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An Adaptive Singer Model Filter Based on Likelihood Function

JIANG Dong-ting;NING Jing;WAN Hong-rong;Military Representative Bureau of Naval Equipment Department in Chongqing;No.10 Research Institute of China Electronics Technology Group Corporation;  
The Singer model filter is an effective algorithm for tracking maneuvering target.Since the parameters are determined depending on prior knowledge,and they can't be changed in the filter process once determined.When the parameters determined in advance don't match with the target maneuvering,it will bring poor tracking performance.In response to these problems which were caused by model mismatching in the traditional Singer model filter,an adaptive Singer model algorithm has been posed,which is based on the model likelihood function.And the model likelihood function is calculated in all the filter process.And the Singer model acceleration parameters is adjusted adaptively according to the likelihood function's value.The simulation results show that the algorithm can track targets in different maneuvers effectively.It performances best in the comparison with traditional Singer model filter and the discrete adaptively Singer model filter.
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