Information-Theoretic Optimal Radar Waveform Selection With Multi-Sensor Cooperation for LPI Purpose

Abstract

For the complex battlefield electromagnetic environment, low probability of interception (LPI) performance has become an indispensable ability for modern radars. Waveform selection is one of the most fundamental and effective technical approaches to achieve the LPI performance of radar. However, the existing LPI waveforms are often optimized by some incomplete or weak performance representation metrics of radar or passive intercept devices (PIDs), which leads to a poor LPI performance of the designed waveform. From the perspective of information flow, this paper reformulated the processes of radar target tracking and the interception and identification of PIDs. For simplifing the LPI waveform selection optimization model, the interception and identification performance optimization criterions of PIDs are well-integrated into a comprehensive metric, which is measured by Kullback-Leibler (KL) divergence. Combining it with the radar tracking performance metric which is measured by the mutual information, an LPI waveform selection optimization model is established, which gives full consideration to both radar and PIDs performance. And, a two-round selection method is proposed to solve the optimization model. In addition, a multi-sensor cooperative tracking mechanism based on the accumulated tracking error constraint is designed for radar radiation control. The optimal waveform selection in the framework of multi-sensor cooperative tracking can improve the LPI performance of radar in both the waveform domain and the energy domain. Simulation results validate the effectiveness of the performance optimization metrics of radar and PIDs, and the superiority and feasibility of the designed waveform selection method in the multi-sensor cooperative target tracking performance and LPI performance.