复域压缩感知近场声图测量方法

doi:10.3969/j.issn.1000-1093.2021.08.018

摘要/Abstract

摘要： 针对频域压缩感知近场声图测量方法性能下降的问题，基于阵列信号处理中相移与时延关系，按近场扫描位置在复域对各通道数据进行时延补偿和相关处理，建立复域感知矩阵和观测序列构建方法，提出复域感知矩阵近场声图测量模型。以数值仿真和某近场目标定位试验中测得数据为案例，将该模型与频域压缩感知模型处理结果进行对比。结果表明，相比频域压缩感知方法，通过改变观测序列和感知矩阵构建方式，最低信噪比的适应性得到近10lgM dB（M为通道数）的提升，提高了近场声图测量性能。

关键词: 阵列信号处理, 近场声图测量, 复域压缩感知, 感知矩阵

Abstract: In order to solve the performance degradation problem of near-field acoustic image measurement method based on compressed sensing in frequency domain, the time delay compensation and correlation are processed based on the relationship between phase shift and time delay in array signal processing according to the near-field scanning position in the complex domain. A near-field acoustic image measurement model of sensing matrix in complex domain is established. Taking the numerical simulation data and the data measured in a near-field target location experiment as an example, the processed results of the proposed model and the frequency domain compressed sensing model are compared. The results show that, compared with frequency domain compressed sensing, the tolerance of lowest signal-to-noise ratio of this method is improved nearly 10lgM dB (where M is the channel number of array) by changing the construction way of sensing matrix and observation sequence, and the ability of near-field acoustic image measurement is improved.

Key words: arraysignalprocessing, near-fieldacousticimagemeasurement, compressedsensingincomplexdomain, sensingmatrix

中图分类号:

陈新华，郑恩明，李嶷，杨鹤，周权斌. 复域压缩感知近场声图测量方法[J]. 兵工学报, 2021, 42(8): 1735-1743.

CHEN Xinhua, ZHENG Enming, LI Yi, YANG He, ZHOU Quanbin. A Near-field Acoustic Image Measurement Method Based on Compressed Sensing in Complex Domain[J]. Acta Armamentarii, 2021, 42(8): 1735-1743.

参考文献

［1］陈泓宇,吴伟伟,王明宇. 基于近场聚焦波束形成方法的声场定位研究［J］. 计算机仿真,2014,31(10): 30-34.
CHEN H Y,WU W W, WANG M Y. Research of sound field localization based on near-field focusing beamforming［J］.Computer Simulation, 2014,31(10): 30-34. （in Chinese）
［2］梅继丹,石文佩,马超,等. 近场反卷积聚焦波束形成声图测量［J］.声学学报,2020,45(1): 15-28.
MEI J D, SHI W P, MA C, et al. Near-field focused beamforming acoustic image measurement based on deconvolution［J］. Acta Acustica, 2020, 45(1): 15-28. （in Chinese）
［3］许高凤,安妍妍,杨丰茂,等. 基于组合线阵的近程运动小目标被动定位跟踪［J］.应用声学,2020,39(1): 149-156.
XU G F, AN Y Y, YANG F M, et al. Passive location and tracking method of short range moving target based on combined linear array［J］. Journal of Applied Acoustics,2020,39(1): 149-156. （in Chinese）
［4］郑恩明，黎远松，陈新华，等.改进的最小方差无畸变响应波束形成方法［J］.上海交通大学学报，2016, 50(2): 188-193.
ZHENG E M, LI Y S, CHEN X H,et al. Improved bearing resolution approach for MVDR beam-forming［J］. Journal of Shanghai Jiao Tong University, 2016, 50(2): 188-193. (in Chinese)
［5］郑恩明,陈新华,宋春楠. 基于全相位预处理的低旁瓣波束形成方法［J］. 兵工学报,2018,39(10): 1971-1978．
ZHENG E M, CHEN X H, SONG C M．Low side-lobe beam-forming method based on all-phase preprocessing ［J］. Acta Armamentarii, 2018,39(10): 1971-1978．（in Chinese）
［6］李冰,汪永明,黄海宁. 基于时域解析估计的多重信号分类波束形成方法［J］. 上海交通大学学报,2019,53(8): 928-925.
LI B, WANG Y M, HUANG H N. Multiple signal classification beam-forming method based on time domain analysis［J］. Journal of Shanghai Jiao Tong University,2019,53(8): 928-925. （in Chinese）
［7］余华兵,郑恩明,陈新华. 基于全相位预处理的时域多重信号分类波达方向估计方法［J］.振动与冲击, 2020,39(10): 242- 248.
YU H B, ZHENG E M, CHEN X H. The time-domain multiple signal classification DOA estimation method based on app-phase preprocessing［J］.Journal of Vibration and Shock, 2020,39(10): 242-248. （in Chinese）
［8］ ZHU W, CHEN B X. Novel methods of DOA estimation based on compressed sensing［J］. Multidimensional Systems and Signal Processing, 2015, 26(1):113-123.
［9］ DAS A, SHODGKISS W,GERSTOFT P. Coherent multipath direction-of-arrival resolution using compressed sensing［J］.IEEE Journal of Oceanic Engineering, 2017, 42(2): 494-505.
［10］ HOU Y G, GAO H F, HUANG Q H, et al. A robust capon beamforming approach for sparse array based on importance resampling compressive covariance sensing［J］. IEEE Access, 2019, 7: 80478-80489.
［11］ LI J, LIN Q H, KANG C Y，et al. DOA estimation for underwater wideband weak targets based on coherent signal subspace and compressed sensing［J］. Sensors, 2018, 18(3):902-910.
［12］陈力恒,马晓川,李璇,等. 结合压缩感知模型的稀疏阵列波束形成方法［J］.信号处理,2020,36(4):475-485.
CHEN L H, MA X C, LI X, et al. Sparse array beamforming method combined with compressed sensing model［J］.Journal of Signal Processing, 2020, 36(4): 475-485. （in Chinese）
［13］李贺,刘志红,仪垂杰.基于压缩感知和约束随机线阵的声源方位估计［J］.山东科技大学学报(自然科学版),2020,39(5): 122-130.
LI H, LIU Z H, YI C J. Sound source location estimation based on compressed sensing based on compressed sensing and random linear array［J］.Journal of Shandong University of Science and Technology (Natural Science), 2020, 39(5): 122-130. （in Chinese）
［14］沈小正,王彪. 基于压缩感知理论的声矢量阵方位估计方法［J］. 传感器与微系统, 2016, 35(7): 35-37.
SHEN X Z, WANG B. Direction of arrival estimation method for acoustic vector sensor array based on compressed sensing theories［J］. Transducer and Microsystem Technologies, 2016, 35(7): 35-37. （in Chinese）
［15］郭双乐,彭临慧,唐瑞春. 基于压缩感知的水下目标定位［J］. 中国海洋大学学报,2015,45(10): 127-132.
GUO S L, PENG L H, TANG R C. Underwater positioning based on compressed sensing［J］. Periodical of Ocean University of China,2015,45(10): 127-132. （in Chinese）
［16］时洁,杨德森,时胜国,等. 基于压缩感知的矢量阵聚焦定位方法［J］.物理学报,2016,65(2): 024302
SHI J, YANG D S, SHI S G, et al. Compressive focused beamforming based on vector sensor array［J］. Acta Physica Sinica ,2016,65(2): 024302.（in Chinese）
［17］康春玉,李前言,章新华,等.频域单快拍压缩感知目标方位估计和信号恢复方法［J］.声学学报, 2016, 41(2): 174-180.
KANG C Y, LI Q Y, ZHANG X H, et al. Direction of arrival estimation and signal recovery based on single snapshot compressed sensing in frequency domain［J］. Acta Acustica, 2016, 41(2):174-180. （in Chinese）
［18］康春玉,李文哲,夏志军,等.盲重构频域阵列信号的压缩感知水声目标方位估计［J］.声学学报, 2019, 44(6): 951-960.
KANG C Y, LI W Z, XIA Z J, et al. Direction of arrival estimation for underwater acoustic based on compressed sensing after blind reconstruction of array signal in frequency domain［J］. Acta Acustica, 2019, 44(6): 951-960. （in Chinese）
［19］周明阳,郭良浩,闫超. 改进的贝叶斯压缩感知目标方位估计［J］.声学学报,2019,44(6):961-969.
ZHOU M Y, GUO L H, YAN C. Improved Bayesian compressive sensing-based direction of arrival estimation［J］. Acta Acustica, 2019, 44(6):961-969. （in Chinese）
［20］余华兵,郑恩明,陈新华. 基于相参累积预处理的空间谱估计方法［J］.上海交通大学学报, 2020, 54(11): 1209-1217.
YU H B, ZHENG E M, CHEN X H. A spatial spectrum estimation method based on coherent cumulative preprocessing ［J］. Journal of Shanghai Jiao Tong University, 2020, 54(11):1209- 1217. （in Chinese）

[1]	郑恩明，陈新华，宋春楠. 基于全相位预处理的低旁瓣波束形成方法[J]. 兵工学报, 2018, 39(10): 1971-1978.
[2]	张柯，程菊明，付进. 基于多级维纳滤波器的声矢量阵空间谱估计算法[J]. 兵工学报, 2015, 36(11): 2128-2134.
[3]	梁国龙，张柯，安少军，范展. 声矢量阵阵元姿态误差自校正算法研究[J]. 兵工学报, 2014, 35(8): 1236-1242.
[4]	顾陈, 何劲, 李洪涛, 朱晓华. 基于扩展孔径ESPRIT算法的高精度无模糊二维DOA估计[J]. 兵工学报, 2012, 33(1): 103-108.