Abstract
Maneuvering target motion is modeled by introducing a binary random variable in the target state equation. The optimal estimate is shown to be a weighted combination of two Kalman filter estimates with weights depending on the likelihood ratio for the detection of a maneuver. A tracking scheme is proposed for maneuvering target tracking and illustrated in an example.

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