Automated Tracking with Target Amplitude Information
Donald Lerro, Yaakov Bar‐Shalom · 1990
In this paper we present a data association technique that utilizes the strength of target returns to improve tracking in a cluttered environment. The approach generalizes the Probabilistic Data Association Filter (PDAF) to include the target amplitude, a feature which is available from the detection system that provides measurements for tracking. The probabilistic modelling of target and clutter intensities is based upon collected real data. The corresponding generalized probabilistic data association is derived and improved tracking performance is demonstrated for targets with several signal to noise ratio values.