TDOA参数估计算法

doi:10.13190/jbupt.200701.96.majm

北京邮电大学学报 ›› 2007, Vol. 30 ›› Issue (1): 96-99.doi: 10.13190/jbupt.200701.96.majm

TDOA参数估计算法

马金明

北京邮电大学信息工程学院, 北京 100876

收稿日期:2005-12-01 修回日期:1900-01-01 出版日期:2007-03-30 发布日期:2007-03-30
通讯作者: 马金明

Research on TDOA Estimating Algorithms

MA Jin-ming

School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2005-12-01 Revised:1900-01-01 Online:2007-03-30 Published:2007-03-30
Contact: MA Jin-ming

摘要/Abstract

摘要：

对基于广义互相关法（GCC）的波束到达时间差（TDOA）估计算法的捕获概率进行了分析，推导了计算捕获概率的数值算法，并在此基础上，对2种常用TDOA估计方法的算法效率进行比较．这2种方法分别是直接对2个接收信号做互相关运算来估计TDOA的方法，以及将2个接收信号分别与1个无噪声的m-序列做互相关运算来估计TDOA的方法．仿真结果表明，后者有较高的算法效率．

关键词: 波束到达时间差, m-序列, 广义互相关法;

Abstract:

The acquisition probability of two popular algorithms are investigated, which are based on general cross correlation (GCC) algorithm and widely used to evaluate time difference of arrival (TDOA) coefficients. A numerical algorithm is proposed to calculate the acquisition probability of GCC, which lays a basis for the comparison between these two algorithms. In order to evaluate the TDOA，one of these algorithms is correlating the input signals directly while the other correlates the two input signals with a noiseless m-sequence separately. The simulation result proves that the later has higher algorithm efficiency.

Key words: time difference of arrival, m-sequence, general cross correlation

中图分类号:

TN929.5

马金明. TDOA参数估计算法[J]. 北京邮电大学学报, 2007, 30(1): 96-99.

MA Jin-ming. Research on TDOA Estimating Algorithms[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2007, 30(1): 96-99.

[1]	马金明,吴伟陵. 基于 GCC算法的m-序列捕获概率的渐进性分析[J]. 北京邮电大学学报, 2003, 26(4): 46-50.
[2]	李中献,杨义先. GF(q^m)上扩展m-序列的自相关函数^*[J]. 北京邮电大学学报, 1998, 21(2): 6-9.

TDOA参数估计算法

Research on TDOA Estimating Algorithms

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics

本文评价