This paper focuses on the precise point positioning (PPP) ambiguity resolution (AR) using the observations acquired from four systems: GPS, BDS, GLONASS, and Galileo (GCRE). A GCRE four-system uncalibrated phase delay (UPD) estimation model and multi-GNSS undifferenced PPP AR method were developed in order to utilize the observations from all systems. For UPD estimation, the GCRE-combined PPP solutions of the globally distributed MGEX and IGS stations are performed to obtain four-system float ambiguities and then UPDs of GCRE satellites can be precisely estimated from these ambiguities. The quality of UPD products in terms of temporal stability and residual distributions is investigated for GPS, BDS, GLONASS, and Galileo satellites, respectively. The BDS satellite-induced code biases were corrected for GEO, IGSO, and MEO satellites before the UPD estimation. The UPD results of global and regional networks were also evaluated for Galileo and BDS, respectively. As a result of the frequency-division multiple-access strategy of GLONASS, the UPD estimation was performed using a network of homogeneous receivers including three commonly used GNSS receivers (TRIMBLE NETR9, JAVAD TRE_G3TH DELTA, and LEICA). Data recorded from 140 MGEX and IGS stations for a 30-day period in January in 2017 were used to validate the proposed GCRE UPD estimation and multi-GNSS dual-frequency PPP AR. Our results show that GCRE four-system PPP AR enables the fastest time to first fix (TTFF) solutions and the highest accuracy for all three coordinate components compared to the single and dual system. An average TTFF of 9.21 min with $$7{^{\circ }}$$
 cutoff elevation angle can be achieved for GCRE PPP AR, which is much shorter than that of GPS (18.07 min), GR (12.10 min), GE (15.36 min) and GC (13.21 min). With observations length of 10 min, the positioning accuracy of the GCRE fixed solution is 1.84, 1.11, and 1.53 cm, while the GPS-only result is 2.25, 1.29, and 9.73 cm for the east, north, and vertical components, respectively. When the cutoff elevation angle is increased to $$30{^{\circ }}$$
 , the GPS-only PPP AR results are very unreliable, while 13.44 min of TTFF is still achievable for GCRE four-system solutions.

Multi-GNSS phase delay estimation and PPP ambiguity resolution: GPS, BDS, GLONASS, Galileo

Unmanned aerial vehicles (UAVs) play a primary role in a plethora of technical and scientific fields owing to their wide range of applications. In particular, the provision of emergency services during the occurrence of a crisis event is a vital application domain where such aerial robots can contribute, sending out valuable assistance to both distressed humans and rescue teams. Bearing in mind that time constraints constitute a crucial parameter in search and rescue (SAR) missions, the punctual and precise detection of humans in peril is of paramount importance. The paper in hand deals with real-time human detection onboard a fully autonomous rescue UAV. Using deep learning techniques, the implemented embedded system was capable of detecting open water swimmers. This allowed the UAV to provide assistance accurately in a fully unsupervised manner, thus enhancing first responder operational capabilities. The novelty of the proposed system is the combination of global navigation satellite system (GNSS) techniques and computer vision algorithms for both precise human detection and rescue apparatus release. Details about hardware configuration as well as the system’s performance evaluation are fully discussed.

Unsupervised Human Detection with an Embedded Vision System on a Fully Autonomous UAV for Search and Rescue Operations

This paper focuses on the contribution of the global positioning system (GPS) and BeiDou navigation satellite system (BDS) observations to precise point positioning (PPP) ambiguity resolution (AR). A GPS + BDS fractional cycle bias (FCB) estimation method and a PPP AR model were developed using integrated GPS and BDS observations. For FCB estimation, the GPS + BDS combined PPP float solutions of the globally distributed IGS MGEX were first performed. When integrating GPS observations, the BDS ambiguities can be precisely estimated with less than four tracked BDS satellites. The FCBs of both GPS and BDS satellites can then be estimated from these precise ambiguities. For the GPS + BDS combined AR, one GPS and one BDS IGSO or MEO satellite were first chosen as the reference satellite for GPS and BDS, respectively, to form inner-system single-differenced ambiguities. The single-differenced GPS and BDS ambiguities were then fused by partial ambiguity resolution to increase the possibility of fixing a subset of decorrelated ambiguities with high confidence. To verify the correctness of the FCB estimation and the effectiveness of the GPS + BDS PPP AR, data recorded from about 75 IGS MGEX stations during the period of DOY 123-151 (May 3 to May 31) in 2015 were used for validation. Data were processed with three strategies: BDS-only AR, GPS-only AR and GPS + BDS AR. Numerous experimental results show that the time to first fix (TTFF) is longer than 6 h for the BDS AR in general and that the fixing rate is usually less than 35 % for both static and kinematic PPP. An average TTFF of 21.7 min and 33.6 min together with a fixing rate of 98.6 and 97.0 % in static and kinematic PPP, respectively, can be achieved for GPS-only ambiguity fixing. For the combined GPS + BDS AR, the average TTFF can be shortened to 16.9 min and 24.6 min and the fixing rate can be increased to 99.5 and 99.0 % in static and kinematic PPP, respectively. Results also show that GPS + BDS PPP AR outperforms single-system PPP AR in terms of convergence time and position accuracy.

Ambiguity resolved precise point positioning with GPS and BeiDou

The focus of this study is on proper modeling of the dynamics for inter-system biases (ISBs) in multi-constellation Global Navigation Satellite System (GNSS) precise point positioning (PPP) processing. First, the theoretical derivation demonstrates that the ISBs originate from not only the receiver-dependent hardware delay differences among different GNSSs but also the receiver-independent time differences caused by the different clock datum constraints among different GNSS satellite clock products. Afterward, a comprehensive evaluation of the influence of ISB stochastic modeling on undifferenced and uncombined PPP performance is conducted, i.e., random constant, random walk process, and white noise process are considered. We use data based on a 1-month period (September 2017) Multi-GNSS Experiment (MGEX) precise orbit and clock products from four analysis centers (CODE, GFZ, CNES, and WHU) and 160 MGEX tracking stations. The results demonstrate that generally, the positioning performance of PPP in terms of convergence time and positioning accuracy with the final products from CODE, CNES, and WHU is comparable among the three ISB handling schemes. However, estimating ISBs as random walk process or white noise process outperforms that as the random constant when using the GFZ products. These results indicate that the traditional estimation of ISBs as the random constant may not always be reasonable in multi-GNSS PPP processing. To achieve more reliable positioning results, it is highly recommended to consider the ISBs as random walk process or white noise process in multi-GNSS PPP processing.

Influence of stochastic modeling for inter-system biases on multi-GNSS undifferenced and uncombined precise point positioning

In the past few decades, global navigation satellite system (GNSS) technology has been widely used in structural health monitoring (SHM), and the monitoring mode has evolved from long-term deformation monitoring to dynamic monitoring. This paper gives an overview of GNSS-based dynamic monitoring technologies for SHM. The review is classified into three parts, which include GNSS-based dynamic monitoring technologies for SHM, the improvement of GNSS-based dynamic monitoring technologies for SHM, as well as denoising and detrending algorithms. The significance and progress of Real-Time Kinematic (RTK), Precise Point Position (PPP), and direct displacement measurement techniques, as well as single-frequency technology for dynamic monitoring, are summarized, and the comparison of these technologies is given. The improvement of GNSS-based dynamic monitoring technologies for SHM is given from the perspective of multi-GNSS, a high-rate GNSS receiver, and the integration between the GNSS and accelerometer. In addition, the denoising and detrending algorithms for GNSS-based observations for SHM and corresponding applications are summarized. Challenges of low-cost and widely covered GNSS-based technologies for SHM are discussed, and problems are posed for future research.

https://www.mdpi.com/2072-4292/11/9/1001/pdf

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

Integration of multi-constellation GNSS creates a significant increase in the number of visible satellites, thus bring new opportunities for improving the accuracy and reliability of Real Time Kinematic (RTK) positioning. This paper proposes a reliable RTK positioning method based on partial wide-lane ambiguity resolution (AR) from GPS/GLONASS/BDS (G/R/C) combination. It takes advantage that wide-lane observation has much longer wavelength, and the multi-constellation combined wide-lane ambiguity-fixed observations are directly used to positioning calculation. In the paper, the G/R/C geometry-based wide-lane ambiguity resolution models are unified and combined. Then a partial ambiguity resolution (PAR) method is introduced to avoid the influence of extreme errors from low-elevation satellites. A set real G/R/C baseline data is used as typical example to reflect the benefits of the proposed method. Experiment results show that the multi-constellation combination can significantly improve the wide-lane AR effects, including the AR success rate, ratio and initialization speed. And the proposed PAR method can effectively avoid the negative influence of new-rising satellites. The positioning accuracy using the proposed method can still reach centimetre level.

Reliable RTK Positioning Method Based on Partial Wide-Lane Ambiguity Resolution from GPS/GLONASS/BDS Combination

Comprehensive outage compensation of real-time orbit and clock corrections with broadcast ephemeris for ambiguity-fixed precise point positioning

Inter-system code double differencing is an effective method for improving the positioning accuracy of low-cost receivers in complex environments. Due to the adoption of Frequency Division Multiple Access (FDMA), Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS) code observations are affected by the Inter-Frequency Code Biases (IFCBs), which makes it difficult to calculate the Differential Inter-System Code Biases (DISCBs) between GLONASS and the Code Division Multiple Access (CDMA) systems directly. In this contribution, the focus is on the performance of tightly combined Global Positioning System (GPS) and GLONASS code Double Difference (DD) positioning. After analysing the relationship between IFCBs and GLONASS channel numbers, an IFCB correction model and an inter-system code differencing model between GLONASS and GPS are proposed. Results show that even if there is no obvious relationship between IFCBs and channel numbers, the long-term stable IFCB values of each satellite can be obtained by using the proposed model. In addition, the GPS + GLONASS DISCB is also stable. Therefore, compared with the intra-system model, the inter-system model can benefit from prior IFCBs and DISCBs parameters and thus can significantly improve the positioning accuracy in obstructed environments.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/1576F815D7F617CDC24F0E8E198D22DF/S0373463319000596a.pdf/div-class-title-tightly-combined-gps-glonass-positioning-with-consideration-of-inter-system-code-bias-and-glonass-inter-frequency-code-bias-div.pdf

Tightly combined GPS + GLONASS positioning with consideration of inter-system code bias and GLONASS inter-frequency code bias

GNSS high-precision differential positioning generally requires the high-precision float solution and the reasonable covariance matrix for ambiguity integers in short observational time spans. But station-star geometric changes little in short observational time spans, which causes the design matrix to be ill-conditioned seriously during adjustment calculation and leads to the solving of parameters is unstable. With the development of Compass Navigation Satellite System, the GNSS high-precision positioning is now entering the multi-system combined ages. GPS, GLONASS and Compass have different orbits and operating features so that there is some difference from each other in adjustment calculation. The paper combining with the analysis theory on ill-conditioned system, analyses the ill posedness of GPS, GLONASS and Compass comparatively through a method called spectrum analysis of eigenvalue. The paper reveals the characteristics of the ill condition in several different positioning forms. The conclusion that the faster the satellites runs, the weaker the ill posedness of the parameters solving system will be is presented.

The Analysis of Ill Posedness in GNSS High-Precision Differential Positioning

The tight combination model improves the positioning accuracy of the Global Navigation Satellite System (GNSS) in complex environments by increasing the redundancy of observation. However, the ambiguity cannot be calculated directly because of the correlation between it and the phase difference inter-system bias (DISB) in the model. This paper proposes a method of DISB estimation based on the principle of maximum ratio. From the data analysis, for the standard deviation of code DISB, the improvement of the method can up to 0·179 m with the poor quality data. In addition, compared to the parameter combination method, the standard deviation of all the phase DISB was deceased with the method in the paper. About the phase DISB of GPS L1/Galileo E1, the standard deviation decreased from 0·014/0·022/0·009/0·051 cycles to 0·006/0·015/0·004/0·029 cycles of four baselines, which represents the improvement of 57·14/31·82/55·56/43·14%. About the phase DISB of GPS L1/BDS B1, the standard deviation decreased from 0·014/0·061/0·010/0·052 cycles to 0·002/0·005/0·009/0·004 cycles of four baselines, which represents the improvement of 85·71/91·80/10·00/92·31%.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/82974BADD20F75C86EA8D29D80A23F4B/S0373463320000430a.pdf/div-class-title-maximum-ratio-principle-based-estimation-of-difference-inter-system-bias-div.pdf

Chengfa Gao

Papers

Reliable RTK Positioning Method Based on Partial Wide-Lane Ambiguity Resolution from GPS/GLONASS/BDS Combination

Comprehensive outage compensation of real-time orbit and clock corrections with broadcast ephemeris for ambiguity-fixed precise point positioning

Tightly combined GPS + GLONASS positioning with consideration of inter-system code bias and GLONASS inter-frequency code bias

The Analysis of Ill Posedness in GNSS High-Precision Differential Positioning

Maximum Ratio Principle-Based Estimation of Difference Inter-System Bias