Multisensor tracking of ballistic targets

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Abstract
This paper addresses the multisensor tracking of targets but considers only the special case of targets on a ballistic trajectory. The scenario consists of two radars tracking the same target. One of these radars periodically sends a track to the other radar for fusion with the track generated by the recipient. A track fusion algorithm for tracking ballistic targets is derived. This algorithm is exercised and illustrated by the Sensor Fusion Architecture Model (SFAM) computer program. Since the repeated track fusion of ballistic trajectories results in correlation that must be removed to preserve the optimality in the resultant estimate, an algorithm that requires the preservation of the last update and the error covariance matrix from another Kalman Filter (KF) also is presented. These data then are used to decorrelate the two track inputs originating at the same-source KF.

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