Adaptive sensor management in target tracking
David D. Sworder, John E. Boyd · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
Model-based, path estimation algorithms are commonly derived from a linear kinematic equation and an expansive observation model. The premise that the measurement region is all-inclusive simplifies the performance analysis, but it does not describe the relevant characteristics of some sensors. Most sensors have an active region. If the region contains the target, a noisy location measurement is made. Alternatively, no location measurement is returned. There is a clear tradeoff between measurement acuity and broad coverage. A sensor that adapts its active region to the most likely target location should achieve higher quality tracking and identification. However, effective utilization of this flexibility requires an accurate determination of the conditional distribution of the target-state. In this paper, the Gaussian Wavelet Estimator is used in an adaptive algorithm for sensor management. It is shown that the adaptive window provides performance that is superior to that achieved using a fixed window of comparable cover probability.