequencies from the GPS, GLONASS, Galileo and BeiDou constellations.
The Trimble UAS1 supports OmniSTAR and Trimble CenterPoint RTX GNSS corrections, which enable precise and robust positioning without the use of a base station via a subscription service. The receiver also offers an industry-standard camera hot-shoe interface and a wide DC voltage range to work in a broad range of UAVs.
While Trimble is highly specialized in providing advanced GNSS solutions, UAV Navigation’s focus is on innovations in flight control systems. With this combined technology, current UAV/RPAS systems can now operate in more demanding environments and deliver higher precision through better navigation, UAV Navigation stated in a press release.
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.
Trimble has introduced the the R12 GNSS receiver, a high-performance GNSS surveying solution. Powered by a new real-time kinematic (RTK) and Trimble RTX positioning engine, it features Trimble ProPoint GNSS technology that empowers land surveyors to quickly measure more points in more places than previously.
Surveyors who work in challenging GNSS environments can use the Trimble R12 receiver to help reduce both the time in the field and the need for conventional techniques such as using a total station.
The new Trimble ProPoint GNSS technology allows for flexible signal management, which helps mitigate the effects of signal degradation and provides a GNSS constellation-agnostic operation.
In head-to-head testing with the Trimble R10-2 in challenging GNSS environments such as near and among trees and built environments, the Trimble R12 receiver performed more than 30 percent better across a variety of factors, including time to achieve survey precision levels, position accuracy and measurement reliability.
“As a leader in the field of GNSS technology and innovation, Trimble dedicated many years of intensive research into developing the Trimble R12,” said Ronald Bisio, senior vice president of Trimble Geospatial. “This has culminated in a first-class solution, which enables our users to extend the reach of their systems to places where other RTK GNSS systems experience degraded performance.”
CHC Navigation has launched its LT700H RTK Android tablet, designed to increase efficiency and productivity of the mobile field workforce in applications requiring centimeter-to-decimeter positioning accuracy.
Photo: CHC Navigation
Portable, rugged and versatile, the LT700H enables precision GIS data collection, forensic mapping, construction site layout, environmental surveys, landscaping and earthmoving jobs.
Powered by 184-channel high-performance GPS, GLONASS, Galileo and BeiDou module and a superior tracking GNSS helical antenna, the LT700H provides position availability in demanding environments. Its integrated 4G modem ensures seamless communication from field-to-office and robust connectivity to GNSS real-time kinematic (RTK) networks corrections.
“With the LT700H RTK Tablet, we are offering a professional and accurate GNSS solution to any mobile applications requiring high-portability,” said George Zhao, CEO of CHC Navigation. “The LT700H enables further use of GNSS technology, from single operator to companies with large field crew.”
Combined with CHCNAV Landstar 7 field data-collection software, the LT700H has a vibrant 8-inch IPS sunlight-viewable screen that perfectly displays GIS data tables, vector and raster maps or high-resolution pictures.
The LT700H Google GMS certification guarantees compatibility with any common GIS and mapping Android applications.
The UAS1 GNSS receiver module has been designed for UAV/UAS applications requiring centimeter accuracy in a small package. (Photo: Trimble)
Trimble has introduced a compact, high-precision GNSS board specifically designed for unmanned aerial systems (UAS).
The Trimble UAS1 has a simple connectivity and configuration to allow UAS system integrators to easily add satellite-based positioning — with the ability to upgrade its capabilities — using rugged connectors and Trimble’s easy-to-use software interface.
The new UAS1 incorporates the latest Trimble Maxwell technology with advances in high-precision GNSS positioning. Its GNSS engine with 336 channels is capable of tracking L1/L2 frequencies from the GPS, GLONASS, Galileo and BeiDou constellations for robust centimeter-level, real-time kinematic (RTK) positioning.
The compact board includes a broad range of receiver capabilities — from high-accuracy GPS-only to full GNSS features for positioning. Firmware options and features are password upgradeable, allowing functionality to be added as requirements change.
The receiver also supports fault detection and exclusion (FDE) and receiver autonomous integrity monitoring (RAIM). System integrators also have the ability to detect interference with the RF Spectrum Monitoring and Analysis tool embedded in the receiver.
“UAS manufacturers demand high performance, reliability and high-quality customized support for their positioning solutions,” said Thomas Utzmeier, general manager of Trimble’s Integrated Technologies Division. “The new UAS1 board delivers the latest GNSS technology in an easy-to-integrate form factor for UAV/UAS applications.”
Designed for easy integration and rugged dependability, the Trimble UAS1 has a Remote Network Driver Interface Specification (RNDIS) that enables manufacturers to access the web UI with the USB connector. As with similar Trimble embedded boards and modules, easy-to-use software commands can simplify integration and reduce development times.
Features also include integrated Trimble RTX technology, an industry-standard camera hot-shoe interface to geo-position photographs, and LED indicators for status checks. The Trimble UAS1 can also output to RINEX, a common postprocessing format.
The Trimble UAS1 supports Trimble CenterPoint RTX GNSS corrections, which enable precise and robust positioning without the use of a base station via a subscription service. CenterPoint RTX allows users to achieve better than 2-centimeter horizontal and 5-centimeter vertical accuracy.
Trimble’s UAS1 is suitable for UAS applications requiring centimeter accuracy in a small package. Manufactured and tested to Trimble’s highest quality standards, the compact design allows for easy setup, configuration and installation in a customers’
system.
Using a full metal shield (the form factor is 71 x 46 x 13 millimeters), the board’s design enables high-precision GNSS signal protection from electromagnetic interference (EMI) on the host UAS platform. In addition, the receiver is FCC- and CE-certified, which speeds compliance for the customer’s overall system and can reduce time to market.
NavCom Technology Inc., a wholly owned subsidiary of Deere & Company, has released the Onyx multi-frequency GNSS OEM board.
Offering integrated StarFire/RTK GNSS capabilities, Onyx features 255-channel tracking, including multi-constellation support for GPS, GLONASS, Beidou and Galileo. It also provides high-performance in GNSS receiver sensitivity and signal tracking as well as patented multipath mitigation, interference rejection and anti-jamming capabilities.
Photo: NavCom
The new Onyx GNSS OEM board is a fully upgradeable GNSS receiver, allowing the receiver to be upgraded from free differential GPS signal sources such as WAAS to increased accuracy services with integrated features with StarFire, through software optioning alone.
The software-enabled features are sold in convenient software bundles, but can also be purchased individually, to suit changing application needs. Integrated StarFire is now simply activated via an over-the-air licensing system that sends a StarFire license via satellite directly to the StarFire-capable receiver from NavCom’s StarFire operations center.
StarFire, NavCom’s global satellite-based augmentation system (SBAS), provides real-time global 5-centimeter accuracy without a base station.
“The release of Onyx advances NavCom’s ability to grow products and services meeting the customer driven demands of uptime, accuracy, and feature rich capabilities,” said Steve Ault, NavCom’s GNSS product marketing manager. “NavCom continues to innovate the StarFire technology through the advanced capabilities inherent to Onyx which will be fully realized over the life of this new product.”
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.”
CHC Navigation has released and is immediately shipping its new i90 IMU-RTK GNSS Series receiver. The i90 IMU-RTK GNSS Series is designed to dramatically increase GNSS real-time kinematic (RTK) availability and reliability.
The i90 is powered by the company’s latest inertial measurement unit (IMU) and RTK technology to provide robust and accurate GNSS positioning in any circumstances.
Unlike standard micro-electro-mechanical (MEMS)-based GNSS receivers, the i90 GNSS IMU-RTK combines a high-end calibration and interference-free IMU sensor with a state-of-the-art GNSS RTK engine and advanced GNSS tracking capabilities.
The i90 is designed to increase productivity and reliability of survey projects. No complicated calibration process, rotation, leveling or accessories are necessary with the i90 GNSS Series. Just a few meters’ walk will initialize the i90 internal IMU sensor and enable RTK survey in difficult field environments. The i90 GNSS automatic pole-tilt compensation boosts survey and stakeout speed by up to 20%.
“Our new i90 IMU-RTK GNSS Series is pushing the boundaries of conventional GNSS survey by extending RTK positioning availability and reliability,” said George Zhao, CEO of CHC Navigation. “CHCNAV is the GNSS technology enabler, making high-end GNSS solutions available for every surveyor.”
The Allystar INS Platform — the company’s latest technology — is a dual-antenna, multi-frequency, multi-GNSS inertial navigation system (INS) that delivers accurate and reliable position, velocity and orientation, the company said.
It is designed for a wide range of autonomous vehicle applications under the most demanding conditions.
The Allystar INS Platform combines high-grade, six-axis, temperature-calibrated accelerometers and gyroscopes with a multi-frequency, multi-GNSS engine, the HD9300 series. HD9300 is a dual-antenna chip-grade real-time kinematic (RTK) GNSS receiver for accurate positioning and heading.
GNSS-aided inertial navigation systems are widely used in autonomous vehicles. However, high-accuracy multi-frequency multi-GNSS receivers are usually too expensive for mass-market applications. The Allystar HD9300 series is a mass-market multi-band chip-grade receiver that concurrently support all civil bands in all GNSS constellations (GPS/QZS L1&L2&L5&L6, BDS B1&B2&B3, GAL E1&E5, GLO L1OF/L2OF) with an integrated RTK engine to achieve centimeter-level accuracy.
The Allystar INS platform contains an on-board sensor-fusion filter, navigation and calibration algorithms for different dynamic motions of land vehicles. Key features include:
multi-band multi-GNSS chip-grade receiver
dual antennas
integrated RTK engine (up to 2 centimeters)
100-hz update rate
OBD data adapter.
Allystar OBD Data Adaptor V1. (Photo: Allystar)
The Allystar OBD Data Adapter (v1.0) enables users to read and monitor various sensors built into cars, obtaining the real-time vehicle speed and gear signals from the OBD interface, and then output AT commands by serial port or SPI. When connected to the Allystar RTK INS platform, the adapter allows for outstanding navigation accuracy, especially in urban areas, helping to increase accuracy and reduce position drift.
An evaluation kit — including platform board, antenna and OBD adaptor — will be available in August.
SoftBank plans to introduce a centimeter-accurate, real-time satnav-based positioning service, specifically using Japan’s Quasi-Zenith Satellite System (QZSS), to guide autonomous vehicles across a range of industries in Japan. The company said it will install more than 3,300 control points at base stations across Japan to deliver centimeter-level accuracy over its mobile network coverage area to provide real-time kinematic (RTK) positioning.
Testing begins in July with a scheduled launch of commercial service by the end of November. Test partners include Yanmar Agribusiness Co., Ltd., a provider of autonomous assisted driving for agricultural machinery, Kajima Corporation, which performs construction site management with automatically controlled drones for aerial photography and monitoring, and SB Drive Corp., a provider of autonomous and assisted driving technology for buses.
SoftBank is developing proprietary low-cost GNSS receivers so that “new services and market expansion can be realized.” A Positioning Core System provided by ALES Corp. will generate correctional data based on signals received and transmitted by SoftBank’s own control points over SoftBank’s mobile communications network to agricultural and construction machinery, self-driving cars, drones and other equipment carrying GNSS receivers. The company expects that centimeter-level positioning can thus be done in real time.
In addition to control points at its own base stations, SoftBank will use the Geospatial Information Authority of Japan’s approximately 1,300 GPS-based control stations.
SoftBank is also developing services to enablec loud-based RTK positioning for devices without GNSS receivers. Cloud-based RTK will provide centimeter-level, location-based services for equipment that needs to be miniature and energy-efficient, such as infrastructure surveillance sensors and wearable devices.
SoftBank Group Corp. is a Japanese multinational conglomerate holding company headquartered in Tokyo. It owns operations in broadband, fixed-line telecommunications, e-commerce, internet, technology services, finance, semiconductor design and more. It is the 36th largest public company in the world, and the 2nd largest in Japan.
ALES is a joint venture established by SoftBank and Enabler in July 2018. Enabler employs GNSS and related technologies to produce such products/services as a synchronization solution for mobile base stations for subway stations and a patented indoor positioning/time synchronization infrastructure platform in Japan.
BRING YOUR OWN DEVICE (BYOD) is not just an industry buzzword. It can change the way professional surveyors work every day. The idea of using a smartphone or tablet instead of a dedicated device is appealing. But is it good enough?
Surveyors and mappers are challenged with the arduous task of data collection that meets accuracy and precision standards and provides adequate attribute information for the project. Before the invention of the electronic data collector, handwritten notes in field books were the norm. Every note keeper’s style varied in content, neatness and thoroughness. Calculations for determining survey data values were completed longhand on paper and were very time consuming.
Like its personal computer counterpart, the electronic data collector was introduced in the late 1970s with minimal adoption by the average surveyor because of cost and complexity. Storage methods for the era included magnetic modules and tape; both forms of media were expensive and fragile with little storage for the cost.
Data collection was limited to numeric values only, with horizontal and vertical angles, slope distance, point number and point code being the extent of the information. Couple this process with the limited availability of printers and plotters capable of depicting the data for the surveyor’s use, and one can see why few practitioners invested in these systems.
iOS aerial viewer. (Screenshot: Tim Burch)
The 1980s and 1990s brought significant changes to surveying with the advancing technology of electronic computing and measuring. The introduction of robotic total stations, various methods of GNSS, and even leveling took advantage of significant computer power and measuring processes, and the data collector stayed in lockstep with the advancing instrumentation. Almost every equipment manufacturer developed their own proprietary data collector and software system because of the unique design and programming of their systems.
In the 2000s and later, third-party manufacturers began producing data collectors with advanced computing power and the ability to connect to varying brands of equipment. Most of the programming for these collectors are still proprietary in nature to this day.
Also during the 2000s, a new wave in mobile communications was taking place. Cellular phone and data signals were now being used to transmit an abundance of information between users.
The rapid development of handheld communication devices has led to the meteoric rise of two specific mobile operating systems: one by a radical startup that concentrated on dominating the search engine market, and the other by an avant garde computer company looking to expand its unique customer base.
By the end of the decade, the world had been introduced to the Android operating system by Google, and the iOS operating system by Apple. The combined market share for the two operating systems at press time was just under 98 percent of all mobile devices worldwide.
Trending Away from Proprietary Data Collectors
Android Point Info: Confirmation of collected data, including equipment and base station. (Screenshot: Tim Burch)
Because data collection by surveyors and mappers have traditionally been performed on proprietary systems designed and produced by equipment manufacturers for use with only their instruments, these collectors, while very powerful and robust, are costly for the equipment manufacturers to produce because of the limited market of surveyors and mappers.
Many suppliers, before the introduction of the iPhone and Android operating systems, attempted to adapt their data-collection platforms to wider recognized mobile operating systems (for example, Windows CE/Pocket PC/Mobile) on a bevy of mobile devices (HP/iPAQ, Sony Eriksson, HTC) with little success. Various versions of Windows are still being used today by GNSS equipment manufacturers’ proprietary data collectors, including Trimble, Hemisphere GNSS, Topcon and CHC Navigation.
However, the field of operating environments has become more crowded as technology continues to advance. The proliferation of Windows-based data collectors are now on the decline.
Survey Point: Status of survey data collection and GNSS engine signal reception. (Screenshot: Tim Burch)
Enter Android and iOS. Driving the decline of the previously popular Windows mobile platform is the rapid adoption of the iOS and Android operating systems. These two environments have also led to a substantial number of devices and applications for users.
Part of the reason for the speedy acceptance of the devices and operating systems has been the ease of programming. It is estimated that each operating system has more than two million applications in their respective online stores, with more being introduced daily.
Because of the proliferation of smartphones, nearly everyone is familiar with the look, feel and operation of touchscreen devices and their various applications. This familiarity is driving a new trend in data collection: the concept of “bring your own device” (otherwise known in IT security circles as “BYOD”). BYOD is being introduced by several surveying and mapping equipment manufacturers as an alternative to their proprietary data-collection devices.
Sky Plot: Where the ‘birds’ are in the sky. (Screenshot: Tim Burch)
These manufacturers are pairing iOS and Android developers with their hardware and firmware specialists to create a user-friendly interface that will function on most of the most popular handheld devices on the market today. From Apple iPhones and iPads to Samsung Galaxy phones and tablets, these applications give the surveyor the best of two worlds — sophisticated data-collection capability on a well-known and reliable mobile operating system platform.
The Android platform is becoming especially popular in the handheld mapping market segment. Current users of this environment include Hemisphere GNSS, CHC Navigation, Tersus GNSS and Trimble.
The iOS applications, while not quite as prevalent as Android, are being embraced by several significant GNSS manufacturers, including JAVAD GNSS and Eos Positioning Systems.
These companies are creating iOS and Android apps that embrace the BYOD market, providing their users with affordability and creating a comfort level simply because of the familiarity of the device and its environment.
How Good Is It?
iOS Position. Status of survey data collection and GNSS engine signal reception. (Screenshot: Tim Burch)
For the surveyor to be satisfied with the operation, the collection process must be efficient, cost-effective and easy to use. For this explanation of key items within a well-rounded data-collection application, we are using the JAVAD Mobile Tools (now J-Mobile) application built specifically for the Android and iOS operating systems.
The Android system (Version 7.0) was installed on a rugged CAT S41 cellphone made Bullitt Group from the United Kingdom, while the iOS app was used on the author’s iPad Air 2 running Version 12.2. Both apps were utilized in conjunction with the JAVAD Triumph-2 GNSS receiver.
After putting both versions through trial testing and checking against values on known monuments, here is the results of our findings:
Receiver Setup. Visual reference for leveling and direction of GNSS receiver. (Screenshot: Tim Burch)
Data Organization. Easy to comprehend and flexible for most naming conventions.
Corrections and Sources. Easily connects to base receiver and radio or available NTRIP correction service for real-time network (RTN) capability.
Sky Plot. Because the Triumph-2 is equipped to receive most of the available satellites in service, the Sky Plot feature is beneficial to the user for assessing potential interference.
File Management, Import and Export. Covers the typical file management and transfer functions used by the surveyor.
RTK Survey Operations. Robust telemetry keeps the users informed of specific satellite data and correction status.
Point Confirmation. Survey point information with metadata and equipment listing. (Screenshot: Tim Burch)
Coordinate Systems. All standard coordinate systems are included with features to allow the user to customize their own systems.
Localization. Creation of a local coordinate system is a simple routine, providing strong quality checks for data integrity.
Lift and Tilt. This feature provides the user with a useful procedure to end data collection without the need to press a button. This feature significantly increases the user’s productivity.
Compass and Level Calibration. With the Triumph-2 having an internal compass and level system, status of the receiver is graphically displayed to help the user keep a close watch on the accuracy of the survey point.
Survey Points and Linework. Most point naming systems and line-coding procedures are easily adapted. Total Station Point Transfer. The creation of control point files for transfer to total stations is simple and easy to use.
Stakeout. Graphical status screens provide the user with simple plotting capability of the desired stakeout point to increase efficiency and accuracy.
These apps are good at providing the surveyor with a solid tool for data collection and staking capability. They are especially good when paired with a real-time kinematic
(RTK) base station or NTRIP correction service.
But what happens when cell service is not readily available, or there are no published monument coordinates to establish site control? These apps have the surveyor covered for that situation as well.
Post-Processing (OPUS and DPOS)
Today’s surveyor works in an environment where geographic-based data is a key component to the services they render to their clients. While most of the world’s developed nations have access to cellular networks in which most GNSS receivers can communicate with an RTN providing corrective solutions, the places where this is not possible relies on other means of data correction.
In the U.S. we rely on OPUS (Online Post-Processing User System) to provide that service. But, as good as it is, it has limitations. Currently, it only utilizes GPS satellite data from the U.S. Department of Defense and is subject to sporadic government shutdowns.
Other services, from both public and private sources, are in place around the world to provide a service similar to OPUS. These include, but are not limited to:
AUSPOS. Geoscience Australia (free)
APPS. Jet Propulsion Laboratory at California Institute of Technology (free)
CSRS-PPP. Natural Resources Canada (free)
GAPS. University of New Brunswick (free)
magicGNSS. GMV (free)
Centerpoint RTX Post Processing. Trimble (free)
JAVAD Data Processing Service (DPOS). JAVAD (free, processes any JAVAD GNSS jps file)
These correction services utilize other satellite constellations (GLONASS, Galileo, BeiDou and QZSS) for their solutions and can provide additional coverage, depending on the location of the user. Because of these services, geographic-based data is at the fingertips of surveyors worldwide.
JAVAD’s DPOS system is has the ability to collect static survey data and send it to the proprietary service for establishing new coordinate values for base-station use. This process is a function of the app and can be completed in a few short steps.
Once the base station values are calculated, the surveyor can make use of this information for establishing a base station for correction broadcasting.
Do You Need a Base Station?
The establishment of RTNs has greatly enhanced surveying capability as cellular service has increased in coverage and speed. However, there are still instances and locales that do not allow for the reliable use of cell signals to provide those corrections accurately.
Various manufacturers’ tests have proven the accuracy of using an RTN subscription versus the traditional GNSS base and rover RTK setup. But cell-signal strength can be an Achilles heel, crippling those who choose not to set up a base station.
The UHF radio, even in its reduced power state from regulatory changes, is still more powerful and reliable than most cell services. 5G technology and coverage is anticipated to revolutionize cellular service, but it has yet to be realized.
Adaptation of the Industry
Other GNSS manufacturers (including NovAtel, Navcom, ComNav, Unicore, Emcore, Suzhou, TeleOrbit and Geneq) are producing receivers that can be adapted to a variety of existing data collectors and connect to iOS/Android mobile devices through various software developers.
The future of communications remains the smartphone or tablet device, with foldable units expected to be the next big thing.
As processors get more powerful, as chip memory becomes more abundant, and as more satellite constellations orbit in our sky, surveyors and their data collectors will continue to evolve. The future remains bright for technology and the surveyor has a front-row seat.
TIM BURCH is GPS World’s contributing editor for Survey. A professional land surveyor with more than 30 years of experience, he is director of surveying at SPACECO Inc. in the Chicago area. For several years he has been secretary and was recently named vice-president of the Board of Directors of the National Society of Professional Surveyors. He writes a bi-monthly column in the Survey Scene e-newsletter. Subscribe free at env-gpsworld-integration.kinsta.cloud/subscribe.
Receiver, Software Ready for Mobile
Photo: ComNav
ComNav receivers offer multiple data-collection device choices via Bluetooth connection, as well as an Android app.
For instance, the G200 provides centimeter-accuracy positioning to any connected mobile devices for RTK field surveying. It is able to delivery robust survey workflows with the SinoGNSS Android-based Survey Master, so that surveyors can collect quality high-accuracy positions no matter what mobile device they are using.
The G200 is a rugged, compact, wearable GNSS receiver. Combined with the high-performance SinoGNSS OEM board tracking GPS L1/L2, BeiDou B1/B2, GLONASS L1/L2, Galileo and QZSS, the G200 enables reliable high-precision GNSS performance for land survey tasks anywhere in the world.
TerraStar Gives Assist to RTK
Photo: Leica Geosystems
NovAtel offers several levels of corrections via its TerraStar service. For surveying applications, the RTK Assist service provides correction data to bridge surveyors through any real-time kinematic (RTK) correction outages. TerraStar services work on NovAtel’s OEM6 and OEM7 receivers..
RTK Assist, available on OEM6/OEM7 receivers, provides 20 minutes of RTK assistance, enabling surveyors to maintain centimeter-level accuracy. A higher service level, RTK Assist Pro, is available on OEM7 receivers. It provides unlimited RTK assistance with stand-alone centimeter-level positioning when RTK is not available.
Trimble Offers Web-Based Post-Processing
Photo: Trimble
Trimble’s CenterPoint RTX Post-Processing Service is a free, web-based solution that provides rigorous processing of GNSS data for users around the globe.
Powered by advanced algorithms for processing static observations, CenterPoint RTX Post-Processing supports data including GPS, GLONASS, Galileo, BeiDou and QZSS. With the service, users can upload GNSS data using Trimble formats or industry-standard RINEX 2 and RINEX 3. The service supports all dual-frequency GNSS receivers and more than 400 different antennas.
The post-processing service computes single-station static observation sessions ranging in length from 10 minutes up to 24 hours, with longer observation sessions recommended to produce the highest accuracy. Using data from the global RTX tracking network, the CenterPoint RTX Post-Processing service computes the position of the observed point with centimeter accuracy.
Results are delivered via email in ITRF coordinates at the current epoch and can be transformed to a fixed epoch by use of a standard tectonic-plate model.
Atlas Corrections Ready for BYOD
The Atlas GNSS global correction service, offered by Hemisphere GNSS, provides correction data for GPS, GLONASS, BeiDou and Galileo constellations. Its global L-band corrections allow for accuracies ranging from sub-meter to sub-decimeter levels. The network has more than 200 reference stations worldwide and covers virtually the entire globe.
Examples of how the AtlasLink webUI looks on a smartphone. (Image: Hemisphere GNSS)
The Atlas platform was conceived to enable as many people as possible to have access to the correction service technology, either as an end-user or as part of their business. Several features are designed to enable customers who use non-Hemisphere positioning systems to have access to Atlas.
For instance, Hemisphere’s SmartLink technology allows an AtlasLink GNSS smart antenna to be used as an Atlas signal extension for any GNSS system compliant with open communication standards.
Hemisphere’s GNSS smart antennas including AtlasLink, A326, C321+ and S321+ offer a user-friendly web user interface (WebUI) that can be used to configure, monitor and manage the receiver from virtually any modern computing device, including computers, phones and tablets.
