An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements

The autonomous vehicular navigation technology has gained more and more attention of researchers. Odometer is the most commonly used auxiliary sensor for autonomous navigation in vehicles due to its stability and high accuracy. However, in poor road conditions, vehicle skidding or slipping will seri...

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Main Authors: Shuang Pan, Chao Wang, Chunlei Zhang, Linping Feng
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/11048567/
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author Shuang Pan
Chao Wang
Chunlei Zhang
Linping Feng
author_facet Shuang Pan
Chao Wang
Chunlei Zhang
Linping Feng
author_sort Shuang Pan
collection DOAJ
description The autonomous vehicular navigation technology has gained more and more attention of researchers. Odometer is the most commonly used auxiliary sensor for autonomous navigation in vehicles due to its stability and high accuracy. However, in poor road conditions, vehicle skidding or slipping will seriously affect the navigation accuracy of INS/OD integrated navigation system. To solve this problem, we propose an improved autonomous vehicular navigation system based on robust filter recursive algorithm for stochastic system with outlier measurements. The main contributions of this study can be summarized as: 1) Incremental odometer measurement model is proposed for INS/OD integrated navigation system to solve the problem of calculation of abnormal odometer information. 2) Robust filter recursive algorithm for stochastic uncertain system with outlier measurements caused by vehicle’s slipping and skidding is proposed to improve the robustness of the INS/OD integrated navigation system. Experimental results demonstrate that the proposed method significantly improves positioning accuracy compared to traditional INS/OD integrated navigation methods, especially under vehicle skidding or slipping conditions.
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institution Matheson Library
issn 2169-3536
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publishDate 2025-01-01
publisher IEEE
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spelling doaj-art-b44b58c1ae5a4ca384f43b71177c9ff62025-07-04T23:00:44ZengIEEEIEEE Access2169-35362025-01-011311336811337810.1109/ACCESS.2025.358231911048567An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous MeasurementsShuang Pan0Chao Wang1Chunlei Zhang2Linping Feng3https://orcid.org/0009-0008-0787-7055Naval Submarine Academy, Qingdao, Shandong, ChinaNaval Submarine Academy, Qingdao, Shandong, ChinaNaval Submarine Academy, Qingdao, Shandong, ChinaNaval Submarine Academy, Qingdao, Shandong, ChinaThe autonomous vehicular navigation technology has gained more and more attention of researchers. Odometer is the most commonly used auxiliary sensor for autonomous navigation in vehicles due to its stability and high accuracy. However, in poor road conditions, vehicle skidding or slipping will seriously affect the navigation accuracy of INS/OD integrated navigation system. To solve this problem, we propose an improved autonomous vehicular navigation system based on robust filter recursive algorithm for stochastic system with outlier measurements. The main contributions of this study can be summarized as: 1) Incremental odometer measurement model is proposed for INS/OD integrated navigation system to solve the problem of calculation of abnormal odometer information. 2) Robust filter recursive algorithm for stochastic uncertain system with outlier measurements caused by vehicle’s slipping and skidding is proposed to improve the robustness of the INS/OD integrated navigation system. Experimental results demonstrate that the proposed method significantly improves positioning accuracy compared to traditional INS/OD integrated navigation methods, especially under vehicle skidding or slipping conditions.https://ieeexplore.ieee.org/document/11048567/Outlier measurementhorizontal robust Kalman filter (HRKF)dead reckoninginertial navigation
spellingShingle Shuang Pan
Chao Wang
Chunlei Zhang
Linping Feng
An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
IEEE Access
Outlier measurement
horizontal robust Kalman filter (HRKF)
dead reckoning
inertial navigation
title An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
title_full An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
title_fullStr An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
title_full_unstemmed An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
title_short An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements
title_sort improved robust filtering recursive algorithm for stochastic uncertain vehicle ins od systems with anomalous measurements
topic Outlier measurement
horizontal robust Kalman filter (HRKF)
dead reckoning
inertial navigation
url https://ieeexplore.ieee.org/document/11048567/
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