基于TDOA与GROA的信号源被动定位偏差消除技术

doi:10.3969/j.iss.0372-2012-2014.03.009

电子学报 ›› 2014, Vol. 42 ›› Issue (3): 477-484.DOI: 10.3969/j.iss.0372-2012-2014.03.009

基于TDOA与GROA的信号源被动定位偏差消除技术

郝本建, 李赞, 万鹏武, 司江勃, 齐佩汉, 关磊

西安电子科技大学ISN国家重点实验室, 陕西西安 710071

收稿日期:2012-10-11 修回日期:2013-06-28 出版日期:2014-03-25
- 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研究生，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.61072070）; 教育部博士学科点基金 (No.20110203110011）; 教育部基础科研业务费 (No.72124338）; ISN国家重点实验室自主课题 (No.ISN1101002）; 高等学校学科创新引智计划 (No.B08038）; 陕西省自然科学基金重点项目 (No.2012JZ8002）

Bias Reduction for Passive Source Localization Based on TDOA and GROA

HAO Ben-jian, LI Zan, WAN Peng-wu, SI Jiang-bo, QI Pei-han, GUAN Lei

State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, Shaanxi 710071, China

Received:2012-10-11 Revised:2013-06-28 Online:2014-03-25 Published:2014-03-25
- Supported by:
- National Natural Science Foundation of China (No.61072070); Ph.D. Programs Foundation of Ministry of Education of China (No.20110203110011); Fundamental Research Funds for Education Ministry (No.72124338); Indenpendent Project of ISN National Key Laboratory (No.ISN1101002); Overseas Expertise Introduction Project for Discipline Innovation (“111Project”) (No.B08038); Natural Science Foundation of Shaanxi Province (No.2012JZ8002)

摘要/Abstract

摘要： 本文针对Ho提出的基于TDOA（Time Difference of Arrival）与GROA（Gain Ratio of Arrival）信号源定位的代数闭式解，提出两种偏差消减方法.首先对其闭式解偏差进行了推导，然后给出BiasRed法与BiasSub法两种偏差消减算法，BiasSub法从Ho给出的解中直接减去期望偏差，BiasRed法通过分析误差表达方程并引入二次约束来提升定位估计精度；分析表明两种方法均可针对远距离信号源，在较小高斯误差情况下有效消减定位偏差，BiasRed法可将偏差降低到最大似然估计算法的水平；计算机仿真分析验证了所提算法的性能.

关键词: 信号源定位, 到达时间差, 到达增益比, 偏差消减

Abstract: We proposed two methods to reduce the bias of the well-known algebraic closed-form solution for source localization proposed by Ho using both TDOA(Time Difference of Arrival) and GROA(Gain Ratio of Arrival).The paper starts by deriving the bias of the source location estimate from Ho's solution.Two methods,called BiasSub and BiasRed,are developed to reduce the bias.The BiasSub method directly subtracts the expected bias from the solution of Ho.The BiasRed method augments the equation error formulation and imposes a constraint to improve the source location estimate.Analysis shows that both methods reduce the bias considerably for distant source when the noise is Gaussian and small.The BiasRed method is able to lower the bias to the same level as the maximum likelihood estimator.Simulations corroborate the performance of the proposed methods.

Key words: source localization, time difference of arrival (TDOA), gain ratio of arrival (GROA), bias reduction

中图分类号:

TN911.23

郝本建, 李赞, 万鹏武, 等. 基于TDOA与GROA的信号源被动定位偏差消除技术[J]. 电子学报, 2014, 42(3): 477-484.

HAO Ben-jian, LI Zan, WAN Peng-wu, et al. Bias Reduction for Passive Source Localization Based on TDOA and GROA[J]. Acta Electronica Sinica, 2014, 42(3): 477-484.

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基于TDOA与GROA的信号源被动定位偏差消除技术

Bias Reduction for Passive Source Localization Based on TDOA and GROA

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