吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (1): 314-321.doi: 10.13229/j.cnki.jdxbgxb201501046

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Augmented target tracking algorithm based on SRCKF for joint estimation of state and sensor systematic error

LIU Yu,HE You,WANG Hai-peng,DONG Kai   

  1. Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001,China
  • Received:2013-05-02 Online:2015-02-01 Published:2015-02-01

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Abstract: Considering three dimensional target tracking systems with unknown systematic error, in order to obtain the joint estimation of target state and sensor systematic error, an augmented target tracking algorithm based on Square-root Cubature Kalman Filter (SRCKF) is proposed. The performance of proposed estimation method is analyzed with a numerical example taking account the root mean square error and average computational cost. Simulation results show that the effectiveness of the proposed algorithm is higher than that of the algorithm based on extended Kalman filter in the aspects of estimation accuracy and filtering stability.

Key words: communication, radar networking, sensor systematic error, joint state estimation, cubature Kalman filter

CLC Number: 

  • TN957
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