An algorithm of maneuvering target tracking based on interacting multiple models and fuzzy neural network

Author(s):  
Shi Jianfang ◽  
Qi Le ◽  
HuangYue
2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Gannan Yuan ◽  
Wei Zhu ◽  
Wei Wang ◽  
Bo Yin

Aiming at improving the accuracy and quick response of the filter in nonlinear maneuvering target tracking problems, the Interacting Multiple Models Cubature Information Filter (IMMCIF) is proposed. In IMMCIF, the Cubature Information Filter (CIF) is brought into Interacting Multiple Model (IMM), which can not only improve the accuracy but also enhance the quick response of the filter. CIF is a multisensor nonlinear filtering algorithm; it evaluates the information vector and information matrix rather than state vector and covariance, which can reduce the error of nonlinear filtering algorithm. IMM disposes all the models simultaneously through Markov Chain, which can enhance the quick response of the filter. Finally, the simulation results show that the proposed filter exhibits fast and smooth switching when disposing different maneuver models; it performs better than the IMMCKF and IMMUKF on tracking accuracy.


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