Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649
Citation:
Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649
Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649
Citation:
Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
2.
Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China
3.
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
Funds:
The National Natural Science Foundation of China (51979061, 51779061), The National Key R&D Program of China (2018YFC1405902)
In view of enhancing the time delay estimation resolution for the target echo in a complex shallow-water environment, thus improving the target detection ability of the active sonar system. A high-resolution time delay estimation technique is proposed to detect the underwater target based on sparse representation theory and deconvolution framework. Firstly, the Toeplitz operator is introduced here to construct a dictionary matrix using the various time delayed replicing of the transmitting signal. The estimated time-delay value can be found in the desired sparse vector solution. Secondly, the Alternating Direction Method of Multipliers (ADMM) is implemented to calculate the optimal solution globally. Thirdly, the reweighted iteration approach is explored to control the regularization parameter, thus suppressing the impact of the multipath channel. The arrival time of the echo can be decoupled to obtain a high-resolution time delay result. The simulated and experimental data verify that the proposed deconvolution-based time delay estimation technique can be used to detect the underwater target in shallow-water acoustic multipath channels. The resolution of the estimated time-delay result can achieve 0.056 ms.
针对浅海复杂声信道环境中的目标回波时延估计问题,本文基于稀疏表示理论和解卷积思想,提出一种可以广泛应用在中远程探测场景的高分辨时延估计技术。本文所提出的解卷积时延估计技术,首先用亮点模型近似表示水下尺度目标的散射特征,然后结合稀疏水声信道的特性,引入Toeplitz算子,线性地表示发射信号与广义信道冲激响应的卷积过程。最后通过交替方向乘子算法(Alternating Direction Method of Multipliers, ADMM)优化框架,解算出目标回波时延的估计值。通过加权迭代策略设置正则化参数,进一步地解耦合信道,重构回波到达时刻。目的是在获得高分辨时延估计结果的同时,突出信道冲激响应的主途径,抑制或忽略其他冗余的弱途径。以此来克服多途信道的影响,实现稳定的水下尺度目标的探测。
HAGUE D A and BUCK J R. An experimental evaluation of the generalized sinusoidal frequency modulated waveform for active sonar systems[J]. The Journal of the Acoustical Society of America, 2019, 145(6): 3741–3755. doi: 10.1121/1.5113581
YIN Jingwei, MEN Wei, HAN Xiao, et al. Integrated waveform for continuous active sonar detection and communication[J]. IET Radar, Sonar & Navigation, 2020, 14(9): 1382–1390. doi: 10.1049/iet-rsn.2020.0099
ZHANG Ting, YANG T C, and XU Wen. Bistatic localization of objects in very shallow water[J]. IEEE Access, 2019, 7: 180640–180651. doi: 10.1109/ACCESS.2019.2947851
YANG T C. Deconvolved conventional beamforming for a horizontal line array[J]. IEEE Journal of Oceanic Engineering, 2018, 43(1): 160–172. doi: 10.1109/JOE.2017.2680818
MA Lin, GULLIVER T A, ZHAO Anbang, et al. Underwater broadband source detection using an acoustic vector sensor with an adaptive passive matched filter[J]. Applied Acoustics, 2019, 148: 162–174. doi: 10.1016/j.apacoust.2018.12.023
HAMA Y and OCHIAI H. Performance analysis of matched-filter detector for MIMO spatial multiplexing over rayleigh fading channels with imperfect channel estimation[J]. IEEE Transactions on Communications, 2019, 67(5): 3220–3233. doi: 10.1109/TCOMM.2019.2892758
PADOIS T, DOUTRES O, and SGARD F. On the use of modified phase transform weighting functions for acoustic imaging with the generalized cross correlation[J]. The Journal of the Acoustical Society of America, 2019, 145(3): 1546–1555. doi: 10.1121/1.5094419
CHANDRAN V, ELGAR S, and NGUYEN A. Detection of mines in acoustic images using higher order spectral features[J]. IEEE Journal of Oceanic Engineering, 2002, 27(3): 610–618. doi: 10.1109/JOE.2002.1040943
BENESTY J, CHEN Jingdong, and HUANG Yiteng. Time-delay estimation via linear interpolation and cross correlation[J]. IEEE Transactions on Speech and Audio Processing, 2004, 12(5): 509–519. doi: 10.1109/TSA.2004.833008
SALVATI D and CANAZZA S. Adaptive time delay estimation using filter length constraints for source localization in reverberant acoustic environments[J]. IEEE Signal Processing Letters, 2013, 20(5): 507–510. doi: 10.1109/LSP.2013.2253319
SHAO Zhenfeng, WANG Lei, WANG Zhongyuan, et al. Remote sensing image super-resolution using sparse representation and coupled sparse autoencoder[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(8): 2663–2674. doi: 10.1109/JSTARS.2019.2925456
CUI Weijia, ZHANG Peng, and BA Bin. Sparse reconstruction OFDM delay estimation algorithm based on Bayesian automatic relevance determination[J]. Journal of Electronics &Information Technology, 2019, 41(10): 2318–2324. doi: 10.11999/JEIT181181
WANG Hongyan and YU Ruonan. Sparse and low rank recovery based robust DOA estimation method[J]. Journal of Electronics &Information Technology, 2020, 42(3): 589–596. doi: 10.11999/JEIT190263
MENG Xiangxia, LI Xiukun, JAKOBSSON A, et al. Sparse estimation of backscattered echoes from underwater object using integrated dictionaries[J]. The Journal of the Acoustical Society of America, 2018, 144(6): 3475–3484. doi: 10.1121/1.5083830
XIA Zhi, LI Xiukun, and MENG Xiangxia. High resolution time-delay estimation of underwater target geometric scattering[J]. Applied Acoustics, 2016, 114: 111–117. doi: 10.1016/j.apacoust.2016.07.016
HAUPT J, BAJWA W U, RAZ G, et al. Toeplitz compressed sensing matrices with applications to sparse channel estimation[J]. IEEE Transactions on Information Theory, 2010, 56(11): 5862–5875. doi: 10.1109/TIT.2010.2070191
TIBSHIRANI R. Regression shrinkage and selection via the lasso[J]. Journal of the Royal Statistical Society: Series B (Methodological) , 1996, 58(1): 267–288. doi: 10.1111/j.2517-6161.1996.tb02080.x
GRANT M and BOYD S. CVX: Matlab software for disciplined convex programming, version 2.1[OL]. http://cvxr.com/, 2014.
BOYD S, PARIKH N, CHU E, et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers[M]. Boston: Now Publishers Inc., 2011. doi: 10.1561/2200000016.
CANDÈS E J, WAKIN M B, and BOYD S P. Enhancing sparsity by reweighted ℓ1 minimization[J]. Journal of Fourier Analysis and Applications, 2008, 14(5/6): 877–905. doi: 10.1007/s00041-008-9045-x
Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649
Siyuan CANG, Xueli SHENG, Hang DONG, Longxiang GUO. Deconvolution-based Target Echo High-resolution Time Delay Estimation Technique Using Active Sonar[J]. Journal of Electronics & Information Technology, 2021, 43(3): 842-849. doi: 10.11999/JEIT200649