Minimum mean square error based low probability of intercept optimization for radar network

Nowadays, there is a growing awareness of the requirement of low probability of intercept (LPI) in modern battlefield. In this study, a novel LPI optimization algorithm is presented for target tracking in radar network architectures. We first provide radar network signal model. Then, an effective LPI optimization algorithm is proposed, where Schleher intercept factor is utilized as an optimization metric for LPI performance. Our purpose is to minimize the intercept factor for a predetermined minimum mean square error (MMSE) threshold of the estimate of target response matrix. The resulting nonlinear and constrained problem is solved through the genetic algorithm with nonlinear constraint (GANC). Simulation results demonstrate the effectiveness of our proposed algorithm.