GP-PDA Filter for Extended Target Tracking With Measurement Origin Uncertainty

Abstract

Extended target tracking (ETT) is an issue in high-resolution radar surveillance, ship tracking, and video tracking. Most of the previous works focus on tracking an ellipsoidal extended target without measurement origin uncertainty (missed detections and clutter). In this paper, a new estimator called the Gaussian process probabilistic data association (GP-PDA) filter is proposed to track an irregularly shaped extended target with measurement origin uncertainty. First, a generalized measurement model for ETT using the Gaussian process (GP) is presented. Both the interior scattering points and the external clutter are considered in this model. Second, a GP-based gating technique is constructed to select validated measurements to feed the filter. Third, the GP-PDA filter is proposed to simultaneously estimate the kinematic state and the contour state of the extended target with measurement origin uncertainty. It is proven that the GP-PDA is a generalized version of the classic PDA, and the latter is a special case of the former in the point target tracking applications. Finally, the GP-based posterior Cramer–Rao lower bound (PCRLB) is derived to evaluate the performance of the ETT with measurement origin uncertainty. Two cases of the PCRLB are discussed, with the number of scattering points being known and unknown. Simulation results verify the effectiveness of the proposed method.