Satellite Navigation

Abstract This paper reviews the status of satellite navigation (as per 11 May 2020)—without claim for completeness—and discusses the various global navigation satellite systems, regional satellite navigation systems and satellite-based augmentation systems. Problems and challenges for delivering nowadays a safe and reliable navigation are discussed. New opportunities, perspectives and megatrends of satellite navigation are outlined. Some remarks are closing this paper emphasizing the great value of satellite navigation at present and in future.

Guenter W. Hein

Satell Navig

Status, perspectives and trends of satellite navigation

卫星导航的现状、展望与趋势

Wang Li

Yiping Jiang

Equatorial plasma bubble model and integrity risk evaluation for ground based augmentation system in Hong Kong

赤道等离子体泡模型与香港地区地基增强系统完整性风险评估

Abstract In complicated urban environments, Global Navigation Satellite System (GNSS) signals are frequently affected by building reflection or refraction, resulting in Non-Line-of-Sight (NLOS) errors. In severe cases, NLOS errors can cause a ranging error of hundreds of meters, which has a substantial impact on the precision and dependability of GNSS positioning. To address this problem, we propose a reliable NLOS error identification method based on the Light Gradient Boosting Machine (LightGBM), which is driven by multiple features of GNSS signals. The sample data are first labeled using a fisheye camera to classify the signals from visible satellites as Line-of-Sight (LOS) or NLOS signals. We then analyzed the sample data to determine the correlation among multiple features, such as the signal-to-noise ratio, elevation angle, pseudorange consistency, phase consistency, Code Minus Carrier, and Multi-Path combined observations. Finally, we introduce the LightGBM model to establish an effective correlation between signal features and satellite visibility and adopt a multifeature-driven scheme to achieve reliable identification of NLOSs. The test results show that the proposed method is superior to other methods such as Extreme Gradient Boosting (XGBoost), in terms of accuracy and usability. The model demonstrates a potential classification accuracy of approximately 90% with minimal time consumption. Furthermore, the Standard Point Positioning results after excluding NLOSs show the Root Mean Squares are improved by 47.82%, 56.68%, and 36.68% in the east, north, and up directions, respectively, and the overall positioning performance is significantly improved.

Xiaohong Zhang

Xinyu Wang

Wanke Liu

Xianlu Tao

Yupeng Gu

Hailu Jia

Chuanming Zhang

A reliable NLOS error identification method based on LightGBM driven by multiple features of GNSS signals

基于多特征GNSS信号驱动的LightGBM可靠NLOS误差识别方法

Abstract Real-Time Precise Point Positioning (RT-PPP) has been one of the research hotspots in GNSS (Global Navigation Satellite System) community for decades. Real-time precise products of satellite orbits and clocks are the prerequisite for RT-PPP. Thus, it is of great importance to investigate the current multi-GNSS real-time precise products in State Space Representation (SSR) from different analysis centers. In this article, SSR products from 10 analysis centers are comprehensively evaluated by comparing them with the final products and performing the kinematic PPP. The results show that analysis centers CNES (Centre National D'Etudes Spatiales) and WHU (GNSS Research Center of Wuhan University) provide the most complete products with the best quality. Concerning the accuracy of real-time products for the GNSSs, the accuracies of orbit and clock products are better than 5 cm and 0.15 ns, respectively, for Global Positioning System (GPS), followed by Galileo navigation satellite system (Galileo), BeiDou-3 Navigation Satellite System (BDS-3), GLObal NAvigation Satellite System (GLONASS), and BeiDou-2 Navigation Satellite System (BDS-2). Meanwhile, the results of the RT-PPP with quad-system show that the positioning accuracies are 1.76, 1.12 and 2.68 cm in east, north, and up directions, respectively, and the convergence time to 0.1, 0.1, 0.2 m for corresponding directions is 15.35 min.

Bofeng Li

Haibo Ge

Yuhang Bu

Yanning Zheng

Leitong Yuan

Comprehensive assessment of real-time precise products from IGS analysis centers

IGS分析中心实时精密产品的综合评估

Abstract Real-time satellite orbit and clock estimations are the prerequisite for Global Navigation Satellite System (GNSS) real-time precise positioning services. To meet the high-rate update requirement of satellite clock corrections, the computational efficiency is a key factor and a challenge due to the rapid development of multi-GNSS constellations. The Square Root Information Filter (SRIF) is widely used in real-time GNSS data processing thanks to its high numerical stability and computational efficiency. In real-time clock estimation, the outlier detection and elimination are critical to guarantee the precision and stability of the product but could be time-consuming. In this study, we developed a new quality control procedure including the three standard steps: i.e., detection, identification, and adaption, for real-time data processing of huge GNSS networks. Effort is made to improve the computational efficiency by optimizing the algorithm to provide only the essential information required in the processing, so that it can be applied in real-time and high-rate estimation of satellite clocks. The processing procedure is implemented in the PANDA (Positioning and Navigation Data Analyst) software package and evaluated in the operational generation of real-time GNSS orbit and clock products. We demonstrated that the new algorithm can efficiently eliminate outliers, and a clock precision of 0.06 ns, 0.24 ns, 0.06 ns, and 0.11 ns can be achieved for the GPS, GLONASS, Galileo, and BDS-2 IGSO/MEO satellites, respectively. The computation time per epoch is about 2 to 3 s depending on the number of existing outliers. Overall, the algorithm can satisfy the IGS real-time clock estimation in terms of both the computational efficiency and product quality.

Xiang Zuo

Xinyuan Jiang

Pan Li

Jungang Wang

Maorong Ge

Harald Schuh

A square root information filter for multi-GNSS real-time precise clock estimation

多GNSS实时精密钟差估计的平方根信息滤波器

Abstract The quest for reliable vehicle navigation in urban environments has led the integration of Light Detection and Ranging (LiDAR) Odometry (LO) with Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU). However, the performance of the integrated system is limited by a lack of accurate LO error modeling. In this paper, we propose a weighted GNSS/IMU/LO integration-based navigation system with a novel LO error model. The Squared Exponential Gaussian Progress Regression (SE-GPR) based LO error model is developed by considering the vehicle velocity and number of point cloud features. Based on error prediction for GNSS positioning and LO, a weighting strategy is designed for integration in an Extended Kalman Filter (EKF). Furthermore, error accumulation of the navigation state, especially in GNSS-challenging scenarios, is restrained by the LiDAR-Aided Lateral Constraint (LALC) and Non-Holonomic Constraint (NHC). An experiment was conducted in a deep urban area to test the proposed algorithm. The results show that the proposed algorithm delivers horizontal and three-dimensional (3D) positioning Root Mean Square Errors (RMSEs) of 3.669 m and 5.216 m, respectively. The corresponding accuracy improvements are 35.9% and 50.0% compared to the basic EKF based GNSS/IMU/LO integration.

Hanzhi Chen

Rui Sun

Qi Cheng

Tong Yin

Yi Zhou

Washington Yotto Ochieng

GNSS/IMU/LO integration with a new LO error model and lateral constraint for navigation in urban areas

GNSS/IMU/LO组合导航系统结合新型LO误差模型与侧向约束在城市区域的应用

Abstract Spaceborne global navigation satellite system-reflectometry has become an effective technique for Soil Moisture (SM) retrieval. However, the accuracy of global SM retrieval using a single model is limited due to the complexity of land surface. Introducing redundant ancillary data may also result in over-reliance problems. Therefore, we propose a method for SM retrieval that considers geographical disparities using the data from Cyclone GNSS (CYGNSS) observations and Soil Moisture Active and Passive (SMAP) product. Based on the CYGNSS effective reflectivity and ancillary datasets of SMAP, we establish five models for each grid with different parameters to achieve global SM retrieval. Subsequently, an optimal model, determined by the performance indicator, is used for SM retrieval. The results show that the root mean square error $$S_{\mathrm{RMSE}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>RMSE</mml:mi> </mml:msub> </mml:math> with the improved method is decreased by 9.1% using SMAP SM as reference with the $$S_{\mathrm{RMSE}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>RMSE</mml:mi> </mml:msub> </mml:math> = 0.040 cm 3 /cm 3 compared with using single reflectivity-temperature-vegetation method. Additionally, using the in-situ SM of International Soil Moisture Network as reference, the overall correlation coefficient $$R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>R</mml:mi> </mml:math> and $$S_{\mathrm{RMSE}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>RMSE</mml:mi> </mml:msub> </mml:math> values with the improved method are 0.80 and 0.064 cm 3 /cm 3 , respectively. The average $$R$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>R</mml:mi> </mml:math> of the chosen sites is increased by 22.7%, and the average $$S_{\mathrm{RMSE}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>S</mml:mi> <mml:mi>RMSE</mml:mi> </mml:msub> </mml:math> is decreased by 8.7%. The results indicate that the improved method can better retrieve SM in both global and local scales without redundant auxiliary data.

Liangke Huang

Anrong Pan

Fade Chen

Fei Guo

Haojun Li

Lilong Liu

A novel global grid model for soil moisture retrieval considering geographical disparity in spaceborne GNSS-R

考虑星载GNSS-R地理差异的土壤湿度反演新型全球网格模型

Abstract The joint utilization of the Fifth Generation Communications Technology (5G) and the Global Navigation Satellite System (GNSS) serves as a promising solution to address the challenges associated with insufficient visible satellites and lower observation quality in urban environments. 5G allows for the angle and distance measurements, augmenting the performance of Real-Time Kinematic (RTK) positioning. To quantify the improvement of 5G observations on RTK positioning, this paper proposes a float solution gain factor and the Ambiguity Dilution of Precision (ADOP) gain factor. Based on these gain factors, the theoretical analysis and simulation are performed. This study designs an extended Kalman filter for 5G-assisted BeiDou Navigation Satellite System (BDS) RTK positioning, employing both the Full Ambiguity Resolution (FAR) and Partial Ambiguity Resolution (PAR) modes. Our experiment verified the effectiveness of 5G-assisted BDS RTK positioning in mitigating outlier occurrences and improving the ambiguity fixing rate as well as the positioning accuracy. In the FAR and PAR modes, the Three-Dimensional (3D) spatial accuracy increased by 48% and 18.8%, respectively, and the results are consistent with theoretical analysis based on gain factors. The fixing rate of RTK increased from 11.11% to 13.93%, while it increased from 32.58% to 44.43% for the PAR mode. The assistance of 5G observations reduced the median error for the FAR mode from over 1.3m to 0.9 m, and the third quartile from 2.1m to 1.05 m. For the PAR mode, the median error decreased from 0.5m to 0.12 m, and the third and fourth quartiles decreased from 0.65m to 0.38 m.

Weixiang Chen

Tengfei Wang

Zheng Yao

Mingquan Lu

Yi Wang

Cheng Li

Analysis of the gain factors of 5G-assisted BDS RTK positioning in urban environments

城市环境中5G辅助BDS RTK定位增益因素分析

Abbreviation	Satell Navig
Journal Impact	8.80
Quartiles(Global)	TELECOMMUNICATIONS(Q1)

ISSN	2662-1363, 2662-9291
h-index	25

Publication Information	Publisher: Springer，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2020，Proportion of original research papers: 89.29%，Self Citation Rate:4.40%， Gold OA Rate: 100.00%
Average review cycle	网友分享经验：12 Weeks

Satellite Navigation

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Status, perspectives and trends of satellite navigation

Equatorial plasma bubble model and integrity risk evaluation for ground based augmentation system in Hong Kong

A reliable NLOS error identification method based on LightGBM driven by multiple features of GNSS signals

Comprehensive assessment of real-time precise products from IGS analysis centers

A square root information filter for multi-GNSS real-time precise clock estimation

Equatorial plasma bubble model and integrity risk evaluation for ground based augmentation system in Hong Kong

A reliable NLOS error identification method based on LightGBM driven by multiple features of GNSS signals

GNSS/IMU/LO integration with a new LO error model and lateral constraint for navigation in urban areas

A novel global grid model for soil moisture retrieval considering geographical disparity in spaceborne GNSS-R

Analysis of the gain factors of 5G-assisted BDS RTK positioning in urban environments