Low probability of intercept optimization for radar network based on mutual information

This paper investigates the problem of low probability of intercept (LPI) design for radar network system and presents a novel LPI optimization strategy based on mutual information (MI) to improve the LPI performance for radar network. With the radar network system model, this paper would first derive Schleher intercept factor for radar network. Then, a novel LPI optimization strategy is proposed, where for a predefined threshold of MI to estimate the target parameters, Schleher intercept factor is minimized by optimizing transmission power allocation among netted radars in the network. Moreover, the nonlinear programming based genetic algorithm (NPGA) is employed to solve the resulting nonconvex and nonlinear optimization problem. Simulations demonstrate that our proposed scheme is valuable and effective to improve the LPI performance for radar network.