Tracking clusters and extended objects with multiple sensors

This paper develops a group tracking algorithm for the tracking of clusters of closely spaced targets as viewed by passive sensors. This problem is complex because the size and shape of the observed cluster will differ from sensor to sensor. Since a passive sensor provides projection of the objects, possible sensors in different locations will provide different projections of the 3-dimensional (3-D) shape of a cluster. Furthermore, the number of resolved objects in a cluster can vary as closely spaced targets may appear to a sensor as a single extended object. In order to track the target clusters with multiple sensois, a method is needed to characterize the size, shape and location of each cluster. The method described in this paper models the target cluster in 3-D as an effipsoid with the projection in 2-D being an effipse. The centroid and parameteis of the ethpsoid are tracked over time using measurements from widely spaced passive sensors. The filtering methods are described and performance is presented based upon tracking simulations. Application of this method to tracking extended objects with multiple sensors is also discussed