电子学报 ›› 2015, Vol. 43 ›› Issue (10): 1888-1897.DOI: 10.3969/j.issn.0372-2112.2015.10.002

• 学术论文 • 上一篇    下一篇

基于TDOAs与FDOAs的多信号源及感知节点联合定位算法

郝本建1, 朱建峰2, 李赞1, 肖嵩1, 关磊1, 万鹏武1   

  1. 1. 西安电子科技大学ISN国家重点实验室, 陕西西安 710071;
    2. 通信信息控制和安全技术重点实验室, 浙江嘉兴 314033
  • 收稿日期:2013-01-28 修回日期:2013-06-07 出版日期:2015-10-25 发布日期:2015-10-25
  • 作者简介:郝本建 男,1982年出生于山东省泰安市,现为西安电子科技大学ISN国家重点实验室博士后,主要研究方向:无线通信,电磁频谱监测,无线传感器网络,信号源定位与跟踪.E-mail:bjhao@xidian.edu.cn
  • 基金资助:

    国家自然科学基金(No.61401323,No.61301179);中国博士后科学基金(No.2014M550479);西安电子科技大学基本科研业务费(No.7214605403,No.7215605401)

Joint Multiple Disjoint Sources and Sensors Localization Based on TDOAs and FDOAs

HAO Ben-jian1, ZHU Jian-feng2, LI Zan1, XIAO Song1, GUAN Lei1, WAN Peng-wu1   

  1. 1. State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, Shaanxi 710071, China;
    2. Science and Technology on Communication Information Security Control Laboratory, Jiaxing, Zhejiang 314033, China
  • Received:2013-01-28 Revised:2013-06-07 Online:2015-10-25 Published:2015-10-25

摘要:

感知节点存在位置误差与速度误差的情况下,本文采用信号到达时间差(TDOAs)与到达频率差(FDOAs)信息,针对多信号源被动定位与感知节点进行位置及速度的同步优化问题进行了研究.在Sun和Ho前期工作中,只对多个不相关信号源进行了定位,并没有同时给出感知节点位置及速度的优化解,在很多实际应用中,对多个信号源进行被动定位的同时需要对感知节点的位置及速度信息进行优化;本文所提出的算法对前期算法进行了提升,被定位信号源与感知节点的位置及速度可同时较好地达到克拉美罗下界(CRLB);计算机仿真对本文理论推导进行了验证.

关键词: 到达时间差, 到达频率差, 多信号源, 被动定位, 节点位置及速度误差

Abstract:

In the presence of sensor position and velocity errors, this paper considers the problem of simultaneously locating multiple disjoint sources and refining erroneous of sensor positions and velocities using time differences of arrival (TDOA) and frequency differences of arrival (FDOA).The previous work by Sun and Ho to solve this problem provided an efficient estimator for multiple disjoint sources, but it cannot provide optimum accuracy for the sensor positions and sensor velocities.In many practical applications, it's necessary and helpful to refine sensor locations and velocities while localizing multiple sources.The proposed method improves the previous method so that both the source and the sensor position and velocity estimates can achieve the Cramér-Rao lower bound (CRLB) accuracy very well over small noise region.The theoretical derivation is corroborated by simulations.

Key words: time differences of arrival (TDOAs), frequency differences of arrival (FDOAs), multiple sources, passive localization, sensor position and velocity errors

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