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A novel maximum likelihood based estimator for bearing-only target localization

机译:一种仅用于方位目标定位的新颖的基于最大似然估计器

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In this paper, we present a new two stage maximum likelihood based estimator for bearing only target localization. In the proposed method, first a coarse and fast estimation of target location is performed. Then in the second stage, the primary estimated location and its features would be applied to extract the noise variance and restrict the search area. Our proposed method in the second stage is capable of being implemented parallelly and simulation results show that our proposed method outperforms traditional bearing only localization algorithms.
机译:在本文中,我们提出了一种新的基于两阶段最大似然性的估计器,仅用于目标定位。在提出的方法中,首先对目标位置进行粗略和快速的估计。然后在第二阶段,将主要的估计位置及其特征应用于提取噪声方差并限制搜索区域。我们提出的方法在第二阶段可以并行执行,并且仿真结果表明,我们提出的方法优于传统的仅方位定位算法。

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