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Asian Simulation Conference

AsiaSim 2022: Methods and Applications for Modeling and Simulation of Complex Systems pp 325–347Cite as

A Method of Square Root Central Difference Kalman Filter for Target Motion Analysis

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1713))

Abstract

The central differential Kalman filter (CDKF) and square root central differential Kalman filter (SR-CDKF) are widely used methods for addressing nonlinear problems in target motion analysis. However, for the bearings-only target motion analysis by single observer, sometimes the CDKF and the SR-CDKF experience the divergence problem or even filter interruption due to the observer’s mobility and system noise. To solve these problems, SR-CDKF is improved, and an adaptive singular value decomposition square root center difference Kalman filter (ASVDSR-CDKF) is proposed. The covariance square root update method based on the singular value decomposition method is deduced. The error discriminant statistics and adaptive factors are constructed. When the disturbance is too large, the adaptive factor is automatically adjusted and the square root updating form is selected. The simulation of bearings only target motion analysis is carried out under three different conditions, and the performance of CDKF, SR-CDKF, square root unscented Kalman filter (SR-UKF) and the proposed ASVDSR-CDKF method are compared. The simulation results demonstrate that the proposed method not only has high accuracy, but is also more stable than the other three methods.

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Author information

Authors and Affiliations

  1. Xi’an Precision Machinery Research Institute, Xi’an, 710000, China

    Yi Zheng, Mingzhou Wang, Yunchuan Yang & Xiangfeng Yang

  2. Kunming Branch of Xi’an Precision Machinery Research Institute, Kunming, 650118, China

    Youfeng Hu

  3. Science and Technology on Underwater Information and Control Laboratory, Xi’an, 710000, China

    Yi Zheng, Yunchuan Yang & Xiangfeng Yang

Authors
  1. Yi Zheng
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  2. Mingzhou Wang
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  3. Youfeng Hu
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  4. Yunchuan Yang
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  5. Xiangfeng Yang
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Corresponding author

Correspondence to Yi Zheng .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Wenhui Fan

  2. Beihang University, Beijing, China

    Lin Zhang

  3. Beihang University, Beijing, China

    Ni Li

  4. Beihang University, Beijing, China

    Xiao Song

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Zheng, Y., Wang, M., Hu, Y., Yang, Y., Yang, X. (2022). A Method of Square Root Central Difference Kalman Filter for Target Motion Analysis. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1713. Springer, Singapore. https://doi.org/10.1007/978-981-19-9195-0_27

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  • DOI: https://doi.org/10.1007/978-981-19-9195-0_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9194-3

  • Online ISBN: 978-981-19-9195-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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