A cognitive active anti-jamming method based on frequency diverse array radar phase center

With the advances in electronic countermeasures (ECMS), especially the emergence and development of active jammers, there is an urgent demand for anti-jamming techniques. In this paper, we proposed a cognitive active anti-jamming method based on frequency diverse array (FDA) radar phase center. For the uniform linear FDA (ULFDA) radar, we derive the closed form of phase center, based on which the regulation effect of frequency increments is explored through Monte Carlo test. Based on the closed form of phase center, an optimization model considering the frequency increments regulation at the fixed time is established and solved by the improved swarm-immune optimization (PSO-IMMU) algorithm to realize active anti-jamming. Finally, for the jammers that implement jamming by determining the position of target, we propose a cognitive active anti-jamming method making the radar difficult for a jammer to detect or locate during the normal operation, and for the case of moving target and fixed jamming source, the Bayesian filter is applied to realize cognitive beamforming, while for the case of fixed target and moving jamming source, the auxiliary radar is applied to predict and estimate jamming source state along with the Bayesian filter. All proposed methods are verified by numerical simulation results. (C) 2020 Elsevier Inc. All rights reserved.