Particle filtering algorithm for DOA tracking with acoustic vector sensor array

LI Xin-bo; JIANG Liang-xu; LIU Guo-jun; Wang Hao-jie; SHI Yao-wu; YANG Zhi-gang; LIU Jian-

doi:10.3788/OPE.20152313.0606

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Particle filtering algorithm for DOA tracking with acoustic vector sensor array

更新时间：2020-08-13

- Particle filtering algorithm for DOA tracking with acoustic vector sensor array
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 605-612(2015)
- 作者机构：
  
  1. 吉林大学通信工程学院,吉林长春,130022
  2. 吉林大学机械科学与工程学院,吉林长春,130022
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0606
  CLC： TP391
- Received：20 May 2015，
  
  Revised：01 June 2015，
  
  Published：14 November 2015
- 稿件说明：
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李新波, 姜良旭, 刘国君等. 用于声矢量阵列目标波达方向跟踪的粒子滤波算法[J]. 光学精密工程, 2015,23(10z): 605-612

LI Xin-bo, JIANG Liang-xu, LIU Guo-jun etc. Particle filtering algorithm for DOA tracking with acoustic vector sensor array[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 605-612
李新波, 姜良旭, 刘国君等. 用于声矢量阵列目标波达方向跟踪的粒子滤波算法[J]. 光学精密工程, 2015,23(10z): 605-612 DOI： 10.3788/OPE.20152313.0606.

LI Xin-bo, JIANG Liang-xu, LIU Guo-jun etc. Particle filtering algorithm for DOA tracking with acoustic vector sensor array[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 605-612 DOI： 10.3788/OPE.20152313.0606.

摘要

针对目标波达方向(Direction of Arrival

DOA)估计方法和子空间更新算法存在的问题

本文以运动目标的方位估计为研究点

结合DOA估计算法

提出了用于声矢量阵列DOA跟踪的粒子滤波跟踪算法。首先

在声矢量传感器阵列模型的基础上

建立观测模型;根据目标运动的二阶匀速模型

建立信源运动的状态方程。然后

借鉴四元数的正交性结构

将四元数多信号分类(Multiple Signal Classification

MUSIC)算法用于改进粒子滤波的观测似然函数

提出了一种新的改进跟踪算法。最后

对各算法的性能进行仿真实验。结果表明

所提算法能实现角度的实时跟踪。与子空间类跟踪算法和粒子滤波算法相比

所提算法的跟踪误差更小。在信噪比(SNR)小于-10 dB时

粒子滤波类算法的跟踪误差均在4°以内

更能适应低信噪比环境。

Abstract

According to the shortcomings of Direction of Arrival(DOA) estimation methods and subspace updating algorithm

this paper proposes a particle filtering algorithm combined with the DOA estimation algorithm for DOA tracking with an acoustic vector sensor array. First

the observation model based on the acoustic vector sensor array was set up

and the state equation was deduced on the basis of the second-order model of uniform velocity. Then

the quaternion Multiple Signal Classification(MUSIC) algorithm was used to improve the observed likelihood function of the particle filtering algorithm and a improved tracking algorithm was proposed. Finally

the performance of each algorithm was simulated. Experimental results show that the mentioned algorithm achieves DOA real-time tracking. As compared with the subspace tracking algorithm and particle filtering algorithm

the tracking error of the proposed algorithm is smaller. When a Signal to Noise Ratio(SNR) is less than-10 dB

the tracking errors of tracking algorithms based on the particle filtering algorithm are within 4°

thus they can adapt to a lower SNR environment.

关键词

Keywords

references

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宋德枢,梁国龙,王燕. 机动目标DOA跟踪粒子滤波算法[J]. 信号处理, 2014,30(7):861-866. SONG D SH, LIANG G L, WANG Y. Particle filter algorithm for DOA tracking of maneuvering targets[J]. Journal of Signal Processing, 2014, 30(7):861-866.(in Chinese)

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李新波,孙海欣,李晓青,等. 基于四元数MUSIC算法的声矢量传感器阵列二维波达角估计[J].吉林大学学报:工学版, 2014, 44(5):1453-1459. LI X B, SUN H X, LI X Q, et al.. 2D direction of arrival estimation with acoustic vector sensor array based on quarternions MUSIC algorithm[J]. Journal of Jilin University:Engineering and Technology Edition, 2014, 44(5):1453-1459.(in Chinese)

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