<title>Multiple sensor tracking with multiple frame, probabilistic data association</title>

Abstract

Probabilistic data association algorithms are described for tracking multiple targets with multiple sensor. These algorithms employ multiple frames in the data association processing. These approaches offer improved performance over Joint Probabilistic Data Association tracking. This improved performance is observed, however, at the expense of increased processing load. Three approaches are described that employ multiple frame data association. With these algorithms, design parameters can be selected to adjust performance to suit a specific application.