Response surface modeling for networked radar resource allocation

Abstract

Sensor management is an important function of any data fusion center as the output of a fusion system is dependent on the quality of the information collected. In this paper, the scheduling aspect of sensor management function is implemented using Response Surface Modeling (RSM). Applying RSM requires formulating the sensor management function as an objective function. The benefit of RSM over prior global optimization approaches is the simplification of the evaluation of this objective function to find global optima. This leads to either reduced computational requirements and/ or shorter due times for creating sensor schedules. This work shows the utility of RSM towards scheduling multiple sensors, and seeks to introduce RSM to the sensor management community. It is shown that the RSM scheduler provides a significant improvement towards reducing the number of missed targets in a surveillance radar network. This is compared to performing a uniform scanning regime (or sequential stepped scan) often employed. Very few iterations are required to provide this gain. The RSM technique also quickly determines where the most effective use of sensor resources needs to be applied. Consequently, it spends more radar dwell time on these beam locations.