Switching Extensible FIR Filter Bank for Adaptive Horizon State Estimation With Application


Horizon size is an important parameter that affects the estimation performance of finite impulse response (FIR) filters. In this brief, we have a tendency to propose a novel adaptive horizon approach that aims to adapt the horizon size at each time point. The approach suggests providing state estimation employing a bank of FIR filters known as the switching extensible FIR filter bank (SEFFB), that consists of several FIR filters operating using totally different horizon sizes. The horizon sizes and the number of FIR filters in the SEFFB are tailored to changes in system characteristics using most likelihood. The SEFFB is applied to focus on tracking employing a ground moving target indicator. A vital performance improvement is demonstrated using the SEFFB as compared with a single FIR filter using constant optimal horizon size.

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