Multi-scan parametric target tracking in clutter

Abstract

This paper presents a new single-target tracking filter. Similar in structure to track-oriented MHT, the Integrated track splitting (ITS) filter is a multi-scan tracking algorithm that, like IPDA, integrates target state estimation with the estimation of target existence. The ITS filter models each track as a set of components, where each component is defined with a unique measurement history which consists of zero or one measurement received each scan. For each component the state estimate and the a-posteriori probability of component existence are computed recursively. After each scan, a new component is formed from each pair of existing component, associated The probability of the new component existence is the probability that the parent component exists and that the measurement used to create the new component is the target measurement. The probability of target existence, mean and covariance of the state estimate for the track are then calculated and used for track maintenance and track output. ITS-MAP filter uses a-priori clutter density information provided by a clutter map, analytically or by some other means to better discriminate clutter from target measurements. Simulations are be used to verify the performance of the ITS-MAP algorithm and to compare its performance with that of other target tracking algorithms in a dense and non-homogeneous clutter environment.