Simulation Experiment and Analysis of GNSS/INS/LEO/5G Integrated Navigation Based on Federated Filtering Algorithm

This article examines the positioning effect of integrated navigation after adding an LEO constellation signal source and a 5G ranging signal source in the context of China’s new infrastructure construction. The tightly coupled Kalman federal filters are used as the algorithm framework. Each signal source required for integrated navigation is simulated in this article. At the same time, by limiting the range of the azimuth angle and visible height angle, different experimental scenes are simulated to verify the contribution of the new signal source to the traditional satellite navigation, and the positioning results are analyzed. Finally, the article compares the distribution of different federal filtering information factors and reveals the method of assigning information factors when combining navigation with sensors with different precision. The experimental results show that the addition of LEO constellation and 5G ranging signals improves the positioning accuracy of the original INS/GNSS by an order of magnitude and ensures a high degree of positioning continuity. Moreover, the experiment shows that the federated filtering algorithm can adapt to the combined navigation mode in different scenarios by combining different precision sensors for navigation positioning.

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Fault-Tolerant Filtering Algorithm for SINS/BDS Tightly-coupled Integrated Navigation System

2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) ◽

10.1109/gncc42960.2018.9019084 ◽

2018 ◽

Author(s):

Zhou Benchuan ◽

Lu Hao ◽

Xu Jianyun ◽

Zhang Hongob

Keyword(s):

Navigation System ◽

Fault Tolerant ◽

Integrated Navigation ◽

Integrated Navigation System ◽

Filtering Algorithm ◽

Tightly Coupled

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Research on Wavelet Singularity Detection Based Fault-Tolerant Federated Filtering Algorithm for INS/GPS/DVL Integrated Navigation System

Journal of Applied Mathematics ◽

10.1155/2014/825726 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 5

Author(s):

Jianhua Cheng ◽

Daidai Chen ◽

Rene Landry Jr. ◽

Lin Zhao ◽

Dongxue Guan

Keyword(s):

Navigation System ◽

Fault Tolerant ◽

Integrated Navigation ◽

Singularity Detection ◽

Integrated Navigation System ◽

Lipschitz Exponent ◽

Filtering Algorithm ◽

Federated Filtering ◽

Soft Faults ◽

Modulus Maxima

Soft faults in navigation sensors will lead to the degradation of the accuracy and reliability of integrated navigation system. To solve this problem, a wavelet analysis and signal singularities based soft fault detection method are given out. To find signal singularities and detect the faults, the modulus maxima values are calculated after the wavelet transform of original signal. By calculating the Lipschitz exponent using the modulus maxima value at the fault point, the fault types are distinguished. Then, a fault-tolerant federated filtering algorithm for the calibration of INS/GPS/DVL integrated navigation system is proposed. Simulations are conducted and results show that sensor soft faults can be detected accurately. By effectively isolating the fault and refactoring information, the accuracy and reliability of navigation system are improved.

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Simplified Federated Filtering Algorithm With Different States in Local Filters

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4002071 ◽

2010 ◽

Vol 133 (1) ◽

Author(s):

Guoliang Liu ◽

Jian Xie ◽

Shizuo Yan ◽

Wenyi Qiang

Keyword(s):

Kalman Filter ◽

Kalman Filtering ◽

Navigation Systems ◽

Integrated Navigation ◽

Transition Matrices ◽

Filtering Algorithm ◽

Federated Kalman Filter ◽

Federated Filtering ◽

Local Filters ◽

Computation Load

In this paper, to reduce the computation load of federated Kalman filters, a simplified federated filtering algorithm for integrated navigation systems is presented. It has been known that the per-cycle computation load grows roughly in proportion to the number of states and measurements for a single centralized Kalman filter. Hence, the states that have poor estimation accuracies are removed from local filters, so that the per-cycle computation load is reduced accordingly. Local filters and master filter of the federated Kalman filter may have different states, so the transition matrices are required to combine the outputs from the local filters and the master filter properly and to reset the global solution into the local filters and the master filter correctly. An experiment demonstrates that the proposed algorithm effectively reduces the computation load, compared with the standard federated Kalman filtering algorithm.

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A Novel Method of Fault Detection and Identification in a Tightly Coupled, INS/GNSS-Integrated System

Sensors ◽

10.3390/s21092922 ◽

2021 ◽

Vol 21 (9) ◽

pp. 2922

Author(s):

Fan Zhang ◽

Ye Wang ◽

Yanbin Gao

Keyword(s):

Fault Detection ◽

Parametric Bootstrap ◽

Integrated System ◽

Range Data ◽

Navigation Systems ◽

Integrated Navigation ◽

Multiple Faults ◽

Detection And Identification ◽

Fault Detection And Identification ◽

Tightly Coupled

Fault detection and identification are vital for guaranteeing the precision and reliability of tightly coupled inertial navigation system (INS)/global navigation satellite system (GNSS)-integrated navigation systems. A variance shift outlier model (VSOM) was employed to detect faults in the raw pseudo-range data in this paper. The measurements were partially excluded or included in the estimation process depending on the size of the associated shift in the variance. As an objective measure, likelihood ratio and score test statistics were used to determine whether the measurements inflated variance and were deemed to be faulty. The VSOM is appealing because the down-weighting of faulty measurements with the proper weighting factors in the analysis automatically becomes part of the estimation procedure instead of deletion. A parametric bootstrap procedure for significance assessment and multiple testing to identify faults in the VSOM is proposed. The results show that VSOM was validated through field tests, and it works well when single or multiple faults exist in GNSS measurements.

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Intelligent fault-tolerant algorithm with two-stage and feedback for integrated navigation federated filtering

Journal of Systems Engineering and Electronics ◽

10.3969/j.issn.1004-4132.2011.02.014 ◽

2011 ◽

Vol 22 (2) ◽

pp. 274-282 ◽

Cited By ~ 5

Author(s):

Li Cong ◽

Honglei Qin ◽

Zhanzhong Tan

Keyword(s):

Fault Tolerant ◽

Integrated Navigation ◽

Two Stage ◽

Federated Filtering

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Heading Measurement Based on Ultrasonic and Magnetic Compass

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.341-342.896 ◽

2013 ◽

Vol 341-342 ◽

pp. 896-900

Author(s):

Bao Jiang Sun ◽

Yue Xu

Keyword(s):

Navigation System ◽

Simulation Experiment ◽

Measurement Data ◽

Magnetic Compass ◽

Positioning System ◽

Integrated Navigation ◽

Adaptive Kalman Filter ◽

Integrated Navigation System ◽

Advantages And Disadvantages ◽

Measurement Principle

Describes briefly ultrasonic positioning system (UPS) and digital magnetic compass (DMC) heading measurement principle,analyzed the advantages and disadvantages of each option. To improve the accuracy of the heading measurement, As the theoretical basis of adaptive Kalman filter, designed a kind of ups and dmc integrated navigation system. Based on both real measurement data, made a simulation experiment and confirmed the feasibility of the navigation system.

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Improved high-degree cubature Kalman filter based on resampling-free sigma-point update framework and its application for inertial navigation system-based integrated navigation

Aerospace Science and Technology ◽

10.1016/j.ast.2021.106905 ◽

2021 ◽

pp. 106905

Author(s):

Bingbo Cui ◽

Xinhua Wei ◽

Xiyuan Chen ◽

Aichen Wang

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Inertial Navigation System ◽

Inertial Navigation ◽

Integrated Navigation ◽

Sigma Point ◽

Cubature Kalman Filter ◽

High Degree

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An INS/Geomagnetic Integrated Navigation Algorithm Based on Matching Strategy and Hierarchical Filtering

Electronics ◽

10.3390/electronics8040460 ◽

2019 ◽

Vol 8 (4) ◽

pp. 460

Author(s):

Xiusheng Duan ◽

Jing Xiao ◽

Xiaohui Qi ◽

Yifei Liu

Keyword(s):

Magnetic Measurements ◽

Inertial Navigation ◽

State Equation ◽

Integrated Navigation ◽

Matching Algorithm ◽

Filtering Algorithm ◽

Navigation Algorithm ◽

Physical Experiments ◽

Matching Strategy ◽

Navigation Information

To improve the positioning accuracy of an inertial/geomagnetic integrated navigation algorithm, a combined navigation method based on matching strategy and hierarchical filtering is proposed. First, the PDA-ICCP geomagnetic matching algorithm is improved. On basis of evaluating the distribution of magnetic measurements, a number of controllable magnetic values are regenerated to participate in the geomagnetic matching algorithm (GMA). As a result, accuracy of the matching algorithm is ensured and its efficiency is improved. Secondly, the integrated navigation filter is designed based on the hierarchical filtering strategy, in which the navigation information of the geomagnetic matching module and inertial navigation module are respectively filtered and fused in the main filter. In this way, the shortcoming that GMA is unable to provide continuous and real-time navigation information is overcome. Meanwhile, precision of the inertial/geomagnetic integrated navigation algorithm is improved. Finally, the feasibility and validity of the proposed algorithm are verified by simulation and physical experiments. Compared with the integrated filtering algorithm which directly uses the error equation of inertial navigation system (INS) as the state equation, the proposed hierarchical filtering algorithm can achieve higher positioning precision.

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