Journal of Systems Engineering and Electronics ›› 2010, Vol. 32 ›› Issue (7): 1415-1418.doi: 10.3969/j.issn.1001506X.2010.07.015

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Unscented Kalman filter with forwardbackward prediction for single observer passive location and tracking

ZHANG Gangbing, LIU Yu, XU Jiajia   

  1. (Coll. of Information Science and Technology, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210016, China)
  • Online:2010-07-20 Published:2010-01-03

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Abstract:

A novel unscented Kalman filter (UKF) algorithm is proposed to improve convergence speed and estimation accuracy. The backward prediction and the state update procedure improve the estimation accuracy of the last state estimate and reduce the current state prediction error. A more accurate current state estimate could be gotten with more precise initial condition. Simulation results show that the performance of the proposed algorithm outperforms that of the conventional iterated UKF in both convergence speed and estimation accuracy.

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