A novel algorithm to counter cross-eye jamming based on a multi-target model

一种基于多目标模型的抗交叉眼干扰新方法（英文）

Cross-eye jamming is an electronic attack technique that induces an angular error in the monopulse radar by artificially creating a false target and deceiving the radar into detecting and tracking it.Presently,there is no effective anti-jamming method to counteract cross-eye jamming.In our study,through detailed analysis of the jamming mechanism,a multi-target model for a cross-eye jamming scenario is established within a random finite set framework.A novel anti-jamming method based on multitarget tracking using probability hypothesis density filters is subsequently developed by combining the characteristic differences between target and jamming with the releasing process of jamming.The characteristic differences between target and jamming and the releasing process of jamming are used to optimize particle partitioning.Particle identity labels that represent the properties of target and jamming are introduced into the detection and tracking processes.The release of cross-eye jamming is detected by estimating the number of targets in the beam,and the distinction between true targets and false jamming is realized through correlation and transmission between labels and estimated states.Thus,accurate tracking of the true targets is achieved under severe jamming conditions.Simulation results showed that the proposed method achieves a minimum delay in detection of cross-eye jamming and an accurate estimation of the target state.

交叉眼干扰是一种电子攻击手段,它通过人为构造虚假目标并欺骗雷达对其进行检测和跟踪,从而导致单脉冲雷达产生角度误差。目前还没有能够有效对抗交叉眼干扰的方法。本文通过对交叉眼干扰详细的机理分析,在随机有限集框架下建立描述典型交叉眼干扰场景的多目标模型。将目标与干扰的特征差异以及交叉眼干扰的释放过程结合,提出一种基于概率假设密度多目标滤波器的抗干扰新方法。目标与干扰的特征差异以及干扰释放的过程信息可用于优化粒子的划分。将表征目标和干扰特性的粒子身份标签引入目标检测和跟踪流程,通过波束内目标数目的实时估计检测干扰的释放,通过粒子标签与估计状态之间的关联和传递实现真实目标与虚假干扰的身份辨别,从而在强干扰条件下实现对真实目标的准确跟踪。仿真结果表明,所提抗干扰方法具有很小的干扰检测延迟以及较高的目标状态估计精度。