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An Approximately Efficient Estimator for Moving Target Localization in Distributed MIMO Radar Systems in Presence of Sensor Location Errors

机译:在传感器位置误差存在下分布式MIMO雷达系统中移动目标定位的近似有效估计器

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摘要

In this paper, a novel algebraic closed-form method is proposed to estimate the position and velocity of a moving target in distributed multiple-input multiple-output radar systems with erroneous sensor locations by utilizing time delay and Doppler shift measurements. Unlike the existing methods that introduce nuisance parameters to build the pseudo-linear equations, the proposed method uses the singular value decomposition approach to establish new linear equations with regard to the target location with no nuisance parameters, and then derives a weighted least-squares (WLS) solution. To further improve the localization accuracy, the solution is refined through estimating the error by another WLS estimator. Based on the theoretical derivation and numerical simulations, the proposed estimator is demonstrated to be approximately unbiased and can attain the CRLB under small noise conditions. Moreover, the simulation results show that the proposed method achieves better target location accuracy than the state-of-the-art algorithms.
机译:在本文中,提出了一种新的代数闭合方法,通过利用时间延迟和多普勒换档测量来估计具有错误传感器位置的分布式多输入多输出雷达系统中的移动目标的位置和速度。与引入讨厌参数的现有方法不同,所提出的方法使用奇异值分解方法在没有滋扰参数的目标位置建立新的线性方程,然后导出加权最小二乘( WLS)解决方案。为了进一步提高本地化精度,通过估计另一个WLS估计器的误差来改进解决方案。基于理论推导和数值模拟,所提出的估计器被证明大致无偏见,并且可以在小噪声条件下获得CRLB。此外,仿真结果表明,该方法比现有技术的算法实现了比最先进的算法更好的目标位置精度。

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