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A Moving Source Localization Method for Distributed Passive Sensor Using TDOA and FDOA Measurements

机译:基于TDOA和FDOA测量的分布式无源传感器运动源定位方法

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摘要

The conventional moving source localization methods are based on centralized sensors. This paper presents a moving source localization method for distributed passive sensors using TDOA and FDOA measurements. The novel method firstly uses the steepest descent algorithm to obtain a proper initial value of source position and velocity. Then, the coarse location estimation is obtained by maximum likelihood estimation (MLE). Finally, more accurate location estimation is achieved by subtracting theoretical bias, which is approximated by the actual bias using the estimated source location and noisy data measurement. Both theoretical analysis and simulations show that the theoretical bias always meets the actual bias when the noise level is small, and the proposed method can reduce the bias effectively while keeping the same root mean square error (RMSE) with the original MLE and Taylor-series method. Meanwhile, it is less sensitive to the initial guess and attains the CRLB under Gaussian TDOA and FDOA noise at a moderate noise level before the thresholding effect occurs.
机译:传统的移动源定位方法是基于集中式传感器的。本文提出了一种使用TDOA和FDOA测量的分布式无源传感器的移动源定位方法。该新方法首先使用最速下降算法获得源位置和速度的适当初始值。然后,通过最大似然估计(MLE)获得粗略位置估计。最后,通过减去理论偏差可以实现更精确的位置估计,而理论偏差可以通过使用估计的源位置和噪声数据测量值通过实际偏差来近似。理论分析和仿真均表明,当噪声水平较小时,理论偏差总是满足实际偏差,并且所提方法可以有效降低偏差,同时保持与原始MLE和Taylor级数相同的均方根误差(RMSE)方法。同时,它对初始猜测不太敏感,并且在阈值效应发生之前,在中等噪声水平下达到高斯TDOA和FDOA噪声下的CRLB。

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  • 来源
    《International journal of antennas and propagation》 |2016年第2期|8625039.1-8625039.12|共12页
  • 作者单位

    Zhengzhou Inst Informat Sci & Technol, Zhengzhou 86450002, Henan, Peoples R China;

    Zhengzhou Inst Informat Sci & Technol, Zhengzhou 86450002, Henan, Peoples R China;

    Zhengzhou Inst Informat Sci & Technol, Zhengzhou 86450002, Henan, Peoples R China;

    Zhengzhou Inst Informat Sci & Technol, Zhengzhou 86450002, Henan, Peoples R China;

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