何漆龙, 黄川, 邱星晔, 等. 基于 5G 信号的分布式被动雷达目标定位方法[J]. 信号处理, 2024, 40(9): 1621-1632. DOI: 10.12466/xhcl.2024.09.005.
引用本文: 何漆龙, 黄川, 邱星晔, 等. 基于 5G 信号的分布式被动雷达目标定位方法[J]. 信号处理, 2024, 40(9): 1621-1632. DOI: 10.12466/xhcl.2024.09.005.
HE Qilong, HUANG Chuan, QIU Xingye, et al. Distributed passive radar target localization method based on 5G signal[J]. Journal of Signal Processing, 2024, 40(9): 1621-1632. DOI: 10.12466/xhcl.2024.09.005.
Citation: HE Qilong, HUANG Chuan, QIU Xingye, et al. Distributed passive radar target localization method based on 5G signal[J]. Journal of Signal Processing, 2024, 40(9): 1621-1632. DOI: 10.12466/xhcl.2024.09.005.

基于 5G信号的分布式被动雷达目标定位方法

Distributed Passive Radar Target Localization Method Based on 5G Signal

  • 摘要: 随着第五代(5th Generation, 5G)无线通信技术的快速发展,基于5G信号的被动雷达技术在目标监测方面具有很大的应用潜力。特别是在分布式体制下,被动雷达系统能够有效整合多个站点信息,完成复杂的目标探测任务,为目标定位技术带来新的思路和方法。然而,在5G基站分布式场景下,基站大多部署在复杂环境中,导致目标定位过程中测量误差增大,从而限制了目标定位的精度。本文针对这一问题,结合5G独特的定位参考信号(Positioning Reference Signal, PRS),提出了一种迭代三步加权最小二乘(Iterative Three-step Weighted Least Squares, I3WLS)算法,用于实现分布式被动雷达目标精准定位。首先建立了基于5G信号的目标回波模型,通过回波时延信息构建了到达距离差(Range Difference of Arrival, RDOA)方程,然后利用加权最小二乘算法对目标位置初始估计值进行参数更新和迭代优化,最后通过线性变换距离约束方程保留目标位置的一次项,从而得到了目标的精确估计值。仿真结果表明,与现有方法相比,所提算法具有更好的定位精度和更强的鲁棒性,在被动雷达目标定位领域具有广阔的应用前景。

     

    Abstract: ‍ ‍With the rapid development of 5th generation (5G) wireless communication technology, passive radar technology based on 5G signal has shown great potential for application in target monitoring. In particular, in a distributed system, a passive radar system could combine information from multiple stations distributed over a large range to jointly complete complex target detection tasks, opening up novel ideas and methods for passive radar target positioning technology. However, in the distributed scenario of 5G base stations, most of them are deployed in complex environments, leading to increased measurement errors in the target localization process, thereby limiting the accuracy of target localization. Therefore, developing novel methods and techniques to improve the accuracy of target localization in a distributed 5G base station environment was necessary. This article introduces a solution to the problem by utilizing the unique positioning reference signal (PRS) of 5G and proposing an iterative three-step weighted least squares (I3WLS) algorithm for accurate target localization in distributed passive radar systems. The first step in the proposed algorithm was to establish a target echo model based on 5G signal and construct the range difference of arrival (RDOA) equation using echo delay information. The second step involved the use of the weighted least squares algorithm to update and iteratively optimize the initial estimation value of the target position. Finally, the third step utilized the linear transformation distance constraint equation to retain the first-order term of the target position, resulting in an accurate estimation value of the target. The simulation results demonstrate that the proposed I3WLS algorithm outperformed existing methods in terms of positioning accuracy and robustness. The algorithm’s ability to accurately localize targets in distributed passive radar systems shows promise for practical applications in various fields, including surveillance, navigation, and communication. In conclusion, the combination of 5G signal and the proposed I3WLS algorithm offers a promising approach for achieving precise target localization in distributed passive radar systems. The algorithm’s ability to mitigate positioning errors and optimize the estimation of target positions demonstrates its potential to advance the field of passive radar target positioning.

     

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