The effects of data association on sensor manager systems
Michael Kalandros, Lucy Y. Pao · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2000
Surveillance systems tracking multiple targets often do not have the sensing or computational resources to apply all sensors to all targets in the allocated time intervals. Hence, sensor management schemes have recently been proposed to reduce the tracking demands on these systems while minimizing the loss of tracking performance by selecting only enough sensing resources to maintain a desired covariance level for each target. However, covariance control algorithms to date have not addressed the presence of clutter measurements and the need for data association in those cases. This paper presents a method of reducing the eects of data association on covariance control algorithms through the addition of a scalar \\loss of information" parameter. Monte Carlo simulations show that without this parameter, the covariance control system is unable to maintain the desired covariance, resulting in a much larger actual covariance level and ultimately a much higher rate of track loss. Use of the ...