Smoothing estimator based on maximum correntropy in non-Gaussian environment
In order to overcome the performance degradation of Kalman smoothing estimator in non-Gaussian envi-ronment,this paper proposes a smoothing estimation method based on the maximum correntropy criterion as the optimal standard,for state estimation of fixed-lag problem,which is called fixed-lag maximum correntropy smoothing estimator(FLMCS).First,another form of maximum correntropy Kalman filter is given based on the matrix transform.Then,new state variables are introduced,and online iterative equations of the proposed FLMCS are derived through an augmented system.Furthermore,state estimation error covariances are compared before and after smoothing,and performance im-provement of the proposed FLMCS is analyzed theoretically.Finally,the illustrative examples are presented to verify the effectiveness and superiority of the proposed FLMCS in non-Gaussian noise environment.
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