Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking

In this paper, an improved interactive multiple model adaptive strong tracking random weighted cubature Kalman filter (IIMM-ASTRWCKF) algorithm is developed to overcome the low tracking accuracy and easy divergence when dealing with complex maneuvering situations. The algorithm is improved in two as...

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Main Authors: Jian Ma, Xiaoting Guo
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9154388/
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author Jian Ma
Xiaoting Guo
author_facet Jian Ma
Xiaoting Guo
author_sort Jian Ma
collection DOAJ
description In this paper, an improved interactive multiple model adaptive strong tracking random weighted cubature Kalman filter (IIMM-ASTRWCKF) algorithm is developed to overcome the low tracking accuracy and easy divergence when dealing with complex maneuvering situations. The algorithm is improved in two aspects: On the one hand, ASTRWCKF is used as the sub filter of IMM algorithm to filter different motion models. By introducing the random weight factor to replace the original weight factor, the accuracy of the algorithm is improved. At the same time, the adaptive strong tracking filter is added to update the prediction covariance matrix and noise covariance matrix for the stability of the algorithm. On the other hand, this algorithm proposes a new method to improve the probability conversion accuracy of IMM by adding time-varying factor to adjust Markov probability transfer matrix. Compared with the performance of IMM-CKF and in dealing with maneuvering problems, IIMM-ASTRWCKF algorithm has better tracking accuracy in solving maneuvering problem.
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spelling doaj.art-246baf0185534bebac6a0597f057eb362022-12-21T22:23:42ZengIEEEIEEE Access2169-35362020-01-01814309514310310.1109/ACCESS.2020.30135619154388Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target TrackingJian Ma0https://orcid.org/0000-0003-2135-2665Xiaoting Guo1https://orcid.org/0000-0002-4892-1058Key Laboratory of Instrumentation Science and Dynamic Measurement, Ministry of Education, School of Instruments and Electronics, North University of China, Taiyuan, ChinaKey Laboratory of Instrumentation Science and Dynamic Measurement, Ministry of Education, School of Instruments and Electronics, North University of China, Taiyuan, ChinaIn this paper, an improved interactive multiple model adaptive strong tracking random weighted cubature Kalman filter (IIMM-ASTRWCKF) algorithm is developed to overcome the low tracking accuracy and easy divergence when dealing with complex maneuvering situations. The algorithm is improved in two aspects: On the one hand, ASTRWCKF is used as the sub filter of IMM algorithm to filter different motion models. By introducing the random weight factor to replace the original weight factor, the accuracy of the algorithm is improved. At the same time, the adaptive strong tracking filter is added to update the prediction covariance matrix and noise covariance matrix for the stability of the algorithm. On the other hand, this algorithm proposes a new method to improve the probability conversion accuracy of IMM by adding time-varying factor to adjust Markov probability transfer matrix. Compared with the performance of IMM-CKF and in dealing with maneuvering problems, IIMM-ASTRWCKF algorithm has better tracking accuracy in solving maneuvering problem.https://ieeexplore.ieee.org/document/9154388/Maneuvering targetIMMASTRWCKF
spellingShingle Jian Ma
Xiaoting Guo
Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
IEEE Access
Maneuvering target
IMM
ASTRWCKF
title Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
title_full Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
title_fullStr Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
title_full_unstemmed Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
title_short Combination of IMM Algorithm and ASTRWCKF for Maneuvering Target Tracking
title_sort combination of imm algorithm and astrwckf for maneuvering target tracking
topic Maneuvering target
IMM
ASTRWCKF
url https://ieeexplore.ieee.org/document/9154388/
work_keys_str_mv AT jianma combinationofimmalgorithmandastrwckfformaneuveringtargettracking
AT xiaotingguo combinationofimmalgorithmandastrwckfformaneuveringtargettracking