QZS-R1 is prepped for testing. At left is the Earth-oriented surface that hosts the L-band antenna. (Photo: JAXA)
By Peter Steigenberger, Steffen Thoelert, Sergei Yudanov and Markus Ramatschi
The Japanese QZS-1R satellite was launched on Oct. 26, 2021, from the Tanegashima Space Center in Japan. It serves as a replenishment for QZS-1, the first spacecraft of the Japanese Quasi-Zenith Satellite System (QZSS) in orbit since September 2010.
QZS-1R joins the current QZSS constellation of three satellites in inclined geosynchronous orbit (IGSO) and one geostationary satellite. These four Block I satellites transmit the L1C/A signal at 1575.42 MHz.
QZS-1R, as well as future QZSS satellites, are able to transmit the new L1C/B signal. L1C/B is based on the same family of gold codes as L1C/A, but uses a binary offset carrier (BOC) modulation instead of the binary phase-shift keying (BPSK) and a different PRN range (203–206).
Compared to BPSK, the BOC modulation adds a square wave subcarrier with a frequency of fsc = 1.023 MHz that equals the chipping rate of the ranging code. This subcarrier shifts the peak spectral energy from the center frequency fL1 to fL1 ± fsc to reduce interference with the GPS L1C/A signals.
During in-orbit testing (IOT) from late November until early December 2021, QZS-1R transmitted L1C/A and L1C/B signals intermittently. FIGURE 1 shows a spectrum of the L1-band transmissions of QZS-1R recorded on Nov. 25 with the 30-meter dish antenna of the German Space Operations Center in Weilheim, Germany, as well as a spectrum of QZS-2 recorded in July 2017.
Figure 1. L1 spectra of QZS-1R (red) transmitting L1C/B and L1C, as well as QZS-2 (blue) transmitting L1C/A and L1C. The spectra were measured with DLR’s 30-meter high-gain antenna on Nov. 25, 2021, and July 20, 2017, respectively. (Credit: DLR)
During IOT, QZS-1R had an extremely low maximum elevation of 0.8° in Weilheim. Due to technical restrictions for such low elevations, QZS-1R had to be observed with a sidelobe of the 30-meter antenna. As a result, the respective observations are much more noisy than the QZS-2 reference data.
Nevertheless, the different spectral characteristics of L1C/B and L1C/A can be clearly seen in FIGURE 1: L1C/B has two maxima at 1574.4 and 1576.5 MHz due to the BOC modulation, whereas the BPSK L1C/A signal has one maximum at the center frequency of 1575.42 MHz.
GNSS receivers of the International GNSS Service (IGS) started to track L1C/A, L1C, L2C and L5 signals of QZS-1R on Nov. 17. Aside from the regular PRN code J04, test signals using the non-standard code PRN J06 were intermittently transmitted by QZS-1R during the IOT and tracked by these receivers.
Based on the public specification of the new L1C/B signal, Javad GNSS developed a prototype firmware that enabled tracking of this signal during the early transmissions. This firmware was installed on a Javad TRE-3 receiver operated by GFZ German Research Centre for Geosciences at its IGS station WUH200CHN in Wuhan, China.
FIGURE 2 illustrates the noise and multipath characteristics of different QZS-1R pseudorange measurements. It is based on the so-called multipath linear combination of L1 pseudorange and L1/L2 carrier-phase observations covering a six-hour data arc. RMS values were computed for 5-degree elevation bins for each pseudorange signal. While the individual signals were tracked on different days of the IOT and the associated results have to be interpreted with care, the data indicate a very similar ranging performance of the legacy C/A signal and the new C/B signal. Best results are obtained with the L1C signal, which uses both a higher signal power and an advanced modulation with superior multipath suppression.
Figure 2. Noise and multipath characteristics of QZS-1R signals on the L1 frequency tracked by the IGS station WUH200CHN in Wuhan, China. (Credit: DLR)
QZS-1R will resume continuous transmission of L1C/A as soon as declared healthy. The transition from L1C/A to L1C/B is planned for 2023-2024, when an operational QZSS constellation of seven satellites is reached. The launches of the IGSO satellite QZS-5, the geostationary QZS-6, and the quasi-geostationary QZS-7 are all planned for 2023.
GNSS data used in this article were collected with a Javad GNSS TRE-3 receiver. The spectral overviews were captured with a Rohde & Schwarz FSQ26 signal analyzer.
Peter Steigenberger is a senior scientist at the German Space Operations Center of the German Aerospace Center (DLR), where he conducts research in the field of new satellite navigation systems.
Steffen Thoelert is an electrical engineer at DLR’s Institute of Communications and Navigation. His research activities focus on signal-quality monitoring and satellite payload characterization.
Sergei Yudanov is a senior firmware developer at Javad GNSS, Moscow. His main field of activity is GNSS signal processing.
Markus Ramatschi is a senior scientist at the Helmholtz Centre Potsdam, GFZ German Research Centre for Geoscience. He is operating a global GNSS reference station network.
Ramatschi M., Bradke M., Nischan T., Männel B. (2019): “GNSS data of the global GFZ tracking network,” vol 1. GFZ Data Services. https://doi.org/10.5880/GFZ.1.1.2020.001
In this issue’s cover, a man with a backpack lidar unit, a GNSS receiver and a tablet computer is surveying in a complex and challenging urban setting. That same lidar unit also can be mounted on a UAV. One of the contributors to this month’s cover story describes the role of aerial photogrammetry in the architecture, engineering and construction (AEC) industry. Satellite navigation, remote sensing, mapping software, a great variety of platforms, and ever more powerful handheld computers — those are the key ingredients in today’s ecosystem of geospatial technologies. The current generation of surveying equipment has more than halved fieldwork in the past two decades while greatly improving the quality of the data collected.
The AEC industry relies on surveyors to be “a bridge between the existing landscape and the design landscape,” said another contributor to our cover story. Unlike traditional boundary surveying, he explained, surveying for AEC requires consideration of a detailed 3D world. It also involves many more stakeholders and much greater liability.
The tight integration of GNSS, inertial systems, lidar sensors and 360° spherical imagery into mobile mapping systems makes 3D modeling possible and traditional GNSS or optical measurement instruments obsolete. However, while inertial systems are invaluable to bridge brief gaps in the availability and reliability of GNSS signals, they are far from the panacea they are sometimes claimed to be, as Brad Parkinson reminds us in an interview with Dana Goward, also in this issue.
Surveying for AEC requires at least centimeter accuracy. The challenges of surveying in urban settings include urban canyons that occult signals and create multipath, traffic and multiple layers of underground, ground-level and above-ground infrastructure.
Beyond the construction phase, 3D survey data is increasingly used to create digital twins of buildings, which facilitate their operation and maintenance throughout their life cycle and help lower their carbon footprint. Once they have completed an initial survey, surveyors often set control to be used for machine control — the theme of our cover story in next month’s issue.
In this issue we also:
• Inaugurate a “letters to the editor” section to make more room for debate in the GNSS/PNT community on the critical issues it faces.
• Report on a Jet Propulsion Laboratory study of the impact on the ionosphere of the enormous volcanic eruption in Tonga and the beginnings of a GNSS-based early warning system for natural hazards.
• Continue our series of articles on GNSS constellations, with an update from Japan’s QZSS constellation.
• Feature three studies: one on real-time simulator testing using an NMEA data stream, one on the first transmission of L1C/B signals by QZSS, and one on self-driving cars in major metropolitan areas.
All these advances, however, are threatened when GPS is threatened. Earlier in the month, three members of our editorial advisory board comment on the recent threat to GPS satellites by the Russian government.
ION’s Pacific PNT Conference is a global cooperative development of Positioning, Navigation and Timing technology and applications where policy and technical leaders from around the world meet to discuss policy updates, receive program status updates and exchange technical information.
The 2022 conference will be hosted virtually April 11-13 PDT on a complimentary basis for ION members. The conference will include sessions on policy and status updates, performance schedules and plans, plus special challenges affecting Asia-Pacific presented by an elite list of experts representing BeiDou, COSMIC/ FORMOSAT, and QZSS.
A session will broadcast each day at 9:00 a.m. JST / 5:00 p.m. PDT. Live-stream attendees will have the opportunity to participate in virtual question and answer periods through the portal.
A successor to the first Quasi-Zenith Satellite System (QZSS) satellite, QZS-1R, was launched at 11:19 a.m. Japan Standard Time, Oct. 26, from the Tanegashima Space Center.
QZS-1R was carried aboard H-IIA rocket No. 44 by Mitsubishi Heavy Industries. The flight proceeded as planned, and, 28 minutes 6 seconds after launch, the payload separated from the launch vehicle.
Designed for a 15-year lifetime, QZS-1R will replace the QZS-1 (Michibiki-1). QZS-1 launched on Sept. 11, 2010, and entered its quasi-zenith orbit 10 days later. Three other quasi-zenith navigation satellites launched in 2017 to complete the constellation.
QZSS began service in November 2018 with four satellites. The Japan Aerospace Exploration Agency (JAXA) plans to have seven satellites aloft by 2023.
An H-2A rocket launches from Tanegashima Space Center carrying the QZS-1R satellite. (Photo: MHI)
UPDATE: Because of bad weather, the launch is now scheduled for Oct. 26 (Oct. 25, 18:45 p.m. PT).
The launch of the “QZS-1R”, the replacement for QZS-1 by H-IIA No. 44 scheduled for Oct. 25 is postponed as a result of weather assessment. New launch date is Oct. 26. #H2AF44
A successor to the first Quasi-Zenith Satellite System (QZSS) satellite is planned for launch from the Tanegashima Space Center on Monday, Oct. 25, from 11 a.m. to 12 p.m. Japan Standard Time (2-3 a.m. UTC).
Michibiki Unit 1 was launched on Sept. 11, 2010, and entered its quasi-zenith orbit 10 days later. QZSS began service in November 2018 with four satellites. The Japan Aerospace Exploration Agency (JAXA) plans to have seven satellites aloft by 2023.
The satellite, designated QZS-1R, will be carried aboard H-IIA rocket No. 44. The QZSS launch will be streamed live. The broadcast program will begin at 10:35 a.m. JST.
Local launch times
Houston: Sunday, October 24, 21:00 New York: Sunday, October 24, 22:00 London: Monday, October 25, 03:00 UAE: Monday, October 25, 06:00 Singapore: Monday, October 25, 10:00
To follow upcoming GNSS satellite launches, see our launch table, provided by Innovation editor Richard Langley.
H-IIA Launch Vehicle No. 44 at the Yoshinobu Vehicle Assembly Building, JAXA Tanegashima Space Center. in preparation for launch of the successor to the Michibiki Unit 1 on Oct. 25. (Photo: MHI)
Shinichi Nakasuka, professor at the University of Tokyo Graduate School of Engineering and member of the Cabinet Office Space Policy Committee, released the following statement about the upcoming launch.
“Three years after the full operation of the four-machine Michibiki started in 2018, as the chairman of the Quasi-Zenith Satellite System Business Promotion Committee of the Cabinet Office, we strive to ensure the reliable operation and expansion of the use of this world-class system.
“I feel that high-precision positioning and two-way communication services in the event of a disaster, which cannot be achieved by GPS alone, are gradually taking root as social infrastructure. In modern society, the provision of highly accurate position and time is exactly the infrastructure that is indispensable as the ‘nerve network’ of society.
“To make that more reliable, the successor to the first machine, which pioneered this system, is about to be launched. We pray for the success of the launch and satellite operation, and hope that the Quasi-Zenith Satellite System will become more and more established in society, and that many people will be able to use this system for various purposes, including business.”
First, there was one. In July 1995, the U.S. Air Force declared the Global Positioning System had met all the requirements for full operational capability (FOC). Soon thereafter, there were two. In December of that same year, Russia’s Globalnaya Navigazionnaya Sputnikovaya Sistema (Global Navigation Satellite System, or GLONASS), also achieved FOC. For a quarter century, that was it.
Then, last year, the number doubled, as both the European Union’s Galileo and China’s BeiDou Navigation Satellite System (BDS, named after the Big Dipper asterism, which is known in Chinese as Beidou) achieved FOC.
The Indian Regional Navigation Satellite System (IRNSS, aka Navigation Indian Constellation, or NavIC, which means “sailor” or “navigator” in Hindi) and Japan’s Quasi-Zenith Satellite System (QZSS, also known as Michibiki) are not global yet, but plan to become so. Currently, NavIC is an autonomous regional satellite navigation system, and NavIC-based trackers are compulsory on commercial vehicles in India. QZSS currently complements GPS to improve coverage in East Asia and Oceania, but Japan plans to have an operational constellation of seven satellites for autonomous capability by 2023. The Korea Positioning System (KPS) plans to join the party by 2035.
Who’s next? Will it be another country or a private company? Given that the state-sponsored systems are free to end users, I don’t see what the business model would be for a private GNSS constellation, unless it were to piggyback on one built mainly for another purpose.
Surveyors who have begun to routinely use three or more constellations are over the moon. One, quoted in this month’s cover story, recalls that “the use of GPS for construction staking was an extremely risky proposition” because its residuals exceeded most construction tolerances. Using multiple GNSS constellations, however, has increased confidence in the accuracy of results to the point that some construction companies are relying on GNSS receivers for staking. Additionally, multi-constellation receivers can now increasingly be used under tree canopies and against structures, whether natural or built.
Whatever their mix of military, political and commercial motivations for building, deploying and operating their own GNSS constellations in addition to the original two, the European Union, China, India, Japan, Korea and whichever entity may follow are greatly improving satellite-based positioning, navigation and timing (PNT) for all users everywhere — by increasing accuracy, shortening the time to first fix, and making GNSS more impervious to jamming and spoofing.
In 1978, the year that the U.S. Department of Defense launched the first NAVSTAR GPS satellite (“NAVSTAR” was later dropped from the system’s name), Neil Young sang “Four Strong Winds” (originally written by Ian Tyson and performed by him with his wife Sylvia as the Canadian folk-duo Ian and Sylvia).
Now, GNSS has “four strong winds,” two lighter ones and several more breezes to follow. As a sailor and a navigator, I welcome them heartily. As this magazine’s editor-in-chief, I don’t mind that, like Jeep, Kleenex, Popsicle and Xerox, GPS probably will stick in popular culture as a generic term for global satellite navigation systems way past its accurate description of what is in the box.
The successor to the first quasi-zenith satellite, dubbed Michibiki, is expected to launch this year.
Michibiki was launched by the Japan Aerospace Exploration Agency (JAXA) in September 2010 and was transferred to the Cabinet Office in 2017. The replacement satellite is now undergoing prototype testing at the satellite manufacturer’s facility(Mitsubishi Electric Co. Ltd. Kamakura Seisakusho) in Kanagawa.
The tests will confirm performance of the replacement satellite before it is put into service. It is undergoing acousitic, vibration and thermal vacuum tests to ensure it will remain functional after launch and in space.
After testing, the satellite will be transported to the Tanegashima Space Center for launch, which is expected to take place later this year.
Replacement for Michibiki: The L-band antenna that transmits the positioning signal is mounted on the Earth-oriented left side. (Photo: JAXA)
Though built to succeed the first QZSS satellite, the replacement is based on the second and fourth satellites
Main specifications of the successor to the first satellite and other satellites:
item
First machine
Units 2 and 4
Unit 3
Successor to the first machine
Orbit
Quasi-zenith
Quasi-zenith
Rest
Quasi-zenith
Positioning signal
L1-C / A,
L1C, L1S,
L2C, L5, L6
L1-C / A, L1C,
L1S, L2C,
L5, L5S, L6
L1-C / A, L1C,
L1S, L1Sb, L2C,
L5, L5S, L6
L1-C / A
(L1-C / B (* 1)),
L1C, L1S, L2C,
L5, L5S, L6
L band antenna
Helical method
(* 2)
Helical method
(* 2)
Patch method
(* 3)
Patch method
(* 3)
Generated power
5.3kW
6.3kW
6.3kW
6.3kW
mass
About 4t
About 4t
About 4.7t
About 4t
Design life
10 years or more
Over 15 years
Over 15 years
Over 15 years
Launch year
2010
2017
2017
2021
(planned)
Launch
rocket
H2A202
H2A202
H2A204
H2A202
(* 1) Signal transmitted by BOC (Binary Offset Carrier) modulation of L1-C / A code
(* 2) Antenna with spiral antenna elements arranged
(* 3) Antenna with planar antenna elements arranged
Japan’s Quasi-Zenith Satellite System (QZSS) CLAS received a major enhancement on Nov. 30. QZSS CLAS (centimeter-level augmentation service) is the satellite-based nationwide open PPP-RTK service in Japan, providing centimeter positioning accuracy within one minute.
With the introduction of a new, highly efficient atmospheric correction message, the number of available satellites will be increased to 17 for those using CLAS. GPS, Galileo and QZS satellites in view will be corrected by the QZS L6 signal.
“The performance is expected be improved considerably, especially in urban areas,” said Rui Hirokawa, the deputy general manager, Space Systems Department of Mitsubishi Electric Corporation, Kamakura Works, in an email to GPS World.
Compact SSR — a highly efficient RTCM-compatible open specification for PPP/PPP-RTK — is applied to QZS CLAS. Compact SSR is accepted as a PPP-RTK standard in the 3GPP LTE positioning protocol (LPP) and the mobile communication standard for LTE/5G, with plans for it to be applied to the Galileo High-Accuracy Service (HAS).
Since July 1, CLAS has been broadcasting a trial signal compliant with IS-QZSS-L6-003 using the L6D signal of QZS-3, which increases the number of augmented satellites to a maximum of 17 for more stable positioning accuracy.
On Nov. 30 (JST), the official broadcast of the augmentation information began from all four QZS satellites (QZS-1, 2, 3 and 4).
To continue using CLAS after Nov. 30, it may be necessary to update the receiver’s F/W to comply with IS-QZSS-L6-003. Please contact the manufacturer of the CLAS receiver for further information. Read more in this National Space Policy Secretariat notice.
The application was developed with special interest paid to raw data recording and NTRIP service connection.
With the SXblue ToolBox iOS application, the user can analyze the position data provided by the SXblue receiver, as well as location metadata.
More important for SXblue clients, the application can record, save and transfer raw data from the GNSS receiver, thereby allowing post-processing activities. The application also acts as a NTRIP client, capable of connecting to a NTRIP server for real-time kinematic (RTK) corrections, and thus allows the receiver to issue very accurate location information.
Receiver configuration is easy through the application, with the ability to set up and save user-defined commands for subsequent use. The settings include constellation to be used, differential source, NTRIP login credentials list and more.
In addition, the iOS application includes a series of audible and visual alarms that are user-configurable to determine the thresholds of information provided by the SXblue GNSS receiver.
The main features of the iOS SXblue ToolBox application are:
Display of location information and quality of positioning data
Skyplot of all-in-view constellations: GPS, GLONASS, Galileo BeiDou, QZSS, SBAS
Recording of raw data and data transfer
NTRIP/DIP client to receive RTK corrections
Terminal to send commands and view the output data of the SXblue device
Audible and visual alarms
Activation of options and licenses via the application.
Allystar Technology Co. has launched its QZSS L6 decoder technology in module TAU-1303, which supports tracking the QZSS signals L6D (CLAS) and L6E (MADOCA).
The Quasi-Zenith Satellite System (QZSS) satellite positioning system is operated by Japan as complementary to and an augmentation for GPS. The four satellites in the system broadcast the L6 signal, including L6D and L6E.
CLAS — the Centimeter-Level Augmentation Service — is provided through the L6(D1) signal, and the experimental augmentation service with MADOCA (Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis) is provided through L6(D2) signal.
For QZSS, which will be fully operational in the future, Allystar’s latest solution can decode the corrections data broadcast from L6D and L6E signals, and assist developers in applying the centimeter-level accuracy by PPP-RTK algorithm with the correction data, according to Justin Yang, Allystar product manager.
Within its 7.6 x 7.6-millimeter tiny size, the TAU-1303 module provides six dedicated tracking channels to support tracking L6D and L6E at the same time.
For professional applications, the TAU1303 comes with built-in support for standard RTCM Protocol (MSM) and Proprietary Protocol, supporting 2,000 bits per second QZSS L6 raw data output directly for third-party integration and application.
CLAS on L6D channel provides the following error corrections: satellite clock, orbit, code bias, phase bias ionospheric delay and tropospheric delay. MADOCA on L6E channel provides the following error corrections: satellite clock, orbit, code bias and phase bias.
Allystar TAU-1303 offers superior performance thanks to an on-board 26-MHz temperature-compensated crystal oscillator (TCXO) and a reduced time to first fix because of its dedicated 32-KHz real-time clock oscillator. Based on 40-nanometer manufacturing processes of the Cynosure III GNSS chipset, the TAU-1303 has very low power consumption of less than 40 mA at 3.3V.
Engineering samples are available.
How Allystar’s QZSS L6 Decoder TAU1303 operates. (Diagram: Allystar)
SoftBank plans to introduce a centimeter-accurate, real-time satnav-based positioning service, specifically using Japan’s Quasi-Zenith Satellite System (QZSS), to guide autonomous vehicles across a range of industries in Japan. The company said it will install more than 3,300 control points at base stations across Japan to deliver centimeter-level accuracy over its mobile network coverage area to provide real-time kinematic (RTK) positioning.
Testing begins in July with a scheduled launch of commercial service by the end of November. Test partners include Yanmar Agribusiness Co., Ltd., a provider of autonomous assisted driving for agricultural machinery, Kajima Corporation, which performs construction site management with automatically controlled drones for aerial photography and monitoring, and SB Drive Corp., a provider of autonomous and assisted driving technology for buses.
SoftBank is developing proprietary low-cost GNSS receivers so that “new services and market expansion can be realized.” A Positioning Core System provided by ALES Corp. will generate correctional data based on signals received and transmitted by SoftBank’s own control points over SoftBank’s mobile communications network to agricultural and construction machinery, self-driving cars, drones and other equipment carrying GNSS receivers. The company expects that centimeter-level positioning can thus be done in real time.
In addition to control points at its own base stations, SoftBank will use the Geospatial Information Authority of Japan’s approximately 1,300 GPS-based control stations.
SoftBank is also developing services to enablec loud-based RTK positioning for devices without GNSS receivers. Cloud-based RTK will provide centimeter-level, location-based services for equipment that needs to be miniature and energy-efficient, such as infrastructure surveillance sensors and wearable devices.
SoftBank Group Corp. is a Japanese multinational conglomerate holding company headquartered in Tokyo. It owns operations in broadband, fixed-line telecommunications, e-commerce, internet, technology services, finance, semiconductor design and more. It is the 36th largest public company in the world, and the 2nd largest in Japan.
ALES is a joint venture established by SoftBank and Enabler in July 2018. Enabler employs GNSS and related technologies to produce such products/services as a synchronization solution for mobile base stations for subway stations and a patented indoor positioning/time synchronization infrastructure platform in Japan.
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.
