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A cognitive active anti-jamming method based on frequency diverse array radar phase center
Digital Signal Processing ( IF 2.9 ) Pub Date : 2020-11-20 , DOI: 10.1016/j.dsp.2020.102915
Jiaang Ge , Junwei Xie , Bo Wang

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.



中文翻译:

基于频分阵列雷达相位中心的认知主动抗干扰方法

随着电子对抗措施(ECMS)的发展,特别是有源干扰器的出现和发展,迫切需要抗干扰技术。本文提出了一种基于频率可变阵列(FDA)雷达相位中心的认知主动抗干扰方法。对于均匀线性FDA(ULFDA)雷达,我们推导了相位中心的闭合形式,在此基础上,通过蒙特卡洛测试探索了频率增量的调节效果。基于相位中心的封闭形式,建立了考虑固定时间频率增量调节的优化模型,并通过改进的群免疫优化算法(PSO-IMMU)进行求解,实现了主动抗干扰。最后,对于通过确定目标位置实现干扰的干扰机,我们提出了一种认知主动抗干扰方法,使雷达在正常操作过程中难以被干扰物探测或定位,对于目标移动和固定干扰源的情况,应用贝叶斯滤波器实现认知波束形成,而对于在目标固定且干扰源移动的情况下,辅助雷达与贝叶斯滤波器一起用于预测和估计干扰源的状态。数值仿真结果验证了所有提出的方法。辅助雷达与贝叶斯滤波器一起用于预测和估计干扰源状态。数值仿真结果验证了所有提出的方法。辅助雷达与贝叶斯滤波器一起用于预测和估计干扰源状态。数值仿真结果验证了所有提出的方法。

更新日期:2020-11-27
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