Cognitive Radar Waveform Design Based on Multi-objective Optimization Criteria

In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming.