A novel resource scheduling method of netted radars based on Markov decision process during target tracking in clutter

Abstract

In order to improve the radio frequency stealth ability of phased array radars, a novel resource scheduling method of the radar network for target tracking in clutter is presented. Firstly, the relationship model between radar resource and tracking accuracy is built, and the sampling interval, power, and waveform will influence predicted error covariance matrix through transition matrix and measurement noise. Then, radar resource scheduling algorithm based on Markov decision process which is converted to be a binary optimization problem is proposed, and an improved binary wind-driven optimization method is presented to solve that problem. The radar and its radiation parameters will be selected for better radio frequency stealth performance and tracking accuracy. Simulation results show that the proposed algorithm not only has excellent tracking accuracy in clutter but also has better radio frequency stealth ability comparing with other methods.