针对雷达主瓣干扰抑制问题，提出一种基于信干噪比(signal to interference plus noise ratio，SINR)最大化的盲提取主瓣干扰抑制方法。与盲分离不同，盲提取能够从多路混合信号中提取出感兴趣的一路分量，这更适合在多信源多通道的复杂电磁环境下进行干扰抑制。该方法在混合信号距离域建立SINR最大化的优化模型，采用粒子群优化(particle swarm optimization，PSO)算法进行求解并提取出目标回波信号实现主瓣干扰抑制。经仿真测试，该方法相较于传统的盲分离干扰抑制方法，提升了干扰抑制效果;无需信源数目估计，对通道数目要求更低，在欠定场景中依然适用;减小了计算复杂度，更适用于复杂电磁环境。
Anti-mainlobe jamming method via blind extraction based on maximizing SINR
Regarding the suppression of radar mainlobe jamming,a blind extraction method for suppressing mainlobe jamming based on maximizing the signal to interference plus noise ratio(SINR)is proposed.Unlike blind separation,blind extraction can extract interested components from multiple mixed signals,making it more suitable for jamming suppression in complex electromagnetic environments with multiple sources and channels.This method establishes an optimization model for maximizing SINR in the distance domain.The target echo signal is solved and extracted using the particle swarm optimization(PSO)algorithm to achieve mainlobe jamming suppression.Simulation testing shows that the proposed method improves the jamming suppression effect compared to traditional blind separation jamming suppression methods.It does not require estimation of the number of sources and has lower requirements for the number of channels,making it applicable in underdetermined scenarios.Additionally,it reduces computational complexity,making it more suitable for complex electromagnetic environments.
万方数据
维普
