传感器参数误差下的运动目标TDOA/FDOA无源定位算法

doi:10.7527/S1000-7527.2019.23317

电子电气工程与控制

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传感器参数误差下的运动目标TDOA/FDOA无源定位算法

孙霆, 董春曦

西安电子科技大学电子工程学院, 西安 710071

收稿日期:2019-07-26 修回日期:2019-08-20 出版日期:2020-02-15 发布日期:2019-09-30
通讯作者: 董春曦 E-mail:chxdong@mail.xidian.edu.cn

TDOA/FDOA passive localization algorithm for moving target with sensor parameter errors

SUN Ting, DONG Chunxi

School of Electronic Engineering, Xidian University, Xi'an 710071, China

Received:2019-07-26 Revised:2019-08-20 Online:2020-02-15 Published:2019-09-30

摘要/Abstract

摘要： 在运动目标无源定位系统中，许多算法的前提是精确已知传感器的位置以及速度，但实际情况下可利用的传感器的参数均会存在一些噪声扰动。针对这一问题，提出一种改进的两步加权最小二乘（TSWLS）时差（TDOA）与频差（FDOA）定位算法。该算法是一种闭式算法并且分为2步。第1步与经典的两步加权最小二乘算法相同，第2步进一步研究了额外变量与目标参数之间的关系并且建立了新的矩阵方程。随后，利用加权最小二乘技术给出了最终解。理论分析证明了在测量噪声较小时该算法能够达到克拉美罗界（CRLB）。所提算法具有计算复杂度低，实时性高的优点；另外，经过适当的维度调整，该算法同样适用于对多非相交源进行定位求解。计算机仿真进一步证明了理论分析的正确性。

关键词: 无源定位, 时差, 频差, 传感器位置误差, 克拉美罗界

Abstract: In a moving target passive localization system, the premise of many algorithms is that the position and velocity of the sensors are accurately known. However, there exists some noise disturbances in the parameters of available sensors. Aiming to solve this problem, an improved Two-Step Weighted Least Squares (TSWLS) localization algorithm using Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) is proposed. The proposed algorithm is a closed-form solution and is divided into two steps. While the first step is the same as that of the typical TSWLS method, the second step further studies the relationship between the nuisances and the target parameters, establishing a new matrix equation. Then, the final solution is given via Weighted Least Squares (WLS) technique. Theoretical analysis proves that this method can reach the Cramér-Rao Lower Bound (CRLB) at a low noise level. The proposed algorithm in this paper has the advantages of low computational complexity and high real-time performance. In addition, this method is also suitable for locating multiple disjoint sources after appropriate dimensional adjustment. Simulations further demonstrate the effectiveness of the theoretical analysis.

Key words: passive localization, time difference of arrival, frequency difference of arrival, sensor position errors, Cramér-Rao lower bound

中图分类号:

V247
TN911.7

孙霆, 董春曦. 传感器参数误差下的运动目标TDOA/FDOA无源定位算法[J]. 航空学报, 2020, 41(2): 323317-323317.

SUN Ting, DONG Chunxi. TDOA/FDOA passive localization algorithm for moving target with sensor parameter errors[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(2): 323317-323317.

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传感器参数误差下的运动目标TDOA/FDOA无源定位算法

TDOA/FDOA passive localization algorithm for moving target with sensor parameter errors

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