基于方位-频率及多阵方位的无源目标跟踪性能研究
Performance of passive target tracking using bearing-frequency and bearings of multiple arrays
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摘要: 研究了两种利用多维信息的目标运动分析(TMA)方法:方位-频率TMA和多阵联合纯方位TMA,应用Gauss-Newton(G-N)和Levenberg--Marquardt(L-M)相结合的最优化方法,分析了最大似然估计(MLE)算法的跟踪性能,进行了仿真实验.研究结果表明利用多维信息的TMA虽然克服了常规纯方位TMA需要观测平台机动的限制,但其应用并不具备普遍性。Abstract: Two target motion analysis (TMA) methods using multi-dimension information are studied in this paper, which are TMA with bearing-frequency and TMA with multiple arrays. The optimization algorithm combining Gauss- Newton (G-N) method with Levenberg-Marquardt (L-M) method is applied to analyze the performance of target tracking with maximum likelihood estimation (MLE). Monte Carlo experiments are presented too. The results of research show that although the TMA with multi-dimension information have eliminated maneuvers needed by conventional bearing-only TMA, but the application are not of universality.