电子学报 ›› 2018, Vol. 46 ›› Issue (12): 2840-2847.DOI: 10.3969/j.issn.0372-2112.2018.12.004

• 学术论文 • 上一篇    下一篇

基于双基地距离的多站多外辐射源无源定位算法

赵勇胜, 赵拥军, 赵闯   

  1. 解放军信息工程大学导航与空天目标工程学院, 河南郑州 450001
  • 收稿日期:2016-12-27 修回日期:2018-03-07 出版日期:2018-12-25
    • 作者简介:
    • 赵勇胜 男,1990年出生于江苏连云港.现为解放军信息工程大学导航与空天目标工程学院博士研究生,主要研究方向为无源雷达信号处理.E-mail:ethanchioa@aliyun.com;赵拥军 男,1964年出生于河南封丘,博士.现为解放军信息工程大学导航与空天目标工程学院教授、博士生导师,主要研究方向为雷达信号处理和阵列信号处理.E-mail:zhaoyongjuntg@126.com;赵闯 男,1978年出生于河北辛集.现为解放军信息工程大学导航与空天目标工程学院副教授,主要研究方向为雷达信号处理.E-mail:rushzhaotg@163.com
    • 基金资助:
    • 国家自然科学基金 (No.61703433)

Multi-transmitter Multi-receiver Passive Location Using Bistatic Range Measurements

ZHAO Yong-sheng, ZHAO Yong-jun, ZHAO Chuang   

  1. School of Navigation and Aerospace Engineering, PLA Information Engineering University, Zhengzhou, Henan 450001, China
  • Received:2016-12-27 Revised:2018-03-07 Online:2018-12-25 Published:2018-12-25

摘要: 针对利用多个外辐射源和多个接收站的无源雷达目标定位场景,提出了一种利用三步加权最小二乘的双基地距离(Bistatic Range,BR)定位问题代数解.首先,在第一步加权最小二乘估计中,通过引入多个辅助参数,将BR观测方程线性化,并得到目标位置粗估计;在后两步加权最小二乘估计中利用辅助参数与目标位置参数的约束关系来提高目标位置的估计精度.对算法理论误差分析表明,其定位精度可以达到克拉美罗界.蒙特卡罗仿真结果表明,算法的定位精度优于现有算法.

关键词: 无源定位, 多站多外辐射源, 双基地距离, 加权最小二乘

Abstract: This paper investigates the problem of locating a target using a passive radar system with multiple transmitters and multiple receivers. The bistatic range (BR), which corresponds to the sum of transmitter-to-target and target-to-receiver distances is used as the measurement. An algebraic solution employing three-step weighted least squares (3WLS) minimizations is proposed. In the first stage, the BR measurements are linearized by introducing multiple additional parameters and a WLS minimization is used to obtain a rough estimate; then in the latter two stages, the relationship between the additional parameters and the target location parameters is utilized to refine the estimate. Theoretical accuracy analysis indicates that the proposed algorithm can achieve the Cramer row lower bound (CRLB), and Monte-Carlo simulations demonstrate the proposed algorithm outperforms existing algorithms.

Key words: passive location, multi-transmitter multi-receiver, bistatic range, weighted least squares

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