Manoeuvre detection and target tracking in uncertain systems using FIR filters

The authors present a novel tracking method for manoeuvering targets using FIR (finite impulse response) filtering techniques, which are known to be robust to modeling errors, in order to overcome the filter divergence problem under model uncertainties. The method is based on the input estimation approach. The method can be applied to real-time tracking problems for maneuvering targets, since its computational burden is small and it works correctly even under modeling errors, owing to the robustness of FIR filters. Computer simulations illustrate the superior performance of the proposed method compared with existing methods