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Biased bearings-only parameter estimation for bistatic system

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Journal of Electronics (China)

Abstract

According to the biased angles provided by the bistatic sensors, the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed, respectively. Additionally, a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation. Finally, Monte-Carlo simulations are conducted in the observable scenario. Simulation results show that the proposed theory holds true, and the dual Kalman filter method can estimate state variable and biased angles simultaneously. Furthermore, the estimated results can achieve their Cramer-Rao low bounds.

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Author information

Authors and Affiliations

  1. Department of Information and Control Engineering, Changshu Institute of Technology, Changshu, 215500, China

    Xu Benlian & Wang Zhiquan

  2. School of Automation, Nanjing University of Science & Technology, Nanjing, 210094, China

    Xu Benlian & Wang Zhiquan

Authors
  1. Xu Benlian
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  2. Wang Zhiquan
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Corresponding author

Correspondence to Xu Benlian.

Additional information

Supported by the Natural Science Foundation of Jiangsu Province, China (BK2004132).

Communication author: Xu Benlian, born in 1974, male, Ph.D. Department of Information and Control Engineering, Changshu Institute of Technology, Changshu 215500, China.

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Xu, B., Wang, Z. Biased bearings-only parameter estimation for bistatic system. J. of Electron.(China) 24, 326–331 (2007). https://doi.org/10.1007/s11767-005-0207-6

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  • DOI: https://doi.org/10.1007/s11767-005-0207-6

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