Journal of Electronics (China)

, Volume 24, Issue 3, pp 326–331

Biased bearings-only parameter estimation for bistatic system

Authors

    • Department of Information and Control EngineeringChangshu Institute of Technology
    • School of AutomationNanjing University of Science & Technology
  • Wang Zhiquan 
    • Department of Information and Control EngineeringChangshu Institute of Technology
    • School of AutomationNanjing University of Science & Technology
Article

DOI: 10.1007/s11767-005-0207-6

Cite this article as:
Xu, B. & Wang, Z. J. of Electron.(China) (2007) 24: 326. doi:10.1007/s11767-005-0207-6
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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.

Key words

BiasBearings-onlyBistatic systemKalman filterParameter estimation

CLC index

TP391.9

Copyright information

© Science Press 2007