Adaptive resource management based on target priority in the radar networks

In sensor networks, resource management is very important for both improving the performance of the system and decreasing the expenses to accomplish the tasks of the networks. Efficient resource management can help us to control the networks appropriately and quickly. In this paper, we consider the problem of adaptive resource management based on target priority in the radar networks. We first propose a novel method to attribute priority to different targets in the radar networks. Second we propose a novel adaptive resource management method in which we adjust the quality of tracking performance adaptively based on the target priority and select the minimum number of radars to satisfy the tracking quality requirement. We select the radars based on the principle that the measurement error are as low as possible. By considering the correlation between the different measurements from the selected radars, we adopt Kalman filter and Covariance-Intersection (CI) information fusion to track the targets. Numerical simulations have verified that the proposed method to attribute target priority and the adaptive resource management are both efficient in radar networks.