Performance of passive target tracking using bearing-frequency and bearings of multiple arrays

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.