Article
Engineering, Aerospace
Baoyu Liu, Yang Gao, Xingqun Zhan
Summary: This paper proposes a new autonomous integrity monitoring algorithm for federated GNSS/INS ultra-tight integrations. By utilizing GNSS code phase tracking errors, the algorithm can detect and bound position solution errors.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Engineering, Multidisciplinary
GuangLe Gao, SheSheng Gao, GaoGe Hu, YongMin Zhong, Xu Peng
Summary: This paper proposes a tightly coupled INS/CNS/SRS integration framework based on the spectral redshift error measurement, which can achieve better anti-interference ability and accuracy under complicated conditions. By incorporating an improved covariance estimation method into the federated Kalman filter, the system can handle measurement outliers caused by inaccurate redshift estimation without affecting the effect of other correct redshift measurements in suppressing the error of the navigation parameter on the filtering solution. Simulations and comprehensive analyses demonstrate the improved performance of the proposed integrated navigation system in handling outliers and outages under hostile observation conditions.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Robotics
Xingxing Li, Shengyu Li, Yuxuan Zhou, Zhiheng Shen, Xuanbin Wang, Xin Li, Weisong Wen
Summary: This letter proposes a tightly coupled integration method that combines global navigation satellite system (GNSS), inertial measurement unit (IMU), and vision to achieve continuous and accurate navigation in urban environments. By directly fusing raw GNSS measurements, IMU data, and visual features at the observation level using a centralized Extended Kalman Filter (EKF), the method makes full use of the multi-sensor information and rejects outlier measurements. Additionally, it unifies high-precision GNSS models, such as precise point positioning (PPP) and real-time kinematic (RTK), to increase usability and flexibility. The proposed method is validated on challenging datasets collected in urban canyons and compared against loosely coupled and state-of-the-art methods.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Environmental Sciences
Jing Mi, Qing Wang, Xiaotao Han
Summary: In order to improve the navigation performance and robustness of a navigation system combining ultrawideband (UWB) and inertial navigation systems (INS) in complex indoor environments, an improved navigation method called Allan variance (AV) is proposed. This method utilizes AV to model the stochastic noise of an inertial sensor and compensates for inertial sensor error caused by stochastic noise. In addition, a modified adaptive extended Kalman Filter based on the dynamic weight function (DWF-MAEFF) is developed to further enhance the robustness of the system. Field tests have shown that this proposed method can achieve up to a 60% improvement compared to existing integrated navigation methods based on EKF and AEKF.
Article
Computer Science, Information Systems
Shengyu Li, Shiwen Wang, Yuxuan Zhou, Zhiheng Shen, Xingxing Li
Summary: The demand for high-precision positioning and navigation in emerging IoT applications is increasing. The limitations of the global navigation satellite system (GNSS) in urban areas and the accuracy issues of inertial navigation system (INS) with low-cost microelectromechanical system (MEMS) inertial measurement units (IMUs) have led to the proposal of a tightly coupled multi-GNSS PPP/INS/LiDAR integrated system. This integrated system, along with the LiDAR sliding-window plane-feature tracking method, has been proven to provide submeter level horizontal positioning accuracy in challenging GNSS environments with significant improvements compared to traditional GNSS/INS integration.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Chun Ma, Shuguo Pan, Wang Gao, Hao Wang, Liwei Liu
Summary: Kalman filter (KF) is an efficient approach for state estimation in integrated positioning systems. However, in urban environments, GNSS/INS integrated positioning systems are susceptible to state model perturbations and measurement outliers. To solve this problem, this study presents a robust adaptive filtering algorithm based on variational Bayesian (VBRAKF), which improves positioning performance by introducing robust estimation and variational Bayesian estimation methods.
Article
Engineering, Civil
Xingxing Li, Zeyang Qin, Zhiheng Shen, Xin Li, Yuxuan Zhou, Baoshan Song
Summary: This article proposes a multi-sensor integration system for high-precision vehicle navigation using GNSS PPP-RTK, MEMS IMU, and wheel odometer. Experimental results demonstrate that the system achieves high-precision positioning in different scenarios and can maintain continuous and stable positioning even in the case of simulated GNSS outages.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Shengyu Li, Xingxing Li, Huidan Wang, Yuxuan Zhou, Zhiheng Shen
Summary: This study proposes a tightly coupled precise point positioning/inertial navigation system/vision/LiDAR integration method for high-precision, continuous, and reliable navigation in urban environments. The experimental results demonstrate significant improvements in positioning and attitude estimation performance compared to other methods.
INFORMATION FUSION
(2023)
Article
Environmental Sciences
Chun Ma, Shuguo Pan, Wang Gao, Fei Ye, Liwei Liu, Hao Wang
Summary: Vehicular positioning in urban environments is a current research hotspot, and multi-frequency and multi-system tightly coupled positioning method can provide higher positioning accuracy. Based on the GPS/BDS-2/INS tightly coupled positioning model, this study introduces BDS-3 four-frequency observations and evaluates the performance of GPS/BDS-2/BDS-3/INS tightly coupled positioning through experiments. The results show that the GPS/BDS-2/BDS-3/INS tightly coupled positioning has significantly improved positioning accuracy compared to GPS/BDS-2/INS in urban dynamic environments.
Article
Remote Sensing
Shuchen Liu, Kaizheng Wang, Dirk Abel
Summary: To address the issues of satellite signal disturbances and poor parametrization in urban environments, an innovative scheme based on extended H-infinity filter and zonotope is proposed for high-rate and highly accurate vehicle-state estimation and protection-level generation. Experimental results demonstrate significant advantages of this scheme over the conventional extended Kalman filter in terms of navigation accuracy and robustness under various GNSS measurement parametrizations and environmental circumstances. The zonotope-based protection-level calculation is proven to be valid, computationally affordable, and feasible for real-time implementations.
Article
Environmental Sciences
Zhuoyang Zou, Wenrui Wang, Bin Wu, Lingyun Ye, Washington Yotto Ochieng
Summary: Global navigation satellite systems (GNSS) cannot be used underwater, posing a challenge for underwater navigation. To tackle this issue, we propose a tightly coupled navigation algorithm based on spatial synthesis and one-way-travel-time (OWTT) range measurement. By combining the DOA/range estimator and the tightly coupled INS/APS navigation estimator using the improved UKF, our method outperforms other navigation approaches in simulation.
Article
Engineering, Multidisciplinary
Jingwen Guo, Yilan Zhou, Shuai Zhao, Zhijian Hu
Summary: High-precision positioning in urban environments with GNSS is challenging due to outliers caused by limited satellites and environmental interference. To achieve high-precision positioning, an algorithm with effective fault detection and exclusion (FDE) for GNSS outliers is necessary. This study proposes a dynamic FDE scheme that combines a prediction-model-based method and a dissimilarity-based method to handle time series GNSS data. The results show that the proposed ARIMA-MLP model significantly improves positioning accuracy. Simulation and real experiments based on a Tokyo urban dataset validate the effectiveness of the FDE method.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Remote Sensing
Bofeng Li, Guang'e Chen
Summary: GNSS/INS combined technology is widely used for high-precision positioning outdoors. However, the performance of this system can be affected by long-term obstruction or interference with satellite signals. This limitation can be overcome by integrating additional sensors, but at an increased cost. The study focuses on enhancing the GNSS/INS combined technique using Tightly integrated Real-Time Kinematic (TRTK) technology, particularly in harsh environments. The results demonstrate that the TRTK-specified GNSS/INS combined model significantly improves positioning accuracy, especially when there is severe satellite signal occlusion.
Article
Geography, Physical
Tian Zhou, Seyyed Meghdad Hasheminasab, Ayman Habib
Summary: Unmanned aerial vehicles equipped with GNSS/INS, cameras, and LiDAR sensors are widely used in topographic mapping. Integrating image-based and LiDAR point clouds can provide a comprehensive 3D model, and ensuring good alignment between data sources is critical. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for UAV systems, which has been proven to accurately estimate system calibration parameters.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Kang Si, Peng Li, Zhi-Peng Yuan, Ke Qiao, Bo Wang, Xiao He
Summary: In this article, an improved distributionally robust Kalman filter (DRKF) based on Wasserstein and moment-based ambiguity sets is proposed to ensure accurate and robust positioning performance for the INS/GPS tightly coupled integration under uncertainties and outliers.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Aerospace
Lin Zhao, Shuo Wang, Yong Hao, Ye Wang
JOURNAL OF AEROSPACE ENGINEERING
(2019)
Article
Chemistry, Analytical
Ningbo Li, Yanbin Gao, Ye Wang, Zhejun Liu, Lianwu Guan, Xin Liu
Article
Computer Science, Information Systems
Ningbo Li, Lianwu Guan, Yanbin Gao, Zhejun Liu, Ye Wang, Hanxiao Rong
Article
Engineering, Multidisciplinary
Ye Wang, Lin Zhao, Yang Gao
MEASUREMENT SCIENCE AND TECHNOLOGY
(2020)
Article
Chemistry, Analytical
Ye Wang, Lin Zhao, Yang Gao
Summary: A method for satellite DCB estimation using a multi-spacing GNSS software receiver is proposed, which analyzes the influence of correlator spacing on DCB estimates and estimates satellite DCBs based on different correlator spacing observations. The results show that the software receiver approach is more flexible and cost-effective than the current hardware receiver-based DCB estimation approach.
Proceedings Paper
Telecommunications
Zhejun Liu, Yanbin Gao, Yunlong Sun, Ye Wang
Summary: This paper presents the problems of the vehicle navigation method based on RISS/GNSS integrated navigation system and proposes a solution to improve navigation accuracy using neural networks. The results of the experiments show that this method significantly improves the position performances and enhances the environmental adaptability of the vehicle navigation system.
CHINA SATELLITE NAVIGATION CONFERENCE PROCEEDINGS, CSNC 2022, VOL II
(2022)
