23 June 1997 Multisensor distributed extended Kalman filtering algorithm and its application to radar/IR target tracking
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Abstract
A multisensor distributed extended Kalman filtering algorithm is presented for nonlinear system, in which the dynamic equation of the system and the equations of sensor's measurements are linearized in the global estimate and global prediction respectively and the suboptimal global estimate based on all available information can be reconstructed from the estimates computed by local sensors based solely on their own local information and transmitted to the data fusion center. An analysis of the properties of the algorithm presented here shows that the global estimate has higher precision than the local one and smaller linearization error than the existing method. Finally, an application of the algorithm to radarflR tracking of a maneuvering target is illustrated. Simulation results show the effectiveness of the algorithm. Keywords: extended Kalman filtering, target tracking, distributed estimation, data fusion
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ningzhou Cui, Weixing Xie, Xiongnan Yu, Yuanliang Ma, "Multisensor distributed extended Kalman filtering algorithm and its application to radar/IR target tracking", Proc. SPIE 3086, Acquisition, Tracking, and Pointing XI, (23 June 1997); doi: 10.1117/12.277179; https://doi.org/10.1117/12.277179
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