Adaptive FastIMM filter for tracking a maneuvering target using nonlinear measurements

Abstract

A commonly encountered problem for tracking community is: target tracking in Cartesian plane while the measurements are delivered by radar in polar coordinates. In this paper we consider a maneuvering target tracking problem by using the Fast Interacting Multiple Model (FastIMM) algorithm. Based on the theoretical framework of the Debiased Converted Measurements Kalman Filter (DCMKF), we propose the use of the pseudo-static versions based on the well known αβ and αβγ filters. The performances of these nonlinear filters, have been assessed by means of Monte Carlo simulations and compared to that of the standard filter. The proposed filter is also suitable for real time implementation, which makes it a potential candidate for applications on embedded systems.