Fernando Mujica Clark Atlanta Univ. and Georgia Institute of Technology (United States) Romain Murenzi Clark Atlanta Univ. (United States) Mark J. T. Smith Georgia Institute of Technology (United States)
In this paper we address the problem of target tacking when flare decoys and severe noise are present in the acquired sensor data. The input imagery is assumed to be obtained from an optical sensor mounted on the interceptor missile, where the goal of the interceptor is to neutralize the target. For this purpose algorithms running on on-board processors must extract information from the input imagery in order to steer the interceptor's course toward the target. Two challenging cases are considered here. First, the input imagery is assumed to be corrupted by additive Gaussian nose. Here we see, to determine the usefulness of our approach when low cost poor quality sensors are employed for acquisition. Second, scenarios where standard flare decoys are released by the target aircraft are considered, which represent a challenge due to the disparity in intensity of the target aircraft versus the decoys. Results using synthetically generated test sequences are presented.