An Adaptive Update-Rate Control of a Phased Array Radar for Efficient Usage of Tracking Tasks

In multi-functional radar, task scheduling algorithm should be designed such that timing resource is efficiently utilized by functions such as surveillance and tracking, and its performance is maximized. In the target tracking, the tasks are required to be executed to consider the maneuvering motion, measurement condition and required tracking performance. Frequent execution of tracking tasks results in not only precise tracking, but also waste of timing resource which is shared with other functions. Therefore, to reduce the number of unnecessary observations, the tracking task is required to be executed only when the update is needed. In this paper, the innovation, position residual, in Kalman filter is used as reference value for adjusting update rate of tracking tasks. Using feedback controller, the update rate is allocated so that predicted observation is expected to be within specified error range. In addition, targets are classified into 7 priorities according to tactical characteristics, and target's priority is also used as reference value for calculating update rate. The simulation results show that the proposed method reduces the tracking error of the target on maneuvering movement compared to fixed update rate case.