Tag: network RTK

  • Adaptive model shields real-time positioning from ionospheric chaos

    Adaptive model shields real-time positioning from ionospheric chaos

    For users relying on centimeter-level accuracy — such as surveyors, engineers and autonomous systems — ionospheric disturbances can mean system downtime and significant losses. Traditional network real-time kinematic (NRTK) positioning methods assume smooth ionospheric conditions and thus fail during active solar periods.

    To meet these challenges, a research team from Wuhan University and Guangzhou Hi-Target Navigation Tech Co. Ltd. developed an NRTK positioning model capable of maintaining centimeter-level accuracy under intense ionospheric disturbances.

    This approach could serve as the foundation for next-generation, self-correcting navigation systems that operate reliably under any atmospheric condition.

    The study (DOI: 10.1186/s43020-025-00179-4), published in Satellite Navigation on Oct. 6, introduces a dual-optimization framework that integrates real-time ionospheric indices with adaptive functional and stochastic models. By learning from disturbance patterns and automatically recalibrating user-side algorithms, the system dramatically enhances GNSS reliability during the ongoing solar cycle peak — offering a key safeguard for positioning technologies in low-latitude regions most vulnerable to ionospheric turbulence.

    The innovation centers on leveraging the rate of the total electron content index (ROTI), a key indicator of ionospheric activity, to dynamically adjust both ionospheric residual estimation and observation weighting. When the system detects disturbances, it automatically reduces the influence of affected satellites and refines error models in real time.

    Using data from Hong Kong’s Continuously Operating Reference Station (CORS) network — one of Asia’s most active low-latitude regions — the researchers found that ROTI showed a strong positive correlation (0.91) with ionospheric interpolation errors and a negative correlation (–0.9) with signal-fixing rates.

    Compared to conventional NRTK methods, their adaptive “Method B” improved horizontal and vertical positioning accuracy by 37.6% and 41.6%, respectively. Moreover, it achieved a stable 84% average fixing rate, even during equinoctial months when ionospheric scintillation is strongest. The results reveal not just a technical upgrade but a practical solution for real-time navigation across regions frequently affected by solar-induced ionospheric noise.

    “Our method essentially teaches GNSS systems to think smarter under stress,” said Xiaodong Ren, senior researcher at Wuhan University and lead author of the study. “By allowing the model to ‘sense’ and adapt to space-weather disturbances in real time, we’ve moved beyond static correction systems toward intelligent positioning. This is crucial not only for maintaining accuracy but also for ensuring resilience as solar activity intensifies.”

    He added that this approach could serve as the foundation for next-generation, self-correcting navigation systems that operate reliably under any atmospheric condition.

    This adaptive NRTK framework marks a significant leap forward for industries that depend on precise, real-time location data — from autonomous driving and drone surveying to precision agriculture and infrastructure monitoring, Ren said. By integrating live ionospheric monitoring into everyday positioning workflows, it ensures continuous accuracy even when solar storms strike.

    Future developments may combine the model with artificial intelligence and multi-constellation GNSS networks to further enhance forecasting and resilience. As Earth moves through one of its most active solar cycles, Ren said, such innovations will be essential to keeping navigation, communication and automation systems firmly on course.

  • Singular XYZ launches GNSS receiver with network RTK rover

    Singular XYZ launches GNSS receiver with network RTK rover

    Singular XYZ has released the Sfaira One GNSS receiver. The portable size, centimeter-accurate receiver provides users with an entry-level network real time kinematic (RTK) rover.

    Sfaira One is equipped with a GNSS module with 1,408 channels for GPS, BDS, GLONASS, Galileo and QZSS tracking — providing centimeter positioning in harsh environments. It also features advanced RTK and an anti-interference algorithm.

    The GNSS receiver connects via Bluetooth and can be configured to conduct surveying tasks on a smartphone. Additionally, Sfaira One supports SingularPad and SingularSurv software and is also compatible with mainstream field survey or GIS software.

    Sfaira One is IP65 dustproof and waterproof, which makes the receiver suitable for all weather conditions. It has a 4,800 mAh battery life with 16 hours working time and type-C interface that can be charged on-the-go with power bank.

    The Sfaira One GNSS receivers are online at SingularXYZ’s website and are available now.

  • Corrections Services Abound

    Corrections Services Abound

    Photo:
    While single-base real-time kinematics RTK can, under specific conditions, be the best option for certain applications in surveying and construction, corrections services typically eschew this solution in favor of network RTK, PPP, and PPP-RTK. There are, though, some agricultural networks made up of clusters of reference stations delivering RTK corrections. (Images: courtesy of Gavin Schrock and Courtney Townsend
    Bigmouse108/iStock / Getty Images/Gettu Images)

    The boom in the development of corrections services for applications such as autonomy and robotics has brought a whole new slate of market players, and an expansion of services from established corrections providers. This has benefitted high-precision users as well as the new not-so-high-precision applications.

    Whereas very high precision — centimeters — is of paramount importance to sectors such as precision agriculture, construction automation, surveying and mapping, new market sectors are less concerned with precision as they are with reliability, availability and resilience. There are many corrections services that can deliver reliable lane-level precision, decimeter precision, sub-meter or whatever the application requires.

    Corrections have been around in various forms for nearly 30 years. Whereas traditional high-precision applications would access corrections services or network infrastructure directly, the user of a mass-market application, such as assisted or autonomous driving, receives corrections second or third hand.

    A car manufacturer may install an integrated navigation and positioning system (GNSS is typically only one of many technologies in a complete system) from a vendor that receives corrections from one or more corrections services.

    A Recap of the Technology

    Uncorrected GNSS is limited to precisions in meters. This may be fine for many purposes, such as coarse navigation and local-based apps. However, for high precision uses, external augmentations (commonly referred to as “corrections”) add more and higher accuracy data to help mitigate multiple sources of error that otherwise limit standalone GNSS results. Various augmented data can be delivered via radio, the internet, or communications satellites. Delivery of augmentations by public or commercial generators of this add-on data is broadly referred to as “positioning services.”

    Photo:
    Network RTK, implemented as real-time networks (RTN), covers hundreds of localities, states, and entire countries and is a go-to for many applications in surveying, mapping, construction, monitoring and agriculture. One disadvantage, compared to PPP, is reliance on terrestrial IP communications. (Images: courtesy of Gavin Schrock and Courtney Townsend
    Bigmouse108/iStock / Getty Images/Gettu Images)

    There are two fundamental approaches to generating corrections: Observation Space Representation (OSR) and State Space Representation (SSR). OSR uses observations of one or more base receivers to derive correction values representative of local conditions. Examples of OSR include base-rover real-time kinematics (RTK) and network RTK (NRTK). SSR provides “states” of conditions derived from terrestrial tracking networks, to improve clock and orbit “products,” and may also include data from global, regional, or localized ionospheric and tropospheric models. Examples of SSR include precise point positioning (PPP) solutions.

    Players in the corrections services sector include vendors who manufacture GNSS hardware, RTK systems, and NRTK software. One example is real-time networks (RTN), which have grown to cover hundreds of localities, states, regions, and even entire countries. Some of these vendors now operate their own wide region RTN. The same large vendors also have developed global PPP services. The most recent decade though has seen rapid growth in new corrections service providers that focus on one or more key markets and develop approaches specifically to serve them. For instance, many agricultural regions of the world have large clusters of RTK stations operated by a vendor or a cooperative. Some newer vendors, focused on the autonomy market, have developed global PPP services, regional NRTK, or hybrids for decimeter to meter precision. One Achilles heel of PPP is its relatively poor vertical precision compared to RTK and NRTK. This partly explains why adoption has been slow for certain high-precision applications, such as surveying.

    Where corrections services have become quite interesting, is in amalgams of these approaches. In recent years, the rapid expansion of corrections services for mass-market applications has given rise to what developers call PPP-RTK. Ostensibly, this is to take advantage of the strengths in each approach, however it may be more about trade-offs between precision and the practicalities of serving wide regions in a cost-effective manner. There are many variations on how this hybridization is achieved; for example, PPP- ambiguity resolution (PPP-AR). PPP-RTK can be somewhat of a nebulous term, much in the same way as the term “AI” gets used. Developers of the specific PPP-RTK approaches for the many corrections services keep certain details close to their chests. Clients are less concerned with how it works as they are with the results.

    Examples of Vendors

    In compiling the following list, we tried to provide examples of all aspects of the corrections service industry — from GNSS network software development to hosting of national and regional networks to providing global PPP. This segment continues to grow; new players continue to develop solutions and enter the market, some with great fanfare, while others seek to stay under the radar. This list does not include the many hundreds of RTN worldwide — local, regional, or national — though the key providers of the NRTK software these networks use are listed.

    Photo:
    One advantage of PPP and PPP-RTK over RTK and NRTK is that they can deliver augmentations by satellites, eliminating reliance on terrestrial communications networks. Satellite delivery has a downside: the number of communications satellites broadcasting the augmentations is limited, which can be problematic in sky-view challenged areas. (Image: courtesy of Gavin Schrock and Courtney Townsend
    Bigmouse108/iStock / Getty Images/Gettu Images)

    Note that other vendors are also not listed, such as some that seek to limit their visibility to specific clients and partners. For example, some offer corrections services as an adjunct to inside hardware/software sales, and others work with developers of certain integrated navigation/autonomy systems. In addition, some of the smaller vendors may be working in conjunction with some of the more established developers, often licensing elements of their software, and in many instances piggybacking on their global tracking networks.

    In alphabetical order:
    Atlas. From Hemisphere GNSS. A global PPP service delivered by L-band satellites. It includes tiered precision for different applications, such as surveying, mapping, and asset management. Atlas Basic, Atlas H30, Atlas H10: bit.ly/3V42qxj.
    CHCNAV. CPS NRTK software: bit.ly/3FI6zlN. It also hosts various RTN and has a global network partner program: bit.ly/3VQugOr.
    CNH. Advance Farming Software (AFS) RTK+ network delivering corrections mostly via cellular to primarily precision agriculture users: bit.ly/3YiCZur.
    DigiFarm. DigiFarm VBN. An example of another network that serves primarily agriculture users, however, it now has a spinoff to serve other high precision markets: bit.ly/3hgnYZs.
    eSurvey. GNSS NET, a VRS management software: bit.ly/3Py0uMp.
    Fugro. Global PPP corrections services; tiered precision for various applications, mostly maritime and marine construction. StarFix, SeaStar, MarineStar, OceanStar: bit.ly/3W4LkA8.
    Geo++. One of the first developers of GNSS network and PPP solutions. Its GNSMART software suite provides NRTK and SSR broadcast capabilities: bit.ly/3FhGE2Z. 
    HERE Technologies. HD GNSS, a PPP-RTK solution for mass-market applications: bit.ly/3Fnle4H. 
    Hi-Target. Hi-RTP, a global PPP- RTK service: bit.ly/3hi2xHv. 
    IGS. International GNSS Service, a federation of agencies and research entities with a global tracking network of more than 400 reference stations. The IGS is a vital component of the global geodetic infrastructure. RTS is its real-time PPP service. It is not fast converging like many of the commercial services, but it is free for many applications. It is not broadcast via satellites, only via the internet: igs.org.
    Leica Geosystems. Part of Hexagon. Provider of NRTK software (Spider), and host of its own RTN covering various regions around the world (SmartNet), and global PPP (SmartLink): bit.ly/3uEwHb9. 
    NovAtel. Part of Hexagon. Includes various tiers of PPP-RTK: RTK Assist, RTK Assist-Pro*, TerraStar-L, Oceanix, TerraStar-C PRO*, and TerraStar-X* (what NovAtel calls “RTK From the Sky”): bit.ly/3HzuqWh. 
    Point One. RTK correction service called Polaris, available also via partners such as Bad Elf: bit.ly/3uPJGqA.
    Premium Positioning. RTK corrections service called RTK Premium: bit.ly/3uT0xZi. 
    Rx Networks. A mix of tiered positioning approaches for location- based applications. Truepoint. io (DGNSS, PPP, PPP-RTK): bit.ly/3We1rvT. 
    SBAS (Public). Satellite-based augmentation systems, national or regional services. Like commercial PPP, SBAS corrections are mostly served via satellites. Public safety and civil aviation are the primary drivers for providing such services. For instance, in North America, the Wide Area Augmentation System (WAAS) was chartered by the Federal Aviation Administration (FAA). There are equivalent systems in Europe (EGNOS), India (GAGAN), Japan (MSAS and QZSS), Russia (SDCM), China (SNAS/BDSAS, which is still in development) and Australia and New Zealand (SouthPAN). Other systems are in development in South America and the Caribbean (SACCSA), Korea (KASS) and in Africa and the Indian Ocean (ASECNA). 
    Sino/Comnav. CDC.NET CORS software, RTN software: bit.ly/3W56hvm. 
    Swift Navigation. Skylark RTK and Skylark DGNSS services: bit.ly/3HyWVn5. 
    Tersus GNSS. Tersus Advanced Positioning (TAP), a PPP service: bit.ly/3hoZkWD. 
    Topcon. TopNet and Topnet Live. RTN Software, regional RTN, and PPP services: bit.ly/3FRRcaw. 
    Trimble. RTN software, VRS Now (regional RTN), and tiered PPP services: CenterPoint RTX, RangePoint RTX, ViewPoint RTX, and FieldPoint RTX: bit.ly/3V3bbax. 
    u-blox. PointPerfect regional PPP and PPP-RTK: bit.ly/3FPVmQo. 
    Veripos. Part of Hexagon. Tiered global PPP services, originally focused on maritime applications: Standard, Ultra, APEX: bit.ly/3BBjfsf. 
    Verizon. Telecom infrastructure-based PPP-RTK service called ThingSpace: bit.ly/3Fw1U55. 
    Vodaphone. Currently developing corrections services in conjunction with Topcon: bit.ly/3Pug4s0. 

    Whatever the application, there are now many options for corrections services. Non-mass-market applications, for traditional high- precision uses, have been tapping such services for (in some cases) decades. The prize of primacy in the autonomy market has been in the sights of many of these vendors for many years, yet there have been relatively few real-world applications to date. That should be changing soon. Early adoptions such as GM’s Super Cruise, which is powered by the same core PPP technology as RTX, have been quite successful. Which will come out on top? That might be a moot question. With the potential of such markets so great, perhaps there is room for all of them, and more. 

  • Testbed enables infrastructure for autonomy, smart cities

    Testbed enables infrastructure for autonomy, smart cities

    Rooftop view of the central parts of Aarhus with the harbor area and the sea in the background. (Photo: DTU Space)
    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)
    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 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)
    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).

    "Figure

    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)
    Test location indicated with purple circle in the network plot. (Image: DTU Space)

    Altus APS3G unit mounted at the test location. (Photo: 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)
    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)
    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)
    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)
    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)
    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)
    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:
    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.

    For more on TAPAS, visit www.tapasweb.dk/english.

    Acknowledgments

    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.

  • Low-cost accuracy for ITS applications from a national GNSS network

    By Martti Kirkko-Jaakkola, Stefan Söderholm, Salomon Honkala, Hannu Koivula, Sonja Nyberg, and Heidi Kuusniemi, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland

    Our real-time kinematic (RTK) implementation, the Public Precise Positioning (P3-Service) project, has achieved horizontal positioning accuracy of 0.5 meters using relatively inexpensive equipment: a commercial off-the-shelf (COTS) low-cost GNSS receiver. The project used FinnRef, the Finnish national GNSS network.

    With inter-station baselines on the order of 200 kilometers, FinnRef is relatively sparse in comparison with commercial RTK networks. We used FinnRef as the RTK base station, either in single-base or network RTK mode. Although FinnRef’s main purpose is to maintain the national coordinate system, it is also capable of delivering DGNSS and network RTK data over the NTRIP protocol.

    Transport Applications. Horizontal position accuracy of 0.5 meters or better, achieved for more than 90 percent of the time with small, low-cost devices, could be useful in various applications, particularly in intelligent transportation systems.

    Current consumer-grade GNSS solutions routinely offer a positioning accuracy in the order of 5 meters, and satellite-based augmentation systems (SBAS) such as WAAS and EGNOS can improve the accuracy to the order of 1 meter. However, this is not adequate for all use cases; in particular, intelligent transportation systems (ITS) require better positioning performance. For instance, a horizontal accuracy of 0.5 meters is needed to reliably identify the lane in which a vehicle is driving. Maintaining inventory of machines, road signs and other infrastructure would also benefit from sub-meter accuracy.

    Sub-meter or even sub-decimeter positioning accuracies can be attained with a relatively good reliability in real time if a dual-frequency GNSS receiver and a physical or virtual base station are available. However, such receivers and virtual base station services are currently too expensive to gain popularity in the mass market. Recently, precise point positioning (PPP) has demonstrated that comparable accuracies can be attained without a base station using real-time precise correction data, but its drawback is a long convergence time. In contrast, differential methods utilizing raw base-station observations, such as RTK, converge much faster.

    Source: Martti Kirkko-Jaakkola, Stefan Söderholm, Salomon Honkala, Hannu Koivula, Sonja Nyberg, and Heidi Kuusniemi, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland
    Horizontal position estimation results from a low-cost COTS receiver (right); the green triangle marks the reference position solution.

    Network RTK Test. Network RTK performance was tested in a static scenario with the closest physical base station 63 kilometers from the rover receiver. Network corrections were delivered in the PRS representation, and data were logged for 20 minutes at a rate of 1 Hz. The plot above shows the resulting horizontal position errors. The dashed red circle with a radius of 0.5 meters centered at the reference location (green triangle) contains 90.4 percent of the position estimates.

    For a full account of the experiments and results described here, see the paper “Low-Cost Precise Posioning Using a National GNSS Network,” presented at ION GNSS+ 2015.

  • Hemisphere GNSS Debuts Atlas GNSS Correction Service

    Hemisphere GNSS Debuts Atlas GNSS Correction Service

    Atlas_Graphics-1-W

    Hemisphere has released Atlas, its new entrant into the GNSS global correction services market. Atlas is delivered via L-Band or the Internet at accuracy levels ranging from meter level to sub-decimeter level. Atlas support is being introduced across a wide range of hardware, including Hemisphere’s new AtlasLink smart antenna, also launched.

    “Atlas comes out of a change of culture and focus,” Hemisphere CEO Chuck Joseph told GPS World in an extensive interview that also included Rodrigo Leandro, Hemisphere’s director of engineering, GNSS Positioning Systems. For the full interview, see the second half of this news story.

    Starting June 19, Atlas will be available for subscription at the dedicated Atlas web portal across a range of Hemisphere’s multi-frequency, RTK-capable products, such as AtlasLink, R330u, V320 and VS330u. Atlas will also be available from a number of Hemisphere’s channel partners and OEMs such as Carlson Software, Inc.

    “Since joining Hemisphere I have heard from customers large and small that they need a different option when it comes to high-accuracy corrections, one they can buy from their provider of choice and with little to no impact on their operating budgets,” said Chuck Joseph, Hemisphere GNSS CEO and president. “We listened hard to what they told us and built Atlas to answer their needs — a totally new service that delivers freedom of choice to our customers along with industry leading corrections at dramatically reduced prices.”

    “We formed a team of our most experienced GNSS professionals with the task of developing a roadmap for the future of correction services business and technology in the world — assessing current needs, and also what users across the globe will be looking for over the next decade or two,” said Rodrigo Leandro, Hemisphere director of engineering. “Atlas not only introduces Hemisphere as a business and technology leader in the correction services industry today, it also provides an essential platform for delivering multiple levels of correction services to a very wide range of users spanning commercial business and consumer application use.”

    Systems supporting Atlas utilize the newly released and proven Athena GNSS engine. To be able to utilize Atlas corrections, users of supported systems will simply need to update to Athena firmware and purchase a subscription through the Atlas portal.

    To build Atlas, Hemisphere GNSS put together a team of seasoned developers whose collective experience matches the best in the GNSS industry. Together they have developed a GNSS correction service, available via L-Band satellite broadcast, which utilizes the most powerful technologies available to deliver a service that matches or exceeds competitive systems across a range of metrics:

    • Positioning accuracy: Atlas provides competitive positioning accuracies down to 2 cm RMS in certain applications.
    • Positioning sustainability: Position quality maintenance in the absence of correction signals, using Hemisphere’s Tracer technology.
    • Scalable service levels: Atlas is designed to serve all. It is capable of providing virtually any accuracy, precision and repeatability level in the 5 to 100 cm range.
    • Convergence time: Convergence times of 10-40 minutes.
    • Exclusive agnostic capability: Atlas is an agnostic positioning system. SmartLink technology allows an AtlasLink antenna to be used as an Atlas signal extension for any GNSS system compliant with open communication standards.
    • Network RTK augmentation: BaseLink technology allows Atlas-capable receivers to self calibrate, self-survey, and automatically manage the transmission of RTK correction data to augment or extend established or new GNSS reference networks in areas of poor Internet connectivity.

    Hemisphere-Atlas-table
    “High-quality corrections are essential to our customers,” said Randy Noland, director of Machine Control, Carlson Software, Inc. “The way all the existing services are purchased, delivered and supported is completely separated from the rest of the positioning ecosystem. We see Atlas as an opportunity for us to deliver corrections under our own brand as part of a holistic package — all of which means empowering our ability to provide a stronger solution and a better experience for our customers.”

    “Atlas completely changes how augmentation services are delivered and supported,” said Andy Smith at Saderet Ltd. “For the first time, distributors and dealers can fully participate in selling to and supporting our customers, strengthening our relationships by providing them with a much better experience.”

    “I’ve extensively tested Atlas, and the performance is exceptional, making it a great fit for our GIS and survey customers” said Jean-Yves Lauture at Eos Positioning Systems, Inc. “Even better, we can now offer global augmentation services with our Arrow GNSS receivers to our customers as part of an integrated solution. After many years in this industry, that’s a major change.”

    Atlas service levels and position accuracies can be customized to meet OEM needs, the company said.

    Exclusive Interview with Hemisphere’s Chuck Joseph and Rodrigo Leandro

    A Startup Inside a Reinvention

    “Atlas comes out of a change of culture and focus,” Hemisphere CEO Chuck Joseph told GPS World, in an extensive interview that also included Rodrigo Leandro, Hemisphere’s director of engineering, GNSS Positioning Systems. “We are reinventing a storied brand, and to do that we have to act more like the startups I have directed since leaving Trimble — move fast, be flexible, and focus on innovation. Effectively we are building a startup inside of a reinvention.”

    “On my first day on the job, we divided the staff into five working groups and told them: you are now startup companies, entrepreneurs, with six people each team. Go away and come back with big ideas. Go build a business plan. Out of that we got Athena, released last month, Atlas, AtlasLink, and a couple more new products coming out in the months to come.”

    A Different Kind of Corrections Service

    Joseph and his colleagues at Hemisphere describe the distribution, pricing, and overall business model of Atlas as “disruptive.”

    “Our approach comes directly from talking to customers in agriculture, machine control, and to our channel partners. Other corrections service providers did not allow them to participate, forced them to give up their end user list, and to buy directly from [the service provider] — who in some cases was their competitor in that market.”

    “When you step back you can see the impact of those restrictions — after 10 plus years the corrections service marketplace generates probably $150 million in total revenue — it should be bigger than that by now. We think a different approach combined with a very aggressive price point will substantially broaden the marketplace.”

    “We’ll be making announcements of OEM signings in the months to come. For us it’s all about what works for our partners — some of them will private-label the service, some will choose to use the Atlas brand. We really don’t care if our name is on the product or not — we’re an OEM play. Whatever brand they choose, we will provide them with the infrastructure to be successful, even down to the portal their customers will use to manage their devices and subscriptions — we will develop that for them, and provide the back-end e-commerce.”

    A Look at the Technology

    Rodrigo Leandro added, “The basic architecture is not extremely different from other L-band reference services. However, within that, we have really pushed to develop leading-edge technology. For example, our correction method format is well-developed for new constellations and different applications it can serve, and our corrections message structure is the most advanced of those available today. As a result, we have a number of patents pending on technologies included in Atlas.”

    Chuck Joseph interjected, “When we were doing the initial planning for Atlas we agreed that it was absolutely critical that our performance meets or beats the competition’s, otherwise we wouldn’t want to offer it to customers out there. We have been benchmarking the competition at every stage of our development, and know that we are delivering a market leading product.”

    “This slide shows the same, single antenna connected to Atlas and to a competitor, and it shows being able to converge down to decimeter level.

    Chart: Hemisphere GNSS

    “This one gives more details on time to converge.

    Chart: Hemisphere GNSS

    “And here, this one shows pass-to-pass results, the relative accuracy between 2 tracks of the tractor — this is important for people more interested in agriculture applications. We can get down to 2.5 centimeters.”

    Chart: Hemisphere GNSS

    “The new AtlasLink antenna is designed to be a main channel for customers of our service. It can be used in GIS, machine control, marine applications and so on. Features inside it include a very big internal memory storage, a web server application, multi-GNSS multi-frequency capability, L-band and RTK — it supports Atlas and Athena out of the box. Other innovations will come later, for instance, incorporating Galileo. We believe it is the most powerful multi-purpose GNSS smart antenna in the industry.”

    “At the same time there is easy support and easy configuration by the user. It takes literally about six clicks from log-in to register the receiver, out of the box. In 20 minutes you’re running Atlas. It’s very easy to get up and running.”

    Broadening the Market

    Leandro continued, “The Atlas service isn’t the only area of innovation however. We also spent a lot of time working on how we could deliver the service to the broadest possible audience, and the resulted in two key features of our AtlasLink antenna — SmartLink and BaseLink. Those features free customers from the restrictions of their current hardware and current service — they really change the game.”

    “Customers don’t want to have to buy a new $10-$20K receiver [in order to get a corrections service]]. If you’re happy with the hardware you’re currently running, there’s no need to change it, you can still get this service. We are not in the business of using the service to sell hardware. We are using the hardware to sell the service.”

    Joseph concluded, “This is all good for OEM customers. For them the SmartLink and BaseLink capabilities are huge. They can go back into their installed base and not have to push people to upgrade receivers or get a brand new receiver. At the same time, it enables them to go after their competitors installed base, and opens up markets that previously weren’t available such as recreational marine service, for example, the lower end of the marketplace. Fundamentally, we want to change this market — enable more users to get access to correction, and deliver real choice to those that have it already.”

     

  • Which Industry Will Be the Largest Consumer of RTK Technology?

    Which Industry Will Be the Largest Consumer of RTK Technology?

    In September, I attended the Institute of Navigation (ION) GNSS+ conference in Tampa, Florida.

    Downtown Tampa, FL Location of the 2014 ION GNSS+ Photo: GPS World
    Downtown Tampa, location of the 2014 ION GNSS+. Photo: GPS World

    The ION GNSS+ conference is a gathering where many of the GNSS scientists from around the world come to share their successes, trials and tribulations. It gives one a view into the future of where GNSS positioning might go. Granted, most of the ideas and concepts presented won’t ever be introduced in a commercial product, but it’s great to see that engineers are pushing the technology envelope to see how much they can squeeze from receivers.

    As I was perusing the ION GNSS+ conference agenda, I was looking for presentations and other subject matter relevant to RTK GNSS technology. (Yes, I’ve been obsessed with low-cost RTK receivers this past year, if you haven’t been following).

    I’d like to tell you about two presentations I attended. The first was sort of unexpected, and the second was every bit of what I hoped it would be.

    The first was a presentation by SubCarrier Systems Corp (SCSC), a small consultancy focused on ITS (Intelligent Transportation Systems) technology. It just so happens, according to David Kelley of SCSC, that RTK receivers and RTK networks will play a critical role in the future of ITS and, as a result, help drive down the cost of RTK technology.

    How is RTK relevant to ITS?

    In ITS, I’ve been told there are three levels of accuracy that drive particular ITS applications. The accuracy terms are expressed in transportation terms:

    • Which Road?, Which Lane? and Where in the Lane?

    Translated into GPS accuracy terms:

    • Which Road? = Autonomous GPS — 5-meter accuracy
    • Which Lane? = WAAS (or SBAS)-corrected GPS — 1-meter accuracy
    • Where in the Lane? = RTK — 2-cm accuracy

    "Safety Applications are Enabled by increased accuracy in the rovers"

    Mr. Kelley further presented that transportation applications of RTK technology will drive mass-market adoption (commoditization) of RTK technology and into the millions of units sold.

    The Automotive Sector: Extending State Networks to Support Vehic

    Lastly, he discussed the strain that such massive deployment of RTK technology in transportation might place on existing RTK networks run by state agencies.

    The Automotive Sector: Extending State Networks to Support Vehic

    To view the entire presentation from Mr. Kelley, you can click here.


    The second RTK-centric presentation I attended at the conference was a moderated discussion panel entitled “High-Precision GNSS — What Will It Look Like in 2020?”

    If you’ve followed my articles over the past couple of years, you have to know I was looking forward to attending this discussion panel with great anticipation.

    Discussion Panel Members: High Precision GNSS - What will it Look Like in 2020?  Photo: GPS World
    Discussion Panel Members:
    High Precision GNSS – What will it Look Like in 2020? Photo: GPS World

    The discussion panel members were (from right to left):

    • Gian Gherardo Calini – European GNSS Agency
    • Ivan Di Federico, Chief Strategy Office and EVP, Topcon Positioning
    • Bernhard Richter, GNSS Business Director,  Leica Geosystems, Switzerland
    • Elmar H. Lenz, General Manager – Geospatial GNSS, Geospatial Division, Trimble Navigation Ltd.
    • Jan Van Hees, Director of Business Development, Altus Positioning Systems
    • Shaowei Han, Co-founder and CEO/President, Wuhan Navigation and LBS, Inc., China

    The discussion began with a short presentation by Gavin Schrock, who, among other things, administers the Washington State Reference Network, a state-wide RTK network, to frame the discussion.

    Next, each panel member commented on the presentation and provided some of their own thoughts. The thoughts by the mainstream manufacturers were largely what you’d expect, since they do not look forward to the day that RTK technology becomes a commodity.

    I’ll cut to the chase and just say that the gentleman from China, Dr. Han, stunned the audience with his claim that RTK GNSS chips will eventually be sold for $20 each. OK, to be fair, he also said RTK GNSS modules (an RTK GNSS chip on a circuit board with supporting components) will sell for $100. At first, these numbers seemed somewhat shocking to the audience, and one might dismiss it as being a speculative pipe-dream to disrupt the current RTK receiver competitive landscape. But then, when questioned, he dropped the reality bomb with a sort of puzzling look at the audience, being a little surprised why they didn’t understand. He said, and I’m paraphrasing, that $100 for an RTK module in 2020 doesn’t seem to be a stretch at all if you consider that RTK GNSS modules in China are selling for only $400 today. BOOM! He dropped the hammer. I admit, the $400 number even surprised me a bit. I thought it was more like $800.

    The reason for the low price is the number of RTK GNSS receivers sold in China is more than 100,000 per year now, and growing. That’s more than the rest of the world combined. What’s driving the demand for RTK GNSS receivers? You guessed it — transportation. While the mainstream RTK GNSS manufacturers are still talking about RTK GNSS technology for niche markets like surveying, engineering, GIS, construction, and agriculture, Dr. Han was talking about RTK GNSS technology being used by everyday consumers for everyday activities. He’s talking about the commoditization of RTK GNSS, and he’s right. The only question that remains is how soon it will arrive.

    Thanks, and see you next month.

    Following me on Twitter at https://twitter.com/GPSGIS_Eric

     

  • Topcon and MAVinci Announce Sirius Pro for Use with RTK Base Stations or NTRIP

    Topcon Positioning Group and MAVinci GmbH have released the latest version of the Sirius Pro surveying UAS (Unmanned Aerial System) program, designed to be compatible with existing RTK (real-time kinematic) base stations or NTRIP (network transport of RTCM data over IP).

    “By connecting an external base station, Sirius Pro will receive the RTCM correction signals and deliver 2-5 centimeter accuracy without using ground control points,” said Eduardo Falcon, executive vice president and general manager for the Topcon GeoPositioning Solutions Group. “When you have mobile Internet on your site, you can achieve the same accuracy even without a local base station using NTRIP.”

    Sirius Pro is designed to deliver orthofotos and three-dimensional elevation models with a high absolute accuracy of 2-5 centimeters without using ground control points. “Combining MAVinci‘s precision timing technology with Topcon sub-centimeter grade L1/L2 GPS/GLONASS RTK receivers, this robust system stands up with a clever solution that helps in the realizing of projects in a better and faster way,” said Johanna Claussen, CEO at MAVinci.

    For users who do not have an RTK base station, an internal base station add-on for the Sirius Pro is available. “It upgrades the Sirius Pro to its full functionality: Use of an internal or external base station depending on your needs,” Claussen said. “This add-on is available anytime via Internet without changing your hardware.”

    Sirius Basic is an entry-level solution for UAS surveying, and delivers orthofotos and 3-D elevation models. The system is designed to offer high-accuracy when using ground control points. “Sirius Basic offers you full flexibility,” said Falcon. “It can be upgraded to Sirius Pro via an Internet update later on — no hardware change is necessary.”

    The system will be available at the Intergeo trade show for geodesy in October and thereon.  The Topcon and MAVinci UAS was first introduced at Intergeo 2013 for the European market and was recently made available in the North American market.

  • Spectra Precision’s Latest Survey Receiver Uses Six GNSS Systems

    Spectra Precision’s Latest Survey Receiver Uses Six GNSS Systems

    Spectra-Precision-SP80-GNSS-Receiver-River-W

    Spectra Precision introduced today its next-generation Spectra Precision SP80 GNSS receiver. Designed to meet the evolving needs of the survey market, the new SP80 combines GNSS technology and a combination of communication capabilities with an ergonomic design, the company said. The SP80 is specifically designed for mainstream surveying and construction applications such as cadastral, topographic, control, stakeout and network RTK.

    Spectra Precision SP80 features Spectra Precision’s Z-Blade GNSS-centric technology running on a new-generation, 240-channel 6G chipset. The SP80 is capable of fully utilizing all six available GNSS systems (GPS, GLONASS, BeiDou, Galileo, QZSS and SBAS), but can also be configured to use only selected constellations in an RTK solution (GPS-only, GLONASS-only or BeiDou-only).The SP80 is also compliant with the new RTCM 3.2 standard, including the recently approved MSM RTCM messages, which means it supports all available GNSS corrections.

    SP80-GNSS-Front-with-Antenna-Pole-WThe extended communication capabilities of the SP80 receiver provide a combination of a 3.5G GSM/UMTS modem, Wi-Fi and Bluetooth connectivity, and an optional transmit UHF radio. The receiver’s built-in Wi-Fi and 3.5G modem can provide an Internet connection for RTK corrections and also send SMS or e-mails with system alerts. The SP80 features a unique anti-theft technology to safeguard the receiver and can detect if it is has been disturbed while in the field (for example, when operating as a GNSS base). The anti-theft protection feature informs the surveyor via SMS or e-mail if the SP80 receiver is moved and can provide its position to facilitate recovery.

    The Spectra Precision SP80 is rugged and waterproof, yet compact, lightweight and ergonomic for ease of use in the field, Spectra Precision said. When the UHF transmit radio module is used, its UHF antenna remains protected inside the rugged rod, extending the radio range performance. Powered with dual hot-swap batteries for typical all-day operation, the SP80 receiver is an ideal tool for any surveyor.

    “The Spectra Precision SP80 introduces several major enhancements and innovations, including the new 6G GNSS ASIC with enhanced Z-Blade technology, unique SMS and e-mail messaging and patented inside-the-rod mounted UHF antenna,” said Olivier Casabianca, business area director of Trimble’s Spectra Precision Division. “In addition, SP80 was designed as an extremely reliable receiver, making it suitable for a variety of challenging surveying projects.”

  • Settop Survey Offers Network RTK Repeater

    Photo: Settop SurveySettop Survey is offering the Settop Repeater, which allows network RTK rover use in areas of low- or non-GSM coverage by receiving differential corrections via radio. A new firmware update allows connection via any external radio to connect the repeater to precision agriculture systems or machine control. Repeater field application versatility is managed by intuitive software using a touchscreen.

  • Network RTK Rover

    Network RTK Rover

    The Topcon Tesla RTK handheld controller can serve as a network RTK rover. It is designed to maximize 3D measurement tasks and use of Magnet Enterprise. Magnet is a browser-based solution to manage field and office data in the cloud, as well as track assets and communicate on projects.

    The Tesla RTK features an integrated RTK GNSS receiver, 5.7-inch touchscreen, Windows 6.5.3 OS, 806-MHz processor, built-in 3.2MP camera, 3.5G cellular modem, and Bluetooth/Wi-Fi ability.

  • Network RTK for Intelligent Vehicles

    opener

    Accurate, Reliable, Available, Continuous Positioning for Cooperative Driving

    By Scott Stephenson, Xiaolin Meng, Terry Moore, Anthony Baxendale, and Tim Edwards

    Adoption of network real-time kinematic GNSS positioning can lead to major improvements in vehicle localization, although implementation must overcome some real-world challenges. This article assesses the extent of GNSS signal outage in a motorway environment. The average total GNSS outage period and the average time to resolve ambiguity for the network RTK solution can help assess complimentary sensors for a ubiquitous positioning system.

    Real-time vehicle localization is one of three key enabling technologies for the concepts of vehicle-to-vehicle and vehicle-to-infrastructure (V2V and V2I, collectively termed V2X, see opening graphic), a classification of intelligent transport systems (ITS). The further enabling technologies are ad-hoc dynamic networking of agents, and accurate dynamic local traffic maps. Jointly, these require that positioning be accurate, reliable, available, and continuous.

    A natural evolution in road transport, V2X promises to deliver the next major safety breakthrough. The concept moves away from vehicles making individual decisions about road safety, as in advanced driver assistance systems, and towards a cooperative driving approach that shifts the emphasis from collision protection to collision prevention. The U.S. National Highway Traffic Safety Administration  estimates that V2X technology can avoid or minimize up to 80 percent of collisions of unimpaired drivers, and that even a small number of deployed vehicles will provide tangible safety benefits.

    Network RTK GNSS positioning, like V2X applications, requires a communication system; and by its nature V2X has a positioning solution requirement. Thus it is envisioned that network RTK will play an essential role in the implementation of V2X systems. The consensus between car manufacturers and research organizations is that the future of V2X communication lies with Dedicated Short Range Communication (DSRC) devices, and a large pilot study is currently under way. However, in the short term many V2X applications could be achieved using existing technology, such as cellular communication, offering a legacy solution, and initiating early uptake of V2X applications.

    Previous research by the Nottingham Geospatial Institute (NGI) at the University of Nottingham showed that network RTK positioning can provide a high-accuracy positioning solution during real-world trials, but also revealed two areas of concern: the loss of the fixed-integer ambiguity during satellite line-of-sight outages; and the fragility of the data communications service that delivers the real-time correction information. During road tests, a fixed-ambiguity network RTK solution was available for less than 50 percent of the time on United Kingdom (UK) roads.

    Network RTK Vehicle Positioning

    Figure 1  OS Net reference station network in Britain, owned by Ordnance Survey.
    Figure 1. OS Net reference station network in Britain, owned by Ordnance Survey.

    Networks of continuously operating reference stations (CORS) extend across Europe, North America, Australia, and East Asia. Networks vary in size from five or six reference stations for agriculture to systems of hundreds of CORSs providing national or regional service. Figure 1 shows the location of the OS Net CORS run by Ordnance Survey in Great Britain.

    Figure 2 shows the main advantage of network RTK as compared to traditional RTK. The individual reference stations on the left suffer from the spatial decorrelation of errors as distance between reference and rover receivers increases. Adequate vehicle positioning would require individually operating reference stations to be placed approximately 20–30 kilometers apart. However, a CORS network can be used to develop a model of differential corrections, as shown at right, from which a rover receiver can interpret RTK correction information and use this during the computation of its position. The geometry of a CORS network allows two adjacent reference stations to be located up to 80–100 kilometers apart without degrading the accuracy, although in practice most systems tend to locate them closer together than this. This is essentially a reduction from 30 reference stations per 10,000km² for conventional RTK, to 5–10 reference stations for network RTK, delivering high-precision services to virtually unlimited users.

    Figure 2  The improved navigation performance from RTK (left) to network RTK (right).
    Figure 2. The improved navigation performance from RTK (left) to network RTK (right).

    It is expected that the CORS networks will become a critical part of a country’s spatial infrastructure, and countries like the UK are leading the way. This makes network RTK one of the most promising positioning technologies for road vehicles and ITS applications.

    As shown in previous research, network RTK can deliver a vehicle positioning accuracy of better than 5 centimeters, and in real-world tests this level of accuracy had an availability of 41–45 percent, depending on the environment. It was also found that the correction information was available via the GSM network for more than 80 percent of the time. In these same tests, the total time without any GNSS position solution (network RTK, DGNSS, or stand-alone) was up to 16 percent in a motorway environment. Network RTK was able to provide lane-level positioning accuracy, but the sensitivity of the technique to GNSS signal loss and coverage of the communication network had a significant effect on availability. GNSS outages could be caused simply by passing under a road bridge, and the network RTK solution would be lost, although there would continue to be a DGNSS solution for a short period. Finding effective solutions to these current barriers, which prevent wide adoption of network RTK, is a key enabling step for ITS.

    Accuracy Assessment

    In much more controlled tests to assess the accuracy of network RTK on a dynamic vehicle, the network RTK GNSS receiver was compared to an inertial navigation system (INS). This test was carried out using the NGI roof laboratory, which houses a 120-meter rail track running an electric locomotive.

    Both the network RTK receiver and the INS used the same antenna, fed separately through a signal splitter. The network RTK solution was recorded in real time onto an SD card in NMEA GGA format. The INS data was recorded and post-processed in a tightly coupled solution using a continuously operating dual-frequency GNSS receiver base station located inside the rail track circuit. There were no recorded GNSS outages as there is a clear-sky view from the roof laboratory.

    The antenna point was also tracked using a total station, recording observations at 10 Hz stamped with GPS time. Although the accuracy of the tracking mode of the total station is not high enough to assess the accuracy of the network RTK solution (because of time synchronization issues), it ensures that any gross errors in GNSS observations that could affect both the network RTK and INS solutions did not occur.

    The results in Table 1 show that the network RTK solution consistently performs to a high accuracy, giving a low standard deviation from the mean in all directions. Listed are three laps of the rail circuit recorded at different times. There are a small number of epochs that encounter large differences of more than 200 millimeters, such as during laps 2 and 3, although these appear to be very short-term anomalies, possibly caused by dynamic GNSS signal multipath or delays and message loss in the communication system.

    TABLE 1.  Comparison of the tightly coupled (GPS+IMU) solution with the N-RTK solution.
    Table 1. Comparison of the tightly coupled (GPS+IMU) solution with the N-RTK solution.

    The worst absolute accuracy is shown during lap 3, although even in this case, with a mean of 21 millimeters and 99 percent of the observations lying within 15 millimeters, this solution still delivers a solution within 36 millimeters of the ground truth. 50 percent of the network RTK observations are within 1 millimeter of the mean difference between the two solutions, showing remarkable consistency and precision.

    Challenge: Comm Signal Strength

    A fundamental aspect of network RTK is the delivery of reference station data used in the processing of the receiver’s position. Although there are various methods used to deliver this data, the most secure and reliable method involves transmitting raw reference station observations, so that the receiver may perform the calculation of the position with all possible data. This provides the highest integrity. The vulnerability here is not the algorithmic method used to transmit the data, but the communication system, in three ways:

    • There is no connection between reference and rover receivers.
    • There is data loss from the connection.
    • There is an unacceptable delay in the transmission of the data.

    Lack of Coverage. The preferable communication system is to use mobile Internet over the GSM/GPRS cell network, which is already well established. The major network operators claim over 99 percent coverage of the population in the UK, but this does not take into account physical and local conditions such as land and building obstructions, atmospheric conditions, and inter-ference from vegetation and other
    radio signals.

    A 2011 BBC survey in the UK found that when users had a cell-phone data connection it was 3G for 75 percent of the time (2G otherwise), but significant “notspots” include major rail and road networks. An ongoing study by OpenSignalMaps has found that a 3G service is only available 58 percent of the time. A 2011 government report detailed the extent of 2G and 3G services, shown in Figure 3. Areas with poor data communication coverage (below 50 percent) pose a significant problem for network RTK in vehicles.

    Figure 3 2G (left) and 3G (right) coverage by geographic area in the UK: green, >90 percent; yellow, 70–90 percent; blue, 50–70 percent; purple, 25–50 percent; red, <25 percent.
    Figure 3. 2G (left) and 3G (right) coverage by geographic area in the UK: green, >90 percent; yellow, 70–90 percent; blue, 50–70 percent; purple, 25–50 percent; red,

    Data Loss. Continuity tests show that when using GSM/GPRS mobile communications to transfer the network  RTK corrections, the availability was approximately 88 percent, and the connection could be lost after a few hours of continuous use. This can be caused either by SIM cards that use dynamic IP addresses, creating interruptions when renewing the addresses, or where voice data was prioritized on the network. Other research has shown that a typical mobile Internet connection (a combination of wired public Internet and GPRS) suffers from approximately 20 percent data loss.

    Message Delay. A network RTK receiver  imposes a transmission time limit on the correction messages that are used to fix the common integer ambiguity (in this case, the Leica GS10 limit is 10 seconds), although messages younger than 60 seconds can be used to give an accurate DGNSS solution. Messages older than 60 seconds result in the receiver only being able to output a standalone position, by which time the accuracy will decay beyond vehicle positioning requirements. Earlier research found the typical mobile Internet connection suffers from an average delay of 0.85 seconds.

    Challenge: GNSS Outages

    The majority of the transport infrastructure is outside and has a clear view of the sky, particularly away from heavily urbanised areas. However, the receiver gets no warning of impending signal obstruction, so that even momentary obstructions such as an overhead gantry on the motorway can cause significant loss of positioning accuracy, and often causes a receiver to output no solution at all, as shown in Figure 4. Here the vehicle is traveling in a northern direction in lane 1 of the left-hand carriageway and passes underneath a series of bridges at a motorway junction. This causes both GNSS outages and deteriorated positional accuracy, so much so that the vehicle is positioned in the southern carriageway (note that the underlying map image is of unknown accuracy).

    Figure 4  The typical effect of overhead obstructions on vehicle GNSS positioning.
    Figure 4. The typical effect of overhead obstructions on vehicle GNSS positioning.

    GNSS outages can occur in several ways: the obstruction of the GNSS signals can lead to a loss of signal lock; a momentary obstruction or partial obstruction can cause cycle slips to occur (during carrier-phase positioning); if the visible satellites at the rover receiver are not the same as at the reference receiver, then the ambiguity cannot be resolved; there may be intentional or unintentional signal jamming or interference; and if the receiver assessed the integrity or accuracy to be poor then it may not provide a solution.

    NGI test vehicle.
    NGI test vehicle.

    Experiment Set-Up

    The test vehicle was equipped with a GNSS receiver and antenna, receiving real-time corrections using a GSM/GPRS connection. The signal strength was measured simultaneously using the Android application RF Signal Tracker on an Android-based mobile phone.

    The data recorded includes: GNSS raw data, RINEX format; network RTK real time output, NMEA format; GSM signal strength, CSV format. As the experiments were not intended for the analysis of the accuracy of the GNSS receiver, there was no need to utilize the ground truth system onboard the NGI test vehicle.

    RF SIGNAL TRACKER Android application and mobile phone used to record the GSM signal strength (left), and GNSS receiver (right).
    RF SIGNAL TRACKER. Android application and mobile phone used to record the GSM signal strength (left), and GNSS receiver (right).

    Test Environment. Two test scenarios were chosen for the experiments. To assess the GNSS signal outages, the test vehicle was driven along the M1 motorway, a length of approximately 100 kilometers. The M1 is a major road transport artery linking London in the South to Leeds in the North of England, typically with three or four lanes in each direction. This route passes under 214 overhead obstructions (northbound and southbound directions), of known classification (gantry, footbridge, road bridge). This scenario was chosen as the environment is quite rigid, allowing repeatable tests, and it is the area in which future ITS technology is most likely to be adopted first.

    To test the variation of GSM signal strength in real-world conditions, a small circuit was chosen close to the Nottingham Geospatial Institute (shown in Figure 5), which incorporates a variety of environments from open sky to bridge underpasses, and dense tree coverage. Using a repeatable path allows the identification of issues that are attributable to problems with the communications link as opposed to other issues (such as hardware problems and GNSS signal outages), and despite the short distance, the loop also provides a wide range of GSM signal strengths. During the experiments to follow, the data was measured during three consecutive laps of the circuit.

    Experiment Results

    GSM Signal Strength. The variation in color along the NGI test route is an indication of the RSSI (Received Signal Strength Indicator). In this area, the RSSI varies between –50 dBm and –105 dBm, which are the typical maximum and minimum strengths of a cellular network. This is despite the assessment from the network provider that this entire area delivers high-speed Internet and email. Figure 5 also shows the subjective rating and expected performance of the RSSI.

    Figure 5  The GSM signal strength around the NGI circuit in Nottingham, with the subjective RSSI ratings.
    Figure 5. The GSM signal strength around the NGI circuit in Nottingham, with the subjective RSSI ratings.

    Table2
    Table 2. The spread of RSSI observations recorded during the trials around the NGI circuit.

    Table 2 details the RSSI observations measured during the signal strength trials around the NGI circuit. The range of values shows the typical maximum and minimum RSSI values experienced by a cell-phone user (other than no signal being received). The signal strength is recorded every 5 meters, in order to achieve a good geographic spread across the area (as opposed to biasing the results with observations recorded whilst the vehicle is stationary). The RSSI observations do not correspond to a typical Gaussian distribution, suggesting that there are external influences on the strength of the signal and the handover between one cell tower and the next.

    Figure 6 shows an increase in the age of correction (AoC) of the messages following a drop in signal strength (RSSI) to approximately –100 dBm. This is visible from the peaks in the age of correction message to over 8 seconds. The graph shows three laps of the NGI circuit, noticeable by the repeated pattern of signal strength. The increase in the AoC occurs at approximately the same geographic location on each lap ­— an area in the northwest of the circuit that suffers from weak signal strength, as seen in Figure 5. The received signal strength is the sum of the direct and indirect (or reflected) waves, varying with distance between a series of maximum and minimum values. On a moving vehicle, the RSSI will vary with time as it moves between these maximum and minimum values, and is especially complicated in urban areas where there may be no direct waves at all, and waves are propagated by a series of reflections. A moving receiver also suffers from a Doppler shift in the received signal’s frequency.

    figure 6  The effect of GSM RSSI on the age of correction messages.
    Figure 6. The effect of GSM RSSI on the age of correction messages.

    During network RTK positioning, the receiver considers messages older than 10 seconds unusable for a fixed network  RTK solution, although messages younger than 60 seconds can be used to give an accurate DGNSS solution. This scenario has a brief occasion during the loop in which loss of the network RTK solution is attributable to weak GSM signal strength.

    A close inspection of Figure 6 highlights a slight delay between the drop in RSSI to –100 dBm and the increase in the AoC. This delay needs further analysis, but is assumed to relate to the slower update rate of the ionospheric and tropospheric corrections (10 seconds and 60 seconds respectively). There are also periods of increased AoC that are uncorrelated with a drop in RSSI, for which there is no clear explanation, although none of these occasions results in a loss of the fixed ambiguity network RTK solution.

    Eighty cell handovers were recorded during the trials, which is higher than average as this area is liable to carry a large volume of cellular traffic (there is a university, a large hospital, and major roads, as well as general housing and business properties). The cell handovers showed an average improvement of +1.2 dBm from just before the handover until just after. The maximum improvement is +22 dBM, although there are occasions when the RSSI gets worse, the biggest fall in received signal strength being –12 dBM. Figure 7 displays the frequency distribution of the change in RSSI during a cell handover. The resolution of the RSSI measurements is 2 dBm.

    figure 7  Frequency histogram of the RSSI change during a cell handover (2 dBm bins).
    Figure 7. Frequency histogram of the RSSI change during a cell handover (2 dBm bins).

    Cell handovers occur at a range of RSSI, not just low signal strength. This suggests that cell handovers are managed by the network operator in a way that does not disrupt the data connection. There appears to be no correlation between a cell handover and a problem with the correction message delivery.
    Although this part of the experiment was not a test of receiver performance, during the NGI circuit trial 63.1 percent of the receiver observations were network RTK fixed, and 33.0 percent of the observations were DGNSS observations. Therefore, 3.9 percent of the possible epochs had no observations, partly due to passing under bridges. The largest GNSS outage during circuit trials was 4.85 seconds. These values show an improvement over previous research, particularly as this is considered a difficult GNSS positioning environment.

    GNSS Outages. During the GNSS outages tests, the vehicle traveled at a constant speed of 60 mph, mostly in lane 1 of the motorway. Table 3 shows statistical breakdown of the GNSS outages and the resulting reacquisition of the fixed ambiguity in network RTK positioning.

    Table3
    Table 3. Statistical breakdown of GNSS outages caused by overhead objects.

    The longest total GNSS outage caused by an overhead obstruction was 4.65 seconds, when passing under a road bridge. At 60 mph this translates into a distance of almost 130 meters without any GNSS solution, which is much further than the width of the overhead object. Once the GNSS signal is reacquired, there is a short period during which the fixed integer ambiguity is resolved, in order to achieve the centimeter-level accuracy. The longest duration between start of a GNSS outage and reacquisition of the fixed ambiguity for the network  RTK solution is 52.10 seconds, or 1,450 meters. Although during this period, a DGNSS solution is available as soon as the satellites are reacquired.

    Discussion

    Nationwide adoption of cellular Internet services by cell phone users has provided a useful communication system for positioning systems. But network providers do not guarantee the type of communication service demanded by advanced ITS and V2X applications. The quality of service is too easily disrupted by passing into an area with weak signal strength, or when many users congest the bandwidth.

    Future generations of cell networks, such as 4G, will significantly increase the available bandwidth and increase download speeds, but there is an unknown increase in the demand on the system from non-critical cell-phone users. The issues in the existing system can be minimized slightly through improvements at the user end, such as using stronger gain antennae or accessing multiple networks with different SIM registrations. The nature of cell networks also leads to a decrease in signal strength occurring prior to the cell handover, which can cause delays in the message delivery, so the management of this process could be improved. Future testing of the GSM network can be carried out at the new innovITS ADVANCE test facility at MIRA in the UK, where the private network can be controlled and manipulated as desired.

    An alternative communication method, that has the same wide area coverage of a cell network, is satellite communication. In tests, observation of static positions showed 98 percent of messages were received correctly at a latency of less than 10s. This compares with the High-Speed Download Packet Access (HSDPA) cell network figures of 99.8 percent and 1.2s. When in a kinematic mode, the satellite communications fared less well. Testing three separate satellite communication systems, problems were encountered with reacquisition, long latency, and static initialization. At best, 70 percent of correct messages were received, with a latency of 4.2s, although often over 20s.

    Digital Audio Broadcasting (DAB) is capable of being used as a future communication method for network  RTK positioning. Compared to traditional VHF and UHF radio communication, it uses the frequency more efficiently and is more robust to degradation.

    The design of the GNSS receiver used in testing is aimed at delivering a very reliable and highly accurate solution. It was not intended for use on vehicles and in dynamic environments. The receiver deals well with multipath, rejecting low-strength GNSS signals, allowing the resolution of the integer ambiguity. However, this means that in city environments it may provide fewer solutions than a modern smartphone, albeit with a much higher accuracy when it does. Recent research shows it is possible to increase the speed of ambiguity resolution, and customize integrity controls, making the resolution process close to instantaneous in certain circumstances.

    Conclusions

    As cellular communications networks evolve in the UK and other countries, the performance of the network  RTK receiver also improves. We found that once the RSSI drops to approximately –100dBm, the correction messages suffer from either message loss or message delay that causes the receiver to underperform. The performance of the communication link during a cell tower handover has shown that there is no deterioration in the performance linked to the handover, although cell tower handovers generally occur at the limits of a cell tower’s coverage, and hence at low signal strengths.

    The resolution of the fixed integer ambiguity is crucial for the high-accuracy solution available with a network RTK receiver. The resolution is relatively fast, typically within two minutes from a cold start, or fewer than 20 seconds from a hot start. During tests on the M1 motorway, passing under an overhead obstruction caused a maximum total GNSS outage of 4.65 seconds, and a maximum time until the ambiguity was resolved of 52.10 seconds. On average, the GNSS outage was 1.14 seconds with an average re-fix time of 13.13 seconds. Until the ambiguity is resolved, the receiver can continue with a DGNSS solution delivering lane-level accuracy.

    Manufacturers

    NGI’s inertial nav system is an Applanix POS/RS, which consists of a NovAtel OEM4 dual-frequency GPS receiver combined with a navigation-grade Honeywell consumer IMU. The network RTK position was provided by a Leica GS10 receiver and Leica SmartNet correction service over the Vodafone network. Both receivers used a Leica AS10 antenna.


    Scott Stephenson is a Ph.D. student at the Nottingham Geospatial Institute within the University of Nottingham.

    Xiaolin Meng is associate professor, theme leader for positioning and navigation technologies, and MSc course director for GNSST and PNT at the Nottingham Geospatial Institute of the University of Nottingham. 

    Terry Moore is director of the Nottingham Geospatial Institute (NGI) at the University of Nottingham, where he is the professor of satellite navigation and also an associate dean within the Faculty of Engineering.

    Anthony Baxendale is head of Advanced Technologies & Research at MIRA Ltd.

    Tim Edwards is the lead engineer of the Intelligent Transportation Systems (ITS) research group at MIRA Ltd