An EM-based adaptive multiple target tracking filter

Abstract

Tracking targets of interest is one of the major research areas in radar surveillance systems. We formulate the problem as incomplete data estimation and apply EM to the MAP estimate. The resulting filter has a recursive structure analogous to the Kalman filter. The advantage is that the measurement-update deals with multiple measurements in parallel and the parameter-update estimates the system parameters on the fly. Experiments tracking separate targets in parallel show that tracking maintenance ratio of the proposed system is better than that of NNF and RMS position error is smaller than that of PDAF Also, the system parameters are correctly obtained even from incorrect initial values. Copyright (C) 2001 John Wiley Sons, Ltd.