基于二次分数低阶协方差的被动式声源定位方法

刘小松1, 郭靖豪1, 柳鹏2, 任玮1, 单泽彪1, 2

振动与冲击 ›› 2024, Vol. 43 ›› Issue (24) : 259-266.

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (24) : 259-266.
论文

基于二次分数低阶协方差的被动式声源定位方法

  • 刘小松1,郭靖豪1,柳鹏2,任玮1,单泽彪1,2
作者信息 +

A passive source location method based on quadratic fractional low order covariance

  • LIU Xiaosong1, GUO Jinghao1, LIU Peng2, REN Wei1, SHAN Zebiao1,2
Author information +
文章历史 +

摘要

针对现有的被动式声源定位算法在强脉冲噪声环境下抗干扰能力弱、定位误差大等问题,提出了一种基于二次分数低阶协方差的被动式声源定位估计方法。该方法首先构建了一个多点共用的最优四基阵阵列结构,利用有界非线性Sigmoid函数对含有脉冲噪声的接收信号进行处理;然后对处理后的阵元间信号进行二次分数低阶协方差运算,即求得阵元信号的自分数低阶协方差和两阵元间信号的互分数低阶协方差之后,再次计算二者的互分数低阶协方差,以期更大程度上抑制脉冲噪声的影响;最终根据求得的时延信息对声源进行定位计算。通过定位实验对所提方法进行了有效性验证。

Abstract

A passive acoustic source localization estimation method based on second-order fractional lower-order covariance is proposed to address the issues of weak anti-interference capability and large localization errors in the presence of strong impulse noise. This method first establishes an optimal four-element array structure with multiple shared points. Then, it employs a bounded non-linear Sigmoid function to process the received signals containing impulse noise. Subsequently, the signals between array elements after processing are subjected to second-order fractional lower-order covariance operation. This involves calculating the self-fractional lower-order covariance of the first element signal and the cross-fractional lower-order covariance between correlated array element signals. The resulting cross-fractional lower-order covariance is then computed once again to further suppress the influence of impulse noise. Finally, source localization calculations are performed based on the obtained delay information. The effectiveness of the proposed method is validated through experiments.

关键词

被动式声源定位 / 脉冲噪声 / 最优四基阵 / 二次分数低阶协方差

Key words

Passive acoustic source localization / Impulse noise / Optimal four-element array / Quadratic fractional low-order covariance

引用本文

导出引用
刘小松1, 郭靖豪1, 柳鹏2, 任玮1, 单泽彪1, 2. 基于二次分数低阶协方差的被动式声源定位方法[J]. 振动与冲击, 2024, 43(24): 259-266
LIU Xiaosong1, GUO Jinghao1, LIU Peng2, REN Wei1, SHAN Zebiao1, 2. A passive source location method based on quadratic fractional low order covariance[J]. Journal of Vibration and Shock, 2024, 43(24): 259-266

参考文献

[1] 杨红波, 郭磊, 史文库, 等. 道路试验下某重型商用车驾驶室啸叫声源定位[J]. 振动与冲击, 2022, 41(20): 307-314.
YANG Hongbo, GUO Lei, SHI Wenku, et al. Noise source localization of a heavy commercial vehicle cab under a road test. [J]. Journal of Vibration and Shock, 2022, 41(20): 307-314.
[2] 初宁, 黄乾, 余亮, 等. 一种基于相位平均的旋转声源高分辨率定位方法[J]. 振动与冲击, 2021, 40(19): 125-136.
CHU Ning, HUANG Qian, YU Liang, et al. A high-resolution positioning method of rotating sound source based on phase average.[J]. Journal of Vibration and Shock, 2021, 40(19): 125-136.
[3] NIU G, GAO J, DU T. Passive localization algorithm for remote multitarget localization information[J]. IEEJ Transactions on Electrical and Electronic Engineering, 2020, 15(8): 1183-1187.
[4] LI Y W, CHEN H W. Reverberation robust feature extraction for sound source localization using a small-sized microphone array[J]. IEEE Sensors Journal, 2017, 17(19): 6331-6339.
[5] ZHAO X, ZHOU L, TONG Y, et al. Robust sound source localization using convolutional neural network based on microphone array[J]. Intelligent Automation and Soft Computing, 2021, 30(1): 361-371.
[6] LIU C, LV Y, MIAO J, et al. Research on high resolution algorithm of sound source localization based on microphone array[C]//2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2019: 1-6.
[7] 王领, 申晓红, 康玉柱, 等. 水声传感器网络信号到达时间差目标定位的最小二乘法估计性能[J]. 兵工学报, 2020, 41(03): 542-551.
WANG Ling, SHEN Xiaohong, KANG Yuzhu, et al . Least Squares Estimation Performance for TDOA Target Localization in Underwater Acoustic Sensor Networks[J] Acta Armamentarii, 2020, 41(03): 542-551.
[8] YIN J, WAN Q, YANG S, et al. A simple and accurate TDOA-AOA localization method using two stations[J]. IEEE Signal Processing Letters, 2015, 23(1): 144-148.
[9] 单泽彪, 鲁胜麟, 刘小松, 等. 基于高阶累积量的阵列式超声波传感器风速风向测量[J]. 仪器仪表学报, 2021, 42(6): 279-286.
SHAN Zebiao, LU Shenglin, LIU Xiaosong, et al. Wind speed and direction measurement of array ultrasonic sensors based on high-order cumulant[J]. Chinese Journal of Scientific Instrument, 2021, 42(6): 279-286.
[10] 单泽彪, 解晓冉, 刘小松, 等. 互射式三阵元超声波传感器的二次相关测风方法[J]. 电子学报, 2023, 51(09): 2428-2436.
SHAN Zebiao, XIE Xiaoran, LIU Xiaosong, et al. Wind measurement with three mutually transmitting ultrasonic sensors based on quadratic correlation method [J]. Acta Electronica Sinica, 2023, 51(09): 2428-2436.
[11] 刘小松, 徐再祥, 单泽彪, 等. 基于二次分数低阶协方差的时延估计方法[J]. 电子测量与仪器学报, 2024, 38(2): 112-119.
LIU Xiaosong, XU Zaixiang, SHAN Zebiao, et al. Time delay estimation method based on second-order fraction low-order covariance [J]. Journal of Electronic Measurement and Instrumentation, 2024, 38(2): 112-119.
[12] 邱天爽, 刘浩, 张家成, 等. 一种改进的广义循环相关熵时延估计方法[J]. 电子与信息学报, 2021, 43(02): 255-262.
QIU Tianshuang, LIU Hao, ZHANG Jiacheng, et al. An improved time delay estimation method based on generalized cyclic correntropy[J]. Journal of Electronics and Information Technology, 2021, 43(02): 255-262.
[13] LI Y M, WANG R D, HU Y L, et al. Defensive compressive time delay estimation using information bottleneck[J]. IEEE Signal Processing Letters, 2021, 28: 1968–1972.
[14] SUN M, WANG Y D, BASTARD C L, et al. Signal subspace smoothing technique for time delay estimation using MUSIC algorithm[J]. Sensors, 2017, 17(12): 1-12.
[15] 邱天爽. 相关熵与循环相关熵信号处理研究进展[J]. 电子与信息学报, 2020, 42(01): 105-118.
QIU Tianshuang. Development in Signal Processing Based on Correntropy and Cyclic Correntropy[J]. Journal of Electronics and Information Technology, 2020, 42(01): 105-118.
[16] GRZESIEK A, SUNDAR S, WYŁOMAŃSKA A. Fractional lower order covariance-based estimator for bidimensional AR(1) model with stable distribution[J]. International Journal of Advances in Engineering Sciences and Applied Mathematics,2019,11(3): 217-229.
[17] 黄健, 严胜刚. 分数低阶协方差谱用于改进的时延估计方法[J]. 应用声学, 2017, 36(05): 424-428.
HUANG Jian, YAN Shenggang. An improved time delay estimation algorithm based on fractional lower order covariance spectrum[J]. Journal of Applied Acoustics, 2017, 36 (05): 424-428.

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