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首页> 外文会议>European Signal Processing Conference(EUSIPCO 2005); 20050904-08; Antalya(TK) >3D PASSIVE LOCALIZATION IN THE PRESENCE OF LARGE BEARING NOISE
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3D PASSIVE LOCALIZATION IN THE PRESENCE OF LARGE BEARING NOISE

机译：存在大噪声时的3D被动定位

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摘要

This paper derives three-dimensional passive bearings-only localization algorithms and examines their performance when the sensor measurements are corrupted by large additive noise. Among the algorithms studied, the maximum likelihood (ML) estimator is shown to have the best localization performance. The ML estimate is computed using the iterative Gauss-Newton (GN) algorithm with the initial guess obtained from a pseudolinear estimator. Bearing measurements are averaged over finite-length non-overlapping windows in order to reduce the computational complexity of the GN algorithm when the number of bearing measurements is large. Simulation studies are provided to illustrate the superior performance of the ML estimator in a radar localization application.
机译：本文推导了仅用于被动轴承的三维定位算法，并在传感器测量值因较大的附加噪声而损坏时检查了它们的性能。在研究的算法中，最大似然（ML）估计器显示出最佳的定位性能。使用迭代高斯-牛顿（GN）算法通过从伪线性估计器获得的初始猜测来计算ML估计。轴承测量值在有限长度的非重叠窗口上取平均值，以便在轴承测量值数量较大时降低GN算法的计算复杂性。提供仿真研究以说明ML估计器在雷达定位应用中的优越性能。

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