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Performance Analysis of Single-Step Localization Method Based on Matrix Eigen-Perturbation Theory with System Errors

机译:基于带有系统误差的矩阵特征摄动理论的单步定位方法性能分析

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Direct position determination (DPD) is a novel technique in passive localization field recently, receiving superior localization performance compared with the conventional two-step method. The DPD estimator using Doppler shifts is first proposed by Weiss, but it is not suitable for antenna arrays. Additionally, the performance analysis of this method with system errors is absent. This study discusses the single-step localization problem based on moving arrays and exhibits the performance analysis via matrix eigen-perturbation theory with system errors. First, the DPD method using angle of arrival and Doppler shifts is introduced. Then, by adding the eigenvalue perturbations to the estimated Hermitian matrix, the asymptotic linear formulation of localization errors is derived. Consequently, the mean square error of the DPD method is available. Finally, Cramér–Rao bound without system errors is presented, providing a benchmark for the best localization precision and revealing the influence of system errors on the localization precision. Simulation results demonstrate the theoretical analysis in this study.
机译:直接位置确定(DPD)是近来被动定位领域中的一种新技术,与传统的两步法相比,它具有优越的定位性能。 Weps首先提出了使用多普勒频移的DPD估计器,但它不适用于天线阵列。此外,这种方法的性能分析也没有系统错误。本研究讨论了基于移动阵列的单步定位问题,并通过具有系统误差的矩阵特征摄动理论展示了性能分析。首先,介绍了使用到达角和多普勒频移的DPD方法。然后,通过将特征值扰动添加到估计的埃尔米特矩阵,得出定位误差的渐近线性公式。因此,可以使用DPD方法的均方误差。最后,提出了没有系统错误的Cramér–Rao界,为最佳定位精度提供了基准,并揭示了系统误差对定位精度的影响。仿真结果证明了本文的理论分析。

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