Industry experts share how GNSS can be used for precision agriculture.
Vazquez
EUROPEAN SATELLITE SERVICES PROVIDER (ESSP)
Juan Vazquez Team Leader, EDAS Service Provision
Pass-to-pass accuracy is the key performance indicator to assess the precision of guidance systems, characterizing the short-term dynamic performance determined from off-track errors along the straight segment passes (error with respect to the desired path in the direction perpendicular to the tractor trajectory).
The results of the tests reported in this article, jointly performed by Topcon Agriculture and ESSP, confirm that EDAS DGPS corrections can support a wide range of precision agriculture applications and represent a real alternative for cereal farms, when located in the vicinity (at least up to 260 km away) of an EGNOS reference station, complementing the benefits that the EGNOS signal-in-space is already providing to a large number of agriculture users in Europe.
EFFIGIS GEO-SOLUTIONS
Nicos Keable-Vézina Director of Precision Agriculture
Thanks to artificial intelligence, variable-rate application of nitrogen has made great strides in recent years. Science has demonstrated that effective nitrogen management requires an array of technologies, including massive databases. Data is geospatial (positioning signal and satellite imagery enabling the identification of changes in nitrogen requirements), agronomic (mainly soil texture and seasonal weather), and economic (grain and nitrogen price).
To automate extraction and analysis of such data, combining very low-cost positioning technologies, satellite imagery and artificial intelligence is paramount. A democratized access to technology has led to the development of scientifically proven nitrogen prescribing platforms, among them FieldApex, that calculate the most profitable nitrogen rates and generate prescriptions in seconds without soil sampling. Further technological and platform integrations are likely to bolster such innovation.
Rioja
TOPCON AGRICULTURE
Julian Rioja Channel Development and Business Intelligence Manager
All tests were performed using Topcon receivers, vehicles and auto-steering systems. Two different Topcon guidance systems on board tractors ran simultaneously to assess the EDAS DGPS positioning performance with respect to the reference provided by a real-time kinematic (RTK) system. Hence, two independent positioning outputs were continuously available (the receivers were placed along the same longitudinal axis on the roof of the tractor):
RTK position: provided by the AGI-4 receiver fed by Topcon’s Hiper V RTK base.
DGPS position: provided by the AGI-4 receiver fed by the EDAS Ntrip service.
On board the tractor, two Topcon X35 consoles were each connected to one of the receivers. A Topcon AES-25 electric steering system was installed on the tractor so that the selected navigation input (RTK or EDAS DGPS) could be used to automatically guide the tractor along the defined reference pattern.
McClure
HEMISPHERE GNSS
John McClure Engineering Manager, Precision Agriculture
Precision agriculture is expanding the use of ISOBUS for CAN communication between a common terminal and implements, to reduce clutter in the cab. These virtual terminals now act as display and user entry for multiple applications including GNSS receivers and factory or after-market steering systems.
INS-aided GNSS solutions, typically using RTK or satellite-based correctors such as Atlas, provide time/position data for rate and section control and auto-steering. CAN-based NMEA 2000 is the commonly used receiver protocol for position data, replacing serial NMEA 0183.
All major tractor, agricultural equipment, and GNSS manufacturers attend regular “Plugfest” meetings, organized by the Agriculture Industry Electronics Foundation, to test interoperability of products and set common standards.
Smart CAN dongles are being developed to read sensors and control systems, supplying positioned data via telematics as the Big Data for real-time and post analysis.
By Juan Vázquez, Elisabet Lacarra, Jorge Morán and Miguel A. Sánchez, ESSP SAS, and Julian Rioja and Jimmy Bruzual, Topcon Agriculture
The European Geostationary Navigation Overlay Service (EGNOS), a satellite-based augmentation system (SBAS), provides corrections and integrity information to GPS signals over Europe and is fully interoperable with other SBAS such as North America’s WAAS. Among its services is the internet-based EGNOS Data Access Service (EDAS).
EDAS gathers raw data from GPS, GLONASS and EGNOS GEO satellites collected by receivers at approximately 40 EGNOS ground stations distributed over Europe and North Africa. EDAS reformats and disseminates GNSS data in real time and through an FTP archive to EDAS users and service providers.
Additionally, EDAS provides differential GNSS corrections to the GPS and GLONASS satellites in view by the EGNOS system network through its Ntrip service.
The tests summarized in this article focused on the EDAS Ntrip Service, which can be used for differential positioning. An earlier test near Seville, Spain, concluded that these corrections could support pass-to-pass accuracies in the order of 20 centimeters in a consistent manner and with a high degree of repeatability.
To assess EDAS performance validity for agriculture applications, two additional tests were done in Lisbon, Portugal, and York, UK. These locations provide diversity with respect to the Seville test, especially in terms of distance from the farm to the selected EGNOS reference station (≈320 km in York and 40 km in Lisbon, versus the 110 km baseline of the test in Seville) and also geographically. In all tests, a real-time kinematic solution operated in parallel to the EDAS DGPS solution to provide the required reference for the post-processing of the recorded data. Nine different runs with a total of 78 passes were performed in these two campaigns.
Considering the results from the three tests, the pass-to-pass accuracy supported by EDAS DGPS corrections was below 10 cm for more than 60% of passes and below 20 cm for more than 85 percent of the passes. These figures exceed the earlier results and confirm that EDAS DGPS corrections can deliver pass-to-pass accuracies in the order of 10 to 20 cm in a consistent manner.
Cumulative distribution of P2P accuracy, in centimeters. (Chart: Topcon)
The stability of the results and the very good pass-to-pass accuracy levels observed in the York scenario, where baselines larger than 300 km were tested, deserve highlighting. For grain and dry soil cultivation, at least 1 meter (95th percentile) of absolute horizontal accuracy is required. It can be assumed that, within the area where EDAS DGPS supports sub-meter horizontal accuracies (up to 260 km from the selected EGNOS station, according to previous studies), EDAS DGPS corrections can also support pass-to-pass accuracies in the order of 10-20 cm.
Such performance levels are considered to be appropriate for most grain farm operations. In particular, the observed performance is sufficient to support the following precision agriculture applications:
By William Roberts, Joshua Critchley-Marrows, Marco Fortunato, Maria Ivanovici, Nottingham scientific Ltd., Karel Callewaert, Thiago Tavares, VVA Brussels, Laurent Arzel and Axelle Pomies, Telespazio France
The FLAMINGO initiative is developing the infrastructure, solutions and services to enable use of accurate, precise GNSS in the mass-market, operating predominantly in an urban environment. Whilst mass-market receivers are yet to achieve accuracies below one meter for standard positioning, the introduction of Android raw GNSS measurements and the Broadcom dual frequency chipset present such an opportunity.
FLAMINGO will enable high-accuracy positioning and navigation information on devices such as smartphones and internet of things (IoT) devices by producing a service delivering accuracies of 50 cm (at 95 percent) and better, employing multi-constellation, PPP and RTK mechanisms, power consumption optimisation techniques.
Whereas the Galileo High Accuracy Service targets 10-cm precision for professional users, FLAMINGO targets 50-cm precision for consumers. With accuracies of a few decimetres, a range of improved and new applications in diverse market sectors are introduced, including, but are not limited to, mapping and GIS, autonomous vehicles, augmented reality environments, location-based gaming and people tracking.
To obtain such high accuracies with mass market devices, FLAMINGO must overcome several challenges which are technical, operational and environmental. This includes the hardware capabilities of most mass-market devices, where components such as antennas and processors are prioritised for other purposes. We demonstrate that, despite these challenges, FLAMINGO has the potential to meet the accuracy required. Tests with the current smartphones that provide access to multi-constellation raw measurements (the dual-frequency Xiaomi Mi 8 and single-frequency Samsung S8 and Huawei P10) demonstrate significant improvements to the PVT solution when processing using both RTK and PPP techniques. Check out more information here.
By Alexander Rügamer, Daniel Rubino, Xabier Zubizarreta, Wolfgang Felber, Fraunhofer IIS, and Jan Wendel and Daniel Pfaffelhuber, Airbus Defense and Space GmbH
This work presents a new secure localization method that can be used for UAVs to obtain a new level of protection against hostile and unauthorized UAVs. While non-spreading code-encrypted (SCE) GNSS devices can be blocked, authorized UAVs using this method have unrestricted access to the non-spoofable and trusted SCE GNSS. The proposed method is to store short sequences of SCE PRN code chips on the user receiver before the mission.
The Precalculate & Process architecture. (Images: Fraunhofer IIS)
These SCE PRN code chips allow the user receiver to calculate at pre-defined points in time a secure and trustable SCE PVT position. Since no communication channel is required, this method mitigates the risk that hostile forces may try to jam the UAV’s radio control. Moreover, radio silence can be realized, which is beneficial or even required for some missions.
No dedicated security module required on the user terminal, no SWaP problems, no keying issues, no handling of controlled items on user side, no need for a communication link giving rise to the availability and radio silence issues, and no security issues due to the short SCE PRN code chip sequences valid only for the limited mission duration and inside a limited area.
Potential target markets for this method are police and special forces and other authorized users which are allowed to use certain SCE GNSS and would like to equip their UAVs with a secure, unspoofable positioning solution. Check out more information here.
Orthometric height support (survey-grade elevations) enables Arrow GNSS receivers to collect high-accuracy, survey-grade vertical data with any data-collection software.
Eos Positioning Systems Inc. has added support for GEOID height models within its Arrow Series GNSS receivers. Eos manufactures high-accuracy GNSS receivers for any app running on iOS/Android/Windows devices and using the Eos Arrow Series.
“You can use Arrow Series receivers with any data-collection software in the world, and benefit from accurate orthometric heights,” Eos CTO Jean-Yves Lauture said. “Our Arrow receivers will output accurate GNSS elevations no matter which data-collection software you use to capture it.”
Image: Eos Positioning
With support for GEOID models, Arrow receivers automatically output survey-grade elevations to all iOS and Android data collection software. Support will also soon be available for Windows devices.
The Arrow receivers now support the entire United States to provide survey-grade elevation in NAVD88 orthometric heights through the GEOID12B (US) model. The Arrow receivers also support the Canadian CGG2013a and HTv2.0 GEOID models for the CGVD2013 and CGVD28 vertical datums, respectively. Additional GEOID models for other countries are planned.
“Eos is intensely focused on supporting high-accuracy GIS, engineering, surveying and construction users by supporting the latest GEOID elevation models within our GNSS monitoring software,” Lauture said. “Our roadmap remains focused on high-accuracy BYOD users by supporting all iOS, Android and Windows users with this capability.”
The problem is that typical Bluetooth GNSS receivers usually provide inaccurate, built-in elevation models. This inaccuracy is reflected in the Mean Sea Level elevation output by those receivers. By outputting orthometric height, the Arrow now solves this problem and turns any smartphone or tablet into a 3D, survey-grade accurate data collection device, the company said.
Eos has designed this new feature so that users will easily be able to update to new GEOID models as they become available.
Field technicians in pipeline, construction, engineering, architecture, water and any other industry are finally able to enjoy GNSS location with survey-grade vertical accuracy on their iOS and Android devices, with the data-collection app of their choice and their Eos Arrow receivers.
Includes first draft of best practices for implementing GIS in elections.
Photo: iStock.com/YinYang
The National States Geographic Information Council (NSGIC) has released the first-year report of phase one of its Geo-Enabled Elections project, highlighting the project’s accomplishments in the first 12 months. These include completing a baseline assessment of how far states have come, to date, in terms of integrating geographic information systems (GIS) with electoral systems, as well as assembling a team of leaders and experts to help guide the project.
The project team has also facilitated conversations with a wide range of stakeholder groups, aimed at raising awareness of the importance of using geospatial technology to increase reliability and accuracy in elections.
The Geo-Enabled Elections project, phase one, runs from Oct. 1, 2017, to Sept. 30, 2019, with the aim to help strengthen electoral systems by supporting states in the adoption of GIS. Concretely, this means encouraging state governments to replace non-spatial “address file” systems with election precinct and voter data in a GIS format, leveraging that format’s inherent visual and analytical advantages.
The Geo-Enabled Elections project is partly funded by the bipartisan Democracy Fund Voice.
“During this first year, we’ve been encouraged to learn that while most voter data across the country is still kept in ‘address file’ tables, many state election directors are interested in the benefits that GIS can bring. Additionally, since most state governments have a geographic information officer (GIO) or equivalent on staff, the prospects for strengthening elections through the integration of GIS into electoral systems are very good,” said Dan Ross, NSGIC president and GIO for the State of Minnesota.
As part of the Geo-Enabled Elections project, NSGIC has been able to help build stronger connections between state officials responsible for the electoral system and state-level GIS subject matter experts, a critical first step towards the successful implementation of GIS in elections.
The organization, which is quickly becoming recognized as the center of expertise for how GIS can be deployed to strengthen electoral systems, also released the first draft of its best practices for how states may go about enhancing election accuracy using GIS. The five identified best practices are:
Convene a team of specialists
Collect and sustain a statewide voting unit GIS layer
Adopt and implement a statewide geocoding strategy
Assemble and provide best Available contextual GIS layers
Define and implement data validation processes
These draft best practices will be put to the test and further refined in five state-wide pilot studies taking place during the project’s second year. The best practices can be viewed in full as part of the first-year report.
NSGIC’s report also outlines the work that lies ahead for the project, as well as opportunities to impact geo-enabled elections in phase two of the project (pending funding).
Mountainous areas present special problems for surveyors, overcome by the expanded availability of multi-GNSS. (Photo: Trimble)
Today’s GNSS satellites transmit on three or more carrier frequencies. The quality of the data in these signals from GPS, BeiDou, Galileo, GLONASS and QZSS reveals the expected measurement precisions. This article explores the noise of the range residual and ionospheric residual to indicate the oncoming capabilities.
Today, four GNSSs transmit various codes on various carrier frequencies: the USA’s GPS, Russia’s GLONASS, Europe’s Galileo and China’s BeiDou. Most of the carrier phase and pseudorange data are available using civilian GNSS receivers. Improvements in signal quality as well as reliability of the satellites are foreseen through the generations, as well as the introduction of new signals, such as L1C, L2C, L5 carrier and codes, and M-codes, on top of the existing L1-C/A code and the P(Y) code on both L1 and L2. Improvements are also seen in boosting the transmitting power.
This article investigates the use of two approaches to analyze the relative noise in the various carrier phase and pseudorange observable for GPS, BeiDou, Galileo, GLONASS and Japan’s Quasi-Zenith Satellite System (QZSS) augmentation. Two approaches analyze the relative noise in the observables: the range residual and the ionospheric residual. Both techniques can also be used to detect cycle slips.
Range Residual
UAV survey operations benefit from multi-GNSS receivers. (Photo: Septentrio)
The range residual is simply the change from one epoch to the next in the difference in the range calculated using the pseudorange and the range calculated by the carrier phase on a specific frequency. The pseudorange values are scaled using the wavelength to an equivalent range in units of the carrier’s cycles rather than meters. Equation 1 illustrates the range residual between the pseudorange ρ on a specific carrier frequency and the carrier phase observable φ, using the wavelength λ of the carrier to scale the pseudorange. The values of these observables are compared between adjacent epochs.
RR = (p/λ) – φ (1)
Two adjacent epochs are used, as then the integer ambiguity value, as well as the ionospheric and tropospheric errors, and satellite and receiver clock errors are the same, or negligibly different at such small (<1 s) epoch intervals. Therefore, these are all canceled out, and the resulting value is the measurement receiver and observable noise. The pseudorange observable will be significantly noisier than the carrier phase observable, therefore this method is a good way to calculate the measurement noise for the pseudoranges.
Ionospheric Residual
Surveyors work the Berezitovy mine in the North Amur region of Russia. (Photo: Javad GNSS)
If the carrier waves traveled only through a vacuum, then a phase observation from a specific satellite to a specific GNSS receiver could be scaled and converted to an equivalent phase measurement on another frequency using the frequencies of the carrier waves. However, as the signal passes through the ionosphere, systematic errors that are frequency dependent are introduced, so it is not possible to directly convert from one carrier phase value to another for a specific range measurement. The error is known as the ionospheric residual, and this will change slowly over time as the satellite passes overhead and the ionosphere being passed through changes, and also as the ionosphere slowly changes its characteristics over time, mainly due to the sun’s activities.
Equation 2 shows the calculation, using L1 and L2 carrier phase readings and corresponding frequencies, used to calculate the ionospheric residual. Again, the difference in the ionospheric residual values between adjacent epochs is used, as in the same way as the range residual values, external noise sources are eliminated.
(2)
Results
The results presented here are a subset of a much larger set. Figure 1 illustrates the range residuals for L1 and L2 as well as the L1L2 ionospheric residual for PRN32 (Block IIA satellite).
Figure 1. L1 range residual (left) L2 range residual (center) and L1L2 ionospheric residual (right) for GPS PRN32 (Block IIA) satellite. (Charts: Authors)
Figure 2 illustrates the L1 and L5 range residuals and the L2 (C-code) L5 ionospheric residual for PRN01 (Block IIF satellite).Both figures’ data are for the complete passing of the satellites from horizon over and back down again.The data for PRN32 is all that exists in the datafile, as this satellite only transmits L1 CA code and P(Y) code, as well as L2 P(Y) code, and corresponding carrier values.
Figure 2. L1 range residual (left) L5 range residual (center) and L2 (C code) L5 ionospheric residual (right) for GPS PRN01 (Block IIF) satellite. (Charts: Authors)
PRN01 is a block IIF satellite, and data for L1 CA code, L2 P(Y) code as well as L2 C-code, L5 code, and corresponding carrier phase values are recorded in the datafile.The block IIF satellites can result in four range residual values and five ionospheric residual combinations.Figure 2 only illustrates three of these combinations.The data were obtained from the Curtin University GNSS repository on Sept. 1, 2015, gathered at a 1-Hz epoch interval; 29,908 epoch of data were gathered for PRN32, and 26,073 epochs for PRN01.
It can be seen from these figures that the L1 range residuals are similar in characteristics for both PRN01 and PRN32.The values are noisy at the start and the end of the time series, indicating that the CA code is more prone to noise at low elevations.Comparing these to the L2 (PRN32) and L5 (PRN01) range residuals, we can see that both the L2 and L5 range residuals are not as prone to low elevation noise. Also, the two L2 and L5 range residuals are visually similar in characteristcs.By comparing the L1L2 and L2L5 ionospheric residuals (Figure 1, right, and Figure 2, right), we can see that the L1L2 combination is slightly noisier than the L2L5, in particular at low elevation angles.
If we compare BeiDou ionospheric residual results, we can see the comparison of noise on the three ionospheric residual combinations, B1B2, B1B3 and B2B3, as well as the results from the three types of satellite orbits, ie MEO, IGSO and GEO. Figure 3 illustrates the ionospheric residual results for PRN07 (IGSO) for the three frequency combinations, from data gathered on a static pillar located on top of the University of Nottingham Ningbo China’s Science and Engineering Building.
Figure 3. Ionospheric residual results for BeiDou PRN07 (IGSO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Chart: Authors)
Figure 4 illustrates the ionospheric residual results for PRN01 (GEO) for the three frequency combinations.
Figure 4. Ionospheric residual results for BeiDou PRN01 (GEO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Chart: Authors)
Figure 5 illustrates the ionospheric residual results for PRN12 (MEO) for the three frequency combinations. Here it can be seen that the B2B3 combination is generally less noisy than the B1B2 and B1B3. In addition to this, it can be seen that when the MEO and IGSO satellites are at lower elevation angles, the observables also become noisier. The GEO satellites have a constant elevation angle, and do not experience this phenomenon.
Figure 5. Ionospheric residual results for BeiDou PRN12 (MEO) for combinations B1B2 (left), B1B3 (center), B2B3 (right). (Charts: Authors)
Detailed Results
The data, gathered on a single GNSS receiver located at the University of Curtin’s GNSS research center, was downloaded in BINEX format and converted into RINEX 3.02 format using RTKLIB software. Software was developed by the authors in Matlab in order to interrogate the data files and implement the range residual and ionospheric residual algorithms. RINEX 3.02 format was chosen due to its compatibility with multi-GNSS and multi-frequencies.
Industrial UAV applications such as construction draw benefits from multi-GNSS receivers’ capabilities. (Photo: Skycatch, Swift Navigation)
Results are presented for both ionospheric residual and range residual results for various GNSS. These results have been calculated with varying elevation mask angles, ranging from 0° to 55° at 5° intervals. The RMS values of the resulting ionospheric residuals and range residuals were calculated and plotted against the respective elevation mask angle for each satellite and frequency combinations. This illustrates the influence of the elevation mask angle used on the results.
Typically, tens of thousands of epochs of data were used for every plotted point in the following figures. Further to this, not only are the results for the various frequencies and frequency combinations for the various GNSS illustrated, but also the various satellite types, MEO, GEO and IGSO, and various satellite Blocks for GNSS. GPS Block IIA (PRN04 and PRN32), Block IIR (PRN14), Block IIR-M (PRN31) and Block IIF (PRN01, PRN26, PRN25) data were all analyzed. Thus, the comparison of the various frequencies within each satellite system are illustrated, as well as the variations by comparing the various satellite constellation types and the various generations of GPS satellites.
Surveying accuracy is critical to roadway construction. (Photo: Leica Geosystems)
The BeiDou data illustrated are MEO (C12, C14, C11), IGSO (C09, C10, C07) and GEO (C01, C02). The data used were gathered on Sept. 1, 2015, in order to include GPS Block IIA satellites (PRN04 and PRN32). PRN32 was retired in June 2016, and PRN04 was taken out of active service in November 2015, but the satellite was reactivated in March 2018, this time broadcasting PRN18.
Figure 6 illustrates RMS of the range residual results for GPS (a), BeiDou (b), Galileo (c), GLONASS (d) and QZSS (e) respectively. These figures have been drawn so that the y-axis ranges are the same for each, hence illustrating the relative values.
Figure 6A illustrates the range residual results for GPS. It can be seen that the L1 CA code results are the noisiest, with PRN14 being the noisiest, followed by PRN31, PRN26, PRN01, PRN04, PRN25 and PRN32. It can also be seen with these results that lower elevation angle mask increases the noise level. Both the L2 and L5 code results are less noisy.
Figure 6A. RMS range residual results for GPS. (Chart: Authors)
Looking at the detail, the L5 code results is less noisy than the L2 and affected less than the L1 results by the changes in elevation mask angles used. Interestingly enough, the data file includes both the L2 P(Y) code and L2C code results. L2C only exists on the Block IIR-M and Block IIF satellites. The L2C code results are generally noisier than the L2 P(Y) code.
Figure 6B illustrates the results for the range residuals for the BeiDou satellites. Here it can be seen that the B1 code is affected more by low elevation mask angles than B2 and B3. It can also be seen that both the geostationary satellites’ B1 results stand out, with satellite C02 being noisier than C01. The B2 and B3 values for both these GEO satellites are bunched up with the majority of the other results towards the middle of the figure. The pairs of B2 and B3 results for the GEO satellites are close to each other in values, and the pairs of B2 and B3 results for the other satellites are also close to each other.
Figure 6B. RMS range residual results for BeiDou. (Chart: Authors)
It can also be seen that the range residual results for BeiDou are generally less noisy than than GPS, in units of cycles.
Similarly, for Galileo, Figure 6C, the E1 results are worst, and affected more by low elevation masks. Again, generally the Galileo results are seen to be improved over GPS. The GLONASS results, Figure 6D, illustrate that the L1C results are generally noisier, and then the L1P, followed by L2C and L2P. PRN09 is also consistently generally noisier than PRN10. Finally, Figure 6E illustrates the results for QZSS. Again, L1C is the noisiest and affected most by low elevation mask angles.
Figure 6C. RMS range residual results for Galileo. (Chart: Authors)Figure 6D. RMS range residual results for GLONASS. (Chart: Authors)Figure 6E. RMS range residual results for QZSS. (Chart: Authors)
Figure 7 illustrates the ionspheric residual results for the same satellites as Figure 6. This time, however, the resulting ionospheric residual values are calculated using pairs of data from the same satellite on different carrier frequencies. The range residual results compare the code and carrier from specific satellites and frequencies.
Figure 7(a) shows that the ionospheric residual results are affected by low elevation masks, and that the L1L2CW (L1 CA code and L2 P(Y) code available on all the satellites) combinations are the noisiest, followed by L2L5WX (L2 P(Y) code and L5 code available on Block IIF satellites, PRN 26, PRN01, PRN25), followed by L1L2CX (L1 CA code and L2 C code available on Block IIF and Block IIR-M satellites, PRN31, PRN26, PRN01 and PRN25), followed by L1L5CX (L1 CA code and L5 code, Block IIF satellites, PRN01, PRN25, PRN26) and finally the least noisy were the L2L5XX results (L2 C code and L5 code available on Block IIF satellites, PRN26, PRN25 and PRN01).
Figure 7A. Ionospheric residual results for GPS. (Chart: Authors)
Figure 7(b) illustrates the BeiDou ionospheric residual plots, illustrating that satellite C14 is much noisier for all three combinations of B1B3, BB1B2 and B2B3 in that order. The B1B2 combinations for the satellites are generally the noisiest, and then the B1B3 and B2B3 combinations are intertwined. The Galileo results again illustrate that the E1 combinations are generally noisier, and again we see the effect of low elevation angle masks, Figure 7(c). Generally, however, the Galileo results are less noisy than GPS, as are the BeiDou results.
Figure 7B. Ionospheric residual results for BeiDou. (Chart: Authors)Figure 7C. Ionospheric residual results for Galileo. (Chart: Authors)
The GLONASS results are again generally the noisiest, and again PRN09 is noisier than PRN10, with the L1P combinations being noisier, Figure 7(d). Figure 7(e) for QZSS shows that there are generally two groups of results. The upper set consists of L1L2ZX, L1L5ZX, L1L2XX, L1L5XX, L1L6ZX and L1L6XX from highest to lowest noise respectively. The lower, less noisy, group consists of L1L2CX, L1L5CX, L2L5XX, L2L6XX, L1L6CX and L5L6XX from highest to lowest noise respectively. Further details about the various codes and carrier values can be found in the RINEX 3.02 manual produced by the IGS.
Figure 7D. Ionospheric residual results for GLONASS. (Chart: Authors)Figure 7E. Ionospheric residual results for QZSS.(Chart: Authors)
Conclusions
A surveyor checks an urban construction project. (Photo: Topcon)
These preliminary results illustrate that there are differences in the noise values for various GNSS, frequencies as well as satellite generations and orbit types. It can be seen that generally L1, B1 and E1 have noisier results, and are affected moreso by low elevation mask data, and hence multipath. It can also be seen that newer generations of satellites do indeed produce better quality data.
Some specific satellites produce lower quality data such as GLONASS PRN09 and BeiDou C14. This could be due to multipath produced at the satellite.
Today roughly 100 GNSS transmit data, and typically users can gather data from 30 to 50 at any time. Positioning requires nowhere near this number of satellites, therefore decisions are needed as to which satellites and which data to use in a positioning solution. Our findings imply that our approach could be used in such decision-making in GNSS processing software, helping the software to choose the optimum satellites to draw from in a positioning solution.
Acknowledgments
This work described in this article was first presented at the FIG 2018 conference held in Istanbul, Turkey. The authors acknowledge the use of data supplied from the Curtin University GNSS Centre.
Manufacturers
The GNSS receiver used is a Trimble NET R9, and the antenna is a Trimble TRM 59800.00 SCIS choke ring antenna. A ComNav K508 GNSS receiver supplied some of the BeiDou results.
GETHIN WYN ROBERTS is an associate professor at Fróðskaparsetur, the University of the Faroe Islands. He is past Chairman of the FIG’s Commission 6, Engineering Surveys, and previously held posts at the University of Nottingham both in the UK and in China. He holds a Ph.D. in engineering surveying and geodesy from the University of Nottingham.
CRAIG M. HANCOCK is an associate professor in Geodesy and Surveying Engineering and the head of the Department of Civil Engineering at the University of Nottingham, Ningbo, China as well as the head of the Geospatial and Geohazards Research Group. He holds a PhD from the University of Newcastle Upon Tyne.
XU TANG is a research fellow at the University of Nottingham, Ningbo, China. He holds a PhD from Nanjing University.
A new interactive app by Esri models the cumulative number of climate hazards likely to occur under different emissions scenarios for any place on Earth through 2100. The app visualizes the index of 11 hazards, including warming, drought, heatwaves, fires, precipitation, floods, storms, water scarcity, sea-level rise, and changes in natural land cover and ocean chemistry. Users can see how severely locations around the world will be affected by these cumulative hazards under different global mitigation scenarios.
Esri created the app in partnership with the University of Hawaii’s Camilo Mora, lead author of a study in Nature Climate Change, which provides a comprehensive assessment of the simultaneous occurrence of multiple climate hazards strengthened by increasing greenhouse gas emissions and their effect on humanity. Mora’s analysis of thousands of peer reviewed scientific papers reveals 467 ways in which human health, food, water, economy, infrastructure and security have been impacted by multiple climatic changes.
By clearly visualizing the threats that our world’s ecosystem faces at every level, the maps and data hammer home how location intelligence can help with understanding what is at stake in making decisions, even at a global scale. Visualize the data here.
CityMapper is a hybrid airborne sensor combining vertical and oblique imagery with 3D laser scanning designed for 3D city modeling and urban mapping.
Using the CityMapper, Bluesky was able to capture parts of London, Manchester and Birmingham as well as Brighton, Bristol, Cambridge, Norwich, Nottingham and Oxford. Bluesky intends to increase its coverage by capturing additional towns and cities across the U.K. and Ireland in 2019.
St. Paul’s Cathedral in London captured in lidar point-cloud data. (Image: Bluesky)
According to Bluesky, this is the first time the technology has been used commercially in the UK to this level. The captured city data is available from Bluesky and Leica Geosystems, part of Hexagon, in its constituent components of vertical orthorectified aerial imagery, oblique photographs and lidar point cloud data. Plans are in place to also include the imagery in the HxGN Content Program.
The combination of multiple survey-grade cameras and lidar enables the simultaneous capture of data for the automatic creation of highly accurate and detailed citywide 3D models, with one sensor, according to Bluesky.
Previous 3D models have either been prohibitively expensive for use across larger areas or of insufficient detail or accuracy. The CityMapper sensor enabled efficient, cost-effective capture of highly detailed and accurate data, and could make possible widespread use of 3D models possible.
The CityMapper sensor is designed for 3D city modeling and urban mapping. (Photo: Leica Geosystems)
CityMapper includes a traditional vertical camera as well as survey-grade oblique cameras. The sensor also includes high-performance lidar technology to accurately collect elevation data even into the shadows, which are common in urban environments and make photo-based data collection difficult.
The CityMapper sensor also collects color infrared data, which can be used to aid greenspace mapping and vegetation studies.
Applications of the new Bluesky 3D models are expected to include urban planning, line-of-sight analysis, new development visualizations and environmental modeling, as well as potentially 3D fly throughs and virtual reality experiences. Early adopters of the data include architects, planning consultants and other map publishers.
What is the “sweet spot” for high-precision multi-GNSS receivers, factoring cost, capability and robustness: processing of 2, 3 or 4 GNSS constellation signals?
Miguel Armor
“Users expect an available GNSS position in the most demanding environments, making the combination of all constellations and frequencies the real sweet spot. The benefits of using all constellations and frequencies is very important and will only increase in the future.” Miguel Amor Hexagon Positioning Intelligence
Terry Moore
“Combining frequencies is a way of removing the impact of ionospheric disturbances. Some new GNSS signals such as Galileo E5 are so high-quality that the solution degrades when they are combined with lower quality signals on other frequencies. We must now use other, novel, approaches to remove the ionosphere disturbances.” Terry Moore University of Nottingham
Brad Parkinson
“Four constellations are now virtually free, and incorporated into new, inexpensive GNSS phone chips. A more complex issue is using all frequency bands. Benefits are enormous. With volume, costs will plummet. So, the sweet spot moves to use of all frequencies, particularly L5 and equivalents.” Bradford W. Parkinson
Stanford Center for Position, Navigation and Time
Allystar Technology Co. Ltd., headquartered in Shenzhen, China, has released a multi-band multi-GNSS chipset, the HD9310. The new product is based on the Cynosure III architecture integrating multi-band multi-system GNSS RF and baseband.
A multi-band, multi-system system-on-chip, it supports BeiDou-3 and is capable of tracking all global civil navigation systems (GPS, BeiDou, Galileo, GLONASS, IRNSS, QZSS and SBAS) in all bands (L1, L2, L5, L6), said Simon Sun, Allystar general manager.
Photo: Allystar Technology
Designed for high-precision applications, the HD9310 measures 5.0mm x 5.0mm. The architecture integrates floating-point arithmetic units based on ARM CortexM4, 160 KB RAM, 32KB backup RAM with VBAT, 386 KB embedded FLASH and peripheral interfaces UART, I2C, SPI, GPIO, CAN.
In terms of the manufacturing processes, it adopts a 40nm process and incorporates a variety of advanced design technologies, endowing it with very power consumption: less than 50mA.
The quad-flat no-leads package allows customers to reduce printed circuit board and bill of materials costs while reducing the number of peripheral devices. This chip supports CAN interface and can be widely used in vehicle management, car navigation, wearable devices, GIS data collection, precision agriculture, smart logistics, driverless, engineering survey and other fields.
“The HD9310 supports three options of RF setting — A, B, C — for product developers to quickly bring their ideas to the different application and markets,” added Shi Xian Yang, high precision project manager at Allystar.
Three available options for the HD9310 chipset. Graphic: Allystar Technology
Option A, focused on L5 band, L5/E5, maximizes measurement accuracy and improves multipath mitigation based on higher chip rate.
Option B is focused on L2 band, and suitable for relative position applications, for example, real-time kinematic (RTK), because worldwide continuously operating reference stations (CORS) commonly support L1/L2/L1OF/L2OF.
Option C is focused on the L6 band and is designed for PPP applications, receiving state space representation (SSR)-type corrections to be broadcast from satellites in the coming future, and supporting B3I already.
The HD9310 comes with built-in support for standard RTCM Protocol (MSM), supporting multi-band multi-system high-precision raw data output, including pseudo range, phase range, Doppler, SNR for any kind of 3rd party integration and application.
Module. Allystar Technology also has launched a multi-band multi-GNSS module, TAU1302, which integrates the HD9310 chipset and measures 12 × 16 × 2.3 millimeters.
With the features of small size, low power consumption (<50 mA), and ease of integration and mass production, HD9310 is suitable for high-precision applications such as vehicle management, car navigation, wearable devices, GIS data collection, precision agriculture, smart logistics, driverless, engineering survey and other fields.
Customer samples of the HD9310 chipset are available now.
Yury Urlichich, First Deputy Director General, Roscosmos. (Photo: Roscosmos)
By Yury Urlichich First Deputy Director General, Roscosmos State Space Corporation
The year 2019 will bring GLONASS users many new opportunities. Improving navigation services specifically at the user level, primarily assessed in terms of signal accuracy and availability, is our primary goal. Improving navigation accuracy is based on space system development, including both the orbital constellation (space segment) and ground control segment.
CDMA Signal
A Glonass-K2 spacecraft (SC) launch followed by flight testing will be the most important event in space segment development. This SC will enable navigation not only using legacy FDMA signals available for users for more than 35 years, but simultaneously with a full row of CDMA signals in all GLONASS frequency bands: L1, L2 and L3.
Currently the major navigation error contributors are the radio signal trajectory and the user terminal receiving environment. The new signals will allow lowering the hardware-dependent SC-user ranging error by an order of magnitude, reducing the influence of signal reflections from buildings, constructions and landscape (multipath effect), thus enabling their effective use for high-precision navigation with real-time errors below 0.1 m.
We are also finalizing in 2019 the newest edition of the GLONASS Interface Control Document containing recommended models for evaluation of tropospheric and ionospheric delays. Our forecasts show two times navigation accuracy improvement for users of these models.
High-Orbit GLONASS
Improving signal availability is equally important. As large urban areas demonstrate growing use of navigation technologies, these users experience difficulties receiving signals from SC flying below the elevation angle of 25°. To provide a navigation solution in such environments, we will begin development of High-Orbit GLONASS in 2019.
High-Orbit GLONASS will consist of six SC distributed among the three orbital planes and forming two SC ground traces with 64.8° orbit inclination, eccentricity of 0.072, revolution period of 23.9 hours, geographical longitude of the ascendant angle – 60°, 120° (See figure below).
High-Orbit GLONASS — ground track in red. (Image: Roscosmos)
The new generation space segment will be populated with Glonass-B satellites designed on the proven Glonass-K platform, successfully providing services since 2012. Users will be offered the full spectrum of new CDMA signals in all three GLONASS frequency bands.
The first Glonass-B is planned for launch in 2023, with the full constellation of six SC to be deployed by the end of 2025, increasing by 25% the navigation accuracy in the Eastern hemisphere.
The satellite mass below 1,000 kg allows Angara-A5, the new Russian heavy launch vehicle, to perform a dual launch from either Plesetsk or Vostochny launch sites.
Much attention is being paid to the signal characteristics’ stability throughout the whole system lifecycle. For this purpose, ROSCOSMOS developed the GLONASS Monitoring and Performance Assessment System for civil users, including the distributed network of monitoring stations abroad, and dedicated radio telescopes capable of analyzing the navigation signal structure and power on the Earth’s surface.
Currently the planned user range error (URE) for signal in space is 1.4 m. Feb. 26, with URE of 1.13 m, became the best day of the ten-month long monitoring in 2018. Moreover, this value tends to decrease as Glonass-M satellites operating beyond their guaranteed life period are being replaced. For instance, on Nov. 3, Glonass-M satellite No. 57 launched, replacing No. 16 after almost 12 years of operation in orbit.
As already mentioned, the Glonass-K2 is planned for launch in 2019. Compared to Glonass-M and Glonass-K satellites, Mission Definition Requirements for Glonass-K2 define URE to be 0.3 m, qualitatively improving GLONASS user performance.
The new on-board frequency standard based on passive hydrogen maser (PHM) will also contribute to better performance. This PHM is undergoing its ground tests and will be installed onboard the SC by the end of the year. Its relative 24-hour stability of better than 5×10-15 ensures the required URE.
