论文信息 - Order statistic fast Kalman filter

Order statistic fast Kalman filter

This paper deals with the derivation of a new adaptive filtering algorithm, which takes into consideration the often encountered case of impulsive perturbations. The proposed method is a combination of a RLS-based algorithm and the Order Statistic (OS) filter, and can be seen as an extension of the LMS-type Order Statistic filter (OSLMS). In order to obtain a computational burden comparable to the OSLMS filter, our derivation is based on a fast version of the RLS algorithm-the Fast Kalman filter. We will show that the new algorithm is not a coarse extension of the OSLMS filter and that care should be taken when performing the order statistic filtering operation.

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