基于TDOA的无人机集群协同单目标定位

doi:10.12305/j.issn.1001-506X.2023.01.01

系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (1): 1-8.doi: 10.12305/j.issn.1001-506X.2023.01.01

• 电子技术 •

基于TDOA的无人机集群协同单目标定位

何胜阳¹, 杜杰朋¹, 赵雅琴¹, 王宝莹², 赵亮³, 吴龙文¹^,*

1. 哈尔滨工业大学电子与信息工程学院, 黑龙江哈尔滨 150001
2. 联发博动科技(北京)有限公司, 北京 100015
3. 中国铁路哈尔滨局集团有限公司工电检测所, 黑龙江哈尔滨 150001

收稿日期:2021-11-11 出版日期:2023-01-01 发布日期:2023-01-03
通讯作者: 吴龙文
作者简介:何胜阳(1983—), 男, 高级工程师, 博士, 主要研究方向为无线光通信、辐射源识别与定位
杜杰朋(1997—), 男, 硕士研究生, 主要研究方向为语音信号处理、声源识别和定位
赵雅琴(1976—), 女, 教授, 博士, 主要研究方向为辐射源识别、辐射源个体识别、无源定位、光通信、医学信号处理
王宝莹(1997—), 女, 工程师, 硕士, 主要研究方向为无源定位
赵亮(1983—), 男, 高级工程师, 硕士, 主要研究方向为无源定位
吴龙文(1988—), 男, 工程师, 博士, 主要研究方向为辐射源识别、辐射源个体识别、无源定位、多核学习、医学信号处理
基金资助:
国家自然科学基金(61671185);国家自然科学基金(62071153)

TDOA-based cooperative single target location using UAV cluster

Shengyang HE¹, Jiepeng DU¹, Yaqin ZHAO¹, Baoying WANG², Liang ZHAO³, Longwen WU¹^,*

1. School of Electronics & Information Engineering, Harbin Institute of Technology, Harbin 150001, China
2. Mediatek (Beijing) Inc, Beijing 100015, China
3. Institute of Industrial and Electrical Testing, China Railway Harbin Group Co. Ltd., Harbin 150001, China

Received:2021-11-11 Online:2023-01-01 Published:2023-01-03
Contact: Longwen WU

摘要/Abstract

摘要：

无源定位作为现代信息化战场中电子侦察的重要技术, 可以在自身不辐射电磁波的情况下实现对敌方目标的精确定位。以高灵活性、高安全性的无人机(unmanned aerial vehicle, UAV)集群为接收站, 研究基于到达时差测量的辐射源定位方法。作为高机动平台, UAV集群的位置误差更大, 基于该情况对Chan算法、Taylor算法进行改进, 并提出了一种粒子群泰勒协同的解算方法。与其他方法的定位结果进行对比, 仿真结果表明所提的方法定位精度接近克拉美罗下界(Cramer-Rao lower bound, CRLB), 解决了Taylor算法的初值问题。

关键词: 无源定位, 到达时间差, 粒子群优化-泰勒算法, 单目标定位

Abstract:

As an important technology of electronic reconnaissance in modern information battlefield, passive positioning technology can achieve accurate localization without emitting radio waves. Taking the unmanned aerial vehicle (UAV) cluster with high flexibility and security as receivers, this paper studies the localization method of emitter target based on time difference of arrival (TDOA) measurement. As a high maneuvering platform, UAV cluster has higher station location error, the improved algorithms of Chan algorithm and Taylor algorithm are simulated under this situation, and a new algorithm based on Taylor particle swarm cooperation is also proposed. Compared with other methods, the simulation results show that the positioning accuracy of the proposed method is close to the Cramer-Rao lower bound (CRLB), and solves the initial value problem of Taylor algorithm.

Key words: passive positioning, time difference of arrival (TDOA), particle swarm optimization (PSO)-Taylor algorithm, single target location

中图分类号:

TN971.1

何胜阳, 杜杰朋, 赵雅琴, 王宝莹, 赵亮, 吴龙文. 基于TDOA的无人机集群协同单目标定位[J]. 系统工程与电子技术, 2023, 45(1): 1-8.

Shengyang HE, Jiepeng DU, Yaqin ZHAO, Baoying WANG, Liang ZHAO, Longwen WU. TDOA-based cooperative single target location using UAV cluster[J]. Systems Engineering and Electronics, 2023, 45(1): 1-8.

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基于TDOA的无人机集群协同单目标定位

TDOA-based cooperative single target location using UAV cluster

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