总体最小二乘波达方向估计方法

doi:10.19678/j.issn.1000-3428.0052052

计算机工程 ›› 2019, Vol. 45 ›› Issue (9): 55-59. doi: 10.19678/j.issn.1000-3428.0052052

总体最小二乘波达方向估计方法

汪海, 张梦晗, 崔逊学

陆军炮兵防空兵学院信息工程系, 合肥 230031

收稿日期:2018-07-09 修回日期:2018-09-14 出版日期:2019-09-15 发布日期:2019-09-03
作者简介:汪海(1994-),男,硕士研究生,主研方向为传感器网络;张梦晗,硕士研究生;崔逊学,教授、博士。
基金资助:
国家自然科学基金"基于TDOA测向交叉的脉冲声源定位优化方法研究"（61672532）。

Total Least Squares Method for Direction of Arrival Estimation

WANG Hai, ZHANG Menghan, CUI Xunxue

Department of Information Engineering, Army Academy of Artillery and Air Defense, Hefei 230031, China

Received:2018-07-09 Revised:2018-09-14 Online:2019-09-15 Published:2019-09-03
Supported by:
This work is supported by China Southern Power Grid Corporation Science and Technology Project (No.ZDKJXM20160007).

摘要/Abstract

摘要： 在到达时间差定位技术中，当传感器位置坐标存在误差时，最小二乘法（LS）所得估计值不再具有最优无偏性，导致测向精度下降。针对该问题，提出基于总体最小二乘的测向方法。将非线性的观测方程转化为伪线性方程，构成增广矩阵并对其进行奇异值分解，从而得到目标位置。理论分析和仿真结果表明，与经典的LS法和LS-Tylar法相比，该方法的定位精度较高。

关键词: 到达时间差, 测向, 总体最小二乘, 奇异值分解, 克拉美罗下界

Abstract: In the Time Difference of Arrival(TDOA) positioning technology,when the position coordinates of the sensor have errors,the estimated value obtained by the Least Squares(LS) method no longer has the best unbiasedness,resulting in a decrease in the direction finding accuracy.Aiming at this problem,a direction finding method based on Total Least Squares(TLS) is proposed.By transforming the nonlinear observation equation into pseudo-linear equation,the augmented matrix is constructed and the singular value decomposition is carried out to achieve the target position.Theoretical analysis and simulation results show that this method is more accurate than the classical LS method and LS-Tylar method.

Key words: Time Difference of Arrival(TDOA), direction finding, Total Least Squares(TLS), singular value decomposition, Cramer-Rao Lower Bound(CRLB)

中图分类号:

TN911

汪海, 张梦晗, 崔逊学. 总体最小二乘波达方向估计方法[J]. 计算机工程, 2019, 45(9): 55-59.

WANG Hai, ZHANG Menghan, CUI Xunxue. Total Least Squares Method for Direction of Arrival Estimation[J]. Computer Engineering, 2019, 45(9): 55-59.

https://www.ecice06.com/CN/Y2019/V45/I9/55

图/表 5

20190912182246

20190912182249

20190912182252

20190912182255

20190912182258

参考文献

[1] FLUCKIGER M,NEILD A,NELSON B J.Optimization of receiver arrangements for passive emitter localization methods[J].Ultrasonics,2012,52(3):447-455.
[2] 张卓然,叶广强,赵晓林.强跟踪修正SRCKF算法在单站无源跟踪中的应用[J].计算机工程,2016,42(7):315-321.
[3] CUI Xunxue,YU Kegen,LU Songsheng.Evolutionary TDOA-based direction finding methods with 3D acoustic array[J].IEEE Transactions on Instrumentation and Measurement,2015,64(9):2347-2359.
[4] HO K C,XUE Wenwei.An accurate algebraic solution for moving source location using TDOA and FDOA measurements[J].IEEE Transactions on Signal Processing,2004,52(9):2453-2463.
[5] YIN Jinhao,WAN Qun,HO K C.A simple and accurate TDOA-AOA localization method using two stations[J].IEEE Signal Processing Letters,2015,23(1):144-148.
[6] ZHU Guohui,FENG Dazheng,XIE Hu,et al.An approximately efficient bi-iterative method for source position and velocity estimation using TDOA and FDOA measurements[J].Signal Processing,2016,125(1):110-121.
[7] YANG Le,HO K C.An approximately efficient TDOA localization algorithm in closed-form for locating multiple disjoint sources with erroneous sensor positions[J].IEEE Transactions on Signal Processing,2009,57(12):4598-4615.
[8] 吴晓平,顾治华,舒红波,等.一种线性最小二乘的声源目标精确定位方法[J].声学学报,2016,41(1):87-93.
[9] FOY W H.Position-location solutions by Taylor-series estimation[J].IEEE Transactions on Aerospace and Electronic Systems,1976,12(2):187-194.
[10] CUI Xunxue,YU Kegen,LU Songsheng.Direction finding for transient acoustic source based on biased TDOA measurement[J].IEEE Transactions on Instrumentation and Measurement,2016,65(11):2442-2453.
[11] ZUO Wenjie,BAI Jiantao,YU Jufeng.Sensitivity reanalysis of static displacement using Taylor series expansion and combined approximate method[J].Structural and Multi-disciplinary Optimization,2016,53(5):953-959.
[12] 方姝,倪育德,刘逸,等.基于最小二乘与Taylor级数展开的新型混合定位方法[J].计算机工程,2015,41(6):316-321.
[13] 郝本建,李赞,任妘梅,等.基于TDOAs与GROAs的多信号源被动定位[J].电子学报,2012,40(12):2374-2381.
[14] 朱国辉,冯大政,聂卫科.传感器位置误差情况下基于多维标度分析的时差定位算法[J].电子学报,2016,44(1):21-26.
[15] FAN X,YOUNAN N H,TAYLOR C D.A perturbation analysis of the regularized constrained total least squares[J].IEEE Transactions on Circuits and Systems Ⅱ:Analog and Digital Signal Processing,1996,43(2):140-142.
[16] WANG Yue,HO K C.An asymptotically efficient estimator in closed-form for 3D AOA localization using a sensor network[J].IEEE Transactions on Wireless Communications,2015,14(12):6524-6535.
[17] 崔逊学,宗军君.基于短基线传感器网络的声源被动测向方法[J].探测与控制学报,2015,37(5):1-6.

选择文件类型/文献管理软件名称

选择包含的内容

总体最小二乘波达方向估计方法

Total Least Squares Method for Direction of Arrival Estimation

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	张天骐, 闻斌, 熊天, 吴超. 基于张量分解与场景分割的鲁棒视频水印算法[J]. 计算机工程, 2023, 49(8): 250-256, 264.
[2]	王富平, 于俊涛, 张锲石. 基于自适应方向导数滤波器的彩色边缘检测[J]. 计算机工程, 2022, 48(9): 204-212.
[3]	周博超, 韩雨男, 桂志国, 李郁峰, 张权. 基于VGG网络与深层字典的低剂量CT图像去噪算法[J]. 计算机工程, 2022, 48(4): 191-196,205.
[4]	赵秀锋, 魏伟一, 陈金寿, 陈帼. 基于自适应四元数奇异值分解的图像拼接检测[J]. 计算机工程, 2022, 48(4): 223-230,239.
[5]	钟宇, 张静, 张华, 肖贤鹏. 基于目标检测的机器人手眼标定方法[J]. 计算机工程, 2022, 48(3): 100-106.
[6]	杨立宁, 李艳婷. 基于SVD和ARIMA的时空序列分解与预测[J]. 计算机工程, 2021, 47(3): 53-61.
[7]	周运腾, 张雪英, 李凤莲, 刘书昌, 焦江丽, 田豆. Q-learning算法优化的SVDPP推荐算法[J]. 计算机工程, 2021, 47(2): 46-51.
[8]	王文冰, 刘粉林, 巩道福, 刘胜利. 基于奇异值分解的水印方法虚警问题分析[J]. 计算机工程, 2020, 46(11): 273-278.
[9]	齐向明, 张晶, 谭昕奇. 基于低频奇异值均值的强鲁棒零水印算法[J]. 计算机工程, 2019, 45(12): 214-221.
[10]	陈辰, 周拥军, 李元祥, 庹红娅, 周瑜, 骆建华. 基于U-net分割与HEIV模型的遥感图像配准方法[J]. 计算机工程, 2019, 45(11): 249-255.
[11]	郑明明, 林志毅. 基于双调合距离的三维形状相似度计算方法[J]. 计算机工程, 2019, 45(10): 266-271.
[12]	侯东升a,崔逊学b. 基于莱温伯格-马夸特的TDOA测向算法研究[J]. 计算机工程, 2018, 44(11): 109-114.
[13]	赵健,范帅帅,徐文胜,张婉如. 基于纹理方向性的非下采样剪切波水印算法[J]. 计算机工程, 2018, 44(1): 263-267.
[14]	牟竹青,黄国勇,吴建德. 考虑敏感因子奇异值分解的北斗周跳探测方法[J]. 计算机工程, 2017, 43(8): 114-119,125.
[15]	李卫疆,齐静,余正涛,赵铁军. 融合信任传播和奇异值分解的社会化推荐算法[J]. 计算机工程, 2017, 43(8): 236-242.

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

总体最小二乘波达方向估计方法

Total Least Squares Method for Direction of Arrival Estimation

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献

相关文章 15

编辑推荐

Metrics

本文评价