基于新息检验的分布式雷达网虚假航迹鉴别

针对电子战飞机(electronic combat air vehicle, ECAV)编队对分布式雷达网的航迹欺骗干扰,提出了一种基于新息检验的分布式雷达网虚假航迹鉴别方法。首先,分析了ECAV引入的虚假目标位置误差,研究了其对雷达量测所造成的影响。在此基础上,采用Kalman滤波对虚假航迹进行跟踪,并在跟踪的过程中提取归一化新息平方,利用统计假设检验实现单部雷达对航迹真实性的判决,采用 m/n 逻辑加强判决结果的可靠性,突出了雷达网在信息融合方面的优势。仿真结果表明,该方法能够实现对虚假航迹的准确鉴别。

Phantom track discrimination based on inspection of innovation in distributed radar network

Aiming at phantom track deception released by electronic combat air vehicles(ECAVs) formation for distributed radar network, a discrimination method is proposed, which is based on the inspection of innovation. Firstly, the position error of the phantom target introduced by ECAV is explored with its influence for the radar measurement. And in this basis, the phantom track is filtered using the Kalman algorithm. The normalized innovation square is constructed during the filtering and the statistical testing is used to utilize the discrimination work for single radar. M/n logic is carried out to enhance the reliability of the judgement, and it also reflects the advantage of the radar network. Simulation results show that phantom track can be discriminated by using the proposed method.