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This paper considers targets that exhibit move-stop-move motion patterns, for which we have kinematic-sensor detections. Our particular focus is how best to score the association of tracklets that result from a first stage of single-sensor kinematic tracking. The tracklets may originate from one or more sensors, and target-emission tracks may be available that typically exhibit low measurement rates...
The design and application of a nonlinear Generalized Likelihood Ratio (GLR) algorithm for target maneuver detection and estimation for short-range air-to-air missile scenarios is addressed. The problem, which is inherently nonlinear, is first reformulated into a linear problem by preprocessing the measurements. The maneuver detection algorithm then consists of a Kalman filter that is tuned to track...
In this paper the Generalized Likelihood Ratio (GLR) method for maneuver detection and estimation is applied to a generic surface-to-air engagement. In the case at hand, the technique results in system model nonlinearities which are incorporated in the algorithm to yield an "extended GLR." By employing Monte Carlo simulations, the detection and maneuver estimation performance of the GLR...
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