李永飞 , 赵航芳 . 内波环境下的时频匹配场定位方法 [J ] . 哈尔滨工程大学学报 , 2020 , 41 ( 10 ): 1605 - 1610 .

LI Y F , ZHAO H F . A time-frequency matched field location method in the presence of internal waves [J ] . Journal of Harbin Engineering University , 2020 , 41 ( 10 ): 1605 - 1610 . (in Chinese)

刘亚琴 , 杨士莪 , 张海刚 , 等 . 利用辐射噪声对舰船进行定位 [J ] . 哈尔滨工程大学学报 , 2021 , 42 ( 7 ): 921 - 927 .

LIU Y Q , YANG S E , ZHANG H G , et al. Localization of ship using radiated noise [J ] . Journal of Harbin Engineering University , 2010 , 42 ( 7 ): 921 - 927 . (in Chinese)

FINETTE S , MIGNEREY P C . Stochastic matched-field localization of an acoustic source based on principles of Riemannian geometry [J ] . The Journal of the Acoustical Society of America , 2018 , 143 ( 6 ): 3628 - 3638 . DOI: 10.1121/1.5040492 http://doi.org/10.1121/1.5040492 https://pubs.aip.org/asa/jasa/article/143/6/3628-3638/915835 https://pubs.aip.org/asa/jasa/article/143/6/3628-3638/915835

MICHALOPOULOU Z H , POLE A , ABDI A . Bayesian coherent and incoherent matched-field localization and detection in the ocean [J ] . The Journal of the Acoustical Society of America , 2019 , 146 ( 6 ): 4812 - 4820 . DOI: 10.1121/1.5138134 http://doi.org/10.1121/1.5138134 https://pubs.aip.org/asa/jasa/article/146/6/4812-4820/954910 https://pubs.aip.org/asa/jasa/article/146/6/4812-4820/954910

刘福臣 , 姬托 , 张巧力 . 基于声场模信号特征和多项式拟合的声速剖面反演技术研究 [J ] . 兵工学报 , 2019 , 40 ( 11 ): 2283 - 2295 . DOI: 10.3969/j.issn.1000-1093.2019.11.013 http://doi.org/10.3969/j.issn.1000-1093.2019.11.013 针对未知环境下利用经验正交函数表示声速剖面的局限性，提出了一种基于多项式拟合和模信号相结合的声速剖面反演方法。介绍了模信号的概念和深海分布特性，通过理论分析和仿真分析，证明低阶多项式拟合可用于深海声速剖面的表征，并提出采用5阶多项式拟合以实现对2 000 m以浅的声速剖面较精确的表征。在反演处理流程中，利用不同参数的多项式拟合计算获得拷贝模信号，利用脉冲声信号获得数据模信号，并通过遗传算法进行参数寻优。以典型Munk剖面为例仿真分析基于垂直阵、单水听器、非海面海底反射(SRBR)信号的反演性能，单水听器的声速剖面反演与垂直阵性能接近，并提出基于非SRBR模信号反演可以提升在海底参数未知条件下反演的技术思路。利用4 000 m海深的单水听器接收的脉冲信号（距离180 km，接收与发射深度均为100 m）进行方法性能验证，结果表明，共轭深度以下（100~2 000 m）的声速剖面反演误差小于0.2 m/s.

LIU F C , JI T , ZHANG Q L . Sound speed profile inversion based on mode signal and polynomial fitting [J ] . Acta Armamentarii , 2019 , 40 ( 11 ): 2283 - 2295 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2019.11.013 http://doi.org/10.3969/j.issn.1000-1093.2019.11.013 A sound speed profile inversion method based on mode signal and polynomial fitting is proposed for the limitation of using the empirical orthogonal function to represent the sound speed profile in unknown environment. A concept of mode signal and the distribution characteristics of deep sea are given. It is proven through theoretical analysis and simulation that the low-order polynomial fitting can be used for presenting the sound speed profile in seabed.The five-order polynomial fitting can be used for accurately presenting the sound speed profile in 2 000 m-depth sea water. And in the inversion process, the copy mode signal vector is obtained by polynomial fitting of different parameters, and the mode signal is obtained from the test data by using the pulse acoustic signal, of which the parameters are optimized by genetic algorithm. The inversion performances of vertical array, single hydrophone and non-SRBR signal are simulated and analyzed by taking typical Munk profile as an example. It is concluded that the higher the order of polynomial is, the better the fitting effect of sound speed profile is. When a certain error is allowed, the lower order can be used for fitting the sound speed profile. The simulated results show that the performance of sound speed profile inversion using a single hydrophone is close to that of the vertical array, and the inversion performance under the condition of unknown seabed parameters can be improved by using the non-SRBR mode signal inversion. And finally, the performance of the proposed method is verified by using the pulse signal received by the single hydrophone in 4 000 m-depth sea water (distance: 180 km, and receiving and transmitting depth: 100 m). The results show that the inversion error of sound speed profile is less than 0.2 m/s. Key

鞠阳 , 元勇虎 , 林蔚 , 等 . 基于声信息的匀加速目标快速目标运动分析解算 [J ] . 兵工学报 , 2019 , 40 ( 8 ): 1688 - 1692 . DOI: 10.3969/j.issn.1000-1093.2019.08.018 http://doi.org/10.3969/j.issn.1000-1093.2019.08.018 目前水下目标运动分析（TMA）基本上以目标作匀速运动为前提进行研究，而少有以目标做匀加速运动为前提的TMA解算研究。提出一种在观测平台不机动时求解匀加速直线运动目标参数的内点-Levenberg-Marquard解算方法，并结合多普勒效应双模型与解算方法，提出一种参数搜索优化方法，使得求解参数的过程快速收敛。仿真结果表明，所提解算方法能够有效地求解匀加速直线运动目标的运动参数，并且降低了对本艇机动的依赖程度。

JU Y , YUAN Y H , LIN W , et al. Acoustic information-based TMA method for uniformly accelerating motion of target [J ] . Acta Armamentarii , 2019 , 40 ( 8 ): 1688 - 1692 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2019.08.018 http://doi.org/10.3969/j.issn.1000-1093.2019.08.018 The most research on target motion analysis (TMA ) of underwater target is based on the hypothesis of uniform motion of a target, but is seldomly based on the hypothesis of uniformly accelerating motion. An innerpoint-Levenberg-Marquard (LM) method of calculating TMA parameters without the motion of observation platform is proposed. And an optimization searching method for TMA parameters is proposed, which combines the Doppler effect double model and the solving method of TMA parameters. It makes the solving process of parameters converge quickly. Simulated result shows that the inner-point LM method can be used to solve the TMA parameters effectively and reduce the dependence on the motion observation platform. Key

王奇 , 王英民 , 苟艳妮 . 不确定环境下后验概率约束的匹配场处理 [J ] . 兵工学报 , 2014 , 35 ( 9 ): 1473 - 1480 . DOI: 10.3969/j.issn.1000-1093.2014.09.021 http://doi.org/10.3969/j.issn.1000-1093.2014.09.021 不确定海洋环境下，匹配场处理(MFP)所使用的环境模型与真实环境总会存在一定的差异，即存在环境参数失配，此时匹配场处理的性能严重下降。为了提高匹配场处理的稳健性，提出了一种后验概率约束的匹配场处理器(MFP-PPC)。利用贝叶斯准则推导出了位置参数的后验概率密度(PPD)估计，以此为约束为自适应匹配场处理器(AMFP)提供主瓣保护，使得算法具有AMFP高分辨特点的同时稳健性也得到改善。为了验证算法的性能，使用不确定浅海环境下的仿真数据和海试数据进行了处理分析。分析结果表明：不确定环境下，MFP-PPC不仅能够稳健地定位固定声源，而且能够稳健地定位运动声源，且跟踪曲线和声源移动轨迹吻合较好。

WANG Q , WANG Y M , GOU Y N . Posterior probability constraint matched field processing with environmental uncertainty [J ] . Acta Armamentarii , 2014 , 35 ( 9 ): 1473 - 1480 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2014.09.021 http://doi.org/10.3969/j.issn.1000-1093.2014.09.021 In an uncertain ocean environment, the environmental model used by matched field processing (MFP) is different from the real world. As a result of the environmental mismatch, the performance of MFP deceases largely. In order to improve its robustness to the environmental mismatch, a posterior probability constraint matched field processing (MFP-PPC) is proposed. The algorithm derives the posterior probability density (PPD) of the source locations from Bayesian criterion, then the main lobe of AMFP is protected by PPD, so MFP-PPC has not only the merit of high resolution as AMFP, but also the advantage of robustness. To evaluate the algorithm, the simulated and experimental data in an uncertain shallow ocean environment are used. The results show that MFP-PPC is robust not only to the moored source in the uncertain ocean environment, but also to the moving source. The tracking curve is consistent with the trajectory of the moving source.

GODIN O A . On sound propagation in a nonstationary ocean [J ] . Doklady Physics , 2002 , 47 ( 9 ): 639 - 642 . DOI: 10.1134/1.1512625 http://doi.org/10.1134/1.1512625 http://link.springer.com/10.1134/1.1512625 http://link.springer.com/10.1134/1.1512625

李晓曼 , 朴胜春 , 张明辉 , 等 . 一种基于单水听器的浅海水下声源被动测距方法 [J ] . 物理学报 , 2017 , 66 ( 18 ): 114 - 127 .

LI X M , PIAO S C , ZHANG M H , et al. A passive range method of underwater source based on single hydrophone [J ] . Acta Physica Sinica , 2017 , 66 ( 18 ): 114 - 127 . (in Chinese)

ZHANG T W , HAN G J , GUIZANI M , et al. Peak extraction passive source localization using a single hydrophone in shallow water [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 3 ): 3412 - 3423 . DOI: 10.1109/TVT.25 http://doi.org/10.1109/TVT.25 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25 https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25

WARNER G A , DOSSO S E , DETTMER J , et al. Bayesian environmental inversion of airgun modal dispersion using a single hydrophone in the Chukchi Sea [J ] . The Journal of the Acoustical Society of America , 2015 , 137 ( 6 ): 3009 - 3023 . DOI: 10.1121/1.4921284 http://doi.org/10.1121/1.4921284 https://pubs.aip.org/asa/jasa/article/137/6/3009-3023/928940 https://pubs.aip.org/asa/jasa/article/137/6/3009-3023/928940

REN Q Y , HERMAND J P . Bayesian tracking of time or space varying environment from ship noise recorded on a drifting vector sensor [C ] ∥Proceedings of 2014 Oceans.St.John’s, Canada:IEEE , 2014 .

高飞 , 潘长明 , 孙磊 . Bayes匹配场地声参数反演:多步退火Gibbs采样算法 [J ] . 兵工学报 , 2017 , 38 ( 7 ): 1385 - 1394 . DOI: 10.3969/j.issn.1000-1093.2017.07.017 http://doi.org/10.3969/j.issn.1000-1093.2017.07.017 为实现海洋地声环境参数的快速高效反演，提出多步退火Gibbs（Multi-AG）采样算法，可消除因参数搜索空间设置对参数反演结果的影响，并有效解决Bayes匹配场高维参数反演过程中常见的运算量大、旁瓣高等问题。分析待反演地声参数对匹配场处理器的敏感性，用以制定多步反演与退火方案，利用Gibbs采样算法反演敏感性级别最高的参数，计算其均值并代入后续反演步骤，进而采用退火Gibbs采样算法逐步反演后续参数；利用数值仿真实验对比Metropolis-Hastings算法、Gibbs采样算法、快速Gibbs采样算法和Multi-AG采样算法的反演效果。实验结果表明，与其他3种算法相比，Multi-AG采样算法可通过最小的计算量得到均方差最小、精度最高的参数反演结果。

GAO F , PAN C M , SUN L . Geoacoustic parameters inversion of Bayes matched-field: a multi-annealing Gibbs sampling algorithm [J ] . Acta Armamentarii , 2017 , 38 ( 7 ): 1385 - 1394 . (in Chinese) DOI: 10.3969/j.issn.1000-1093.2017.07.017 http://doi.org/10.3969/j.issn.1000-1093.2017.07.017 A multi-annealing Gibbs (multi-AG) sampling algorithm is developed to obtain a fast, accurate inversion result of ocean geoacoustic parameters. The proposed algorithm can deal well with huge computation load and high side lobe in multi-dimensional inversion of Bayes matched-field, and also eliminate the effects from the sampling bounds. The sensitivity of geoacoustic parameters to the matched-field processor is analyzed, which contributes to establish the multi-step inversion and annealing scheme. The Gibbs sampling algorithm is used to invert the highest sensitive parameters, which mean value is necessary to the following inversion steps. The inversion of remain parameters can be operated with annealing Gibbs sampling algorithm step by step. The inversion effects of Metropolis-Hastings, Gibbs, FGS, and multi-AG algorithms are compared through numerical experiment, and the research shows that multi-AG sampling algorithm can be used to obtain the inversion results with the smallest mean square deviation and the highest precision, while costing the least algorithm computation. Key

GUO L X , LIU J A , ZHANG X , et al. Robust underwater acoustic channel estimation in impulsive noise environment [C ] ∥Proceedings of 2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops).Xiamen,China. IEEE , 2021 : 278 - 281 .

OGISO S , MIZUTANI K , WAKATSUKI N , et al. Robust localization of mobile robot in reverberant rooms using acoustic beacons with iterative Bayesian filtering [C ] ∥Proceedings of 2018 International Conference on Indoor Positioning and Indoor Navigation.Nantes , France : IEEE , 2018 : 1 - 6 .

王彪 , 朱志慧 , 戴跃伟 . 一种快速稀疏贝叶斯学习的水声目标方位估计方法研究 [J ] . 声学学报 , 2016 , 41 ( 1 ): 81 - 86 .

WANG B , ZHU Z H , DAI Y W . A fast underwater acoustic target direction of arrival estimation method based on sparse Bayesian learing [J ] . Acta Acustica , 2016 , 41 ( 1 ): 81 - 86 . (in Chinese)

王彪 , 朱志慧 , 戴跃伟 . 基于具有时序结构的稀疏贝叶斯学习的水声目标DOA估计研究 [J ] . 电子学报 , 2016 , 44 ( 3 ): 693 - 698 . DOI: 10.3969/j.issn.0372-2112.2016.03.030 http://doi.org/10.3969/j.issn.0372-2112.2016.03.030 现有的基于CS-MMV(Compressed Sensing-Multiple Measurement Vectors)模型的DOA估计一般都假定信号源为独立同分布(i.i.d),算法建立在信号的空间结构上进行分析,而当处理具有时序结构的源信号时表现出性能和鲁棒性差的问题,为此该文提出一种具有时序结构的稀疏贝叶斯学习的DOA算法,该方法通过建立一阶自回归过程(AR)来描述具有时序结构的水声信号,将信号源的时间结构特性充分应用到DOA估计模型中,然后采用针对多测量矢量的稀疏贝叶斯学习(Muti-vectors Sparse Bayesian Learning)算法重构信号空间谱,建立多重测量向量中恢复未知稀疏源的信号的CS(Compressed Sensing)模型,最终完成DOA估计.仿真结果表明该方法相对于传统的算法具有更高的空间分辨率和估计精度的特点,且抗干扰能力强.

WANG B , ZHU Z H , DAI Y W . Direction of arrival estimation research for underwater acoustic target based on sparse Bayesian learing with temporally correlated source vectors [J ] . Acta Electronica Sinica , 2016 , 44 ( 3 ): 693 - 698 . (in Chinese) DOI: 10.3969/j.issn.0372-2112.2016.03.030 http://doi.org/10.3969/j.issn.0372-2112.2016.03.030 Assuming independently but identically distributed sources,most existing DOA algorithms based on the CS-MMV model are analyzed according to the spatial structure of the signals. The temporal correlation between the sources,however,results in poor performance and robustness. To overcome this problem,we propose a DOA estimation algorithm based on Sparse Bayesian Learning (SBL) with temporally correlated source vectors. In this method,an underwater acoustic source is regarded as a first-order autoregressive process,with time structure characteristics being applied to DOA estimation model. After that,the multi-vector SBL algorithm is used to reconstruct the signal spatial spectrum. Then the CS-MMV model of the unknown sparse vector signal sources is established to estimate the DOA. Through simulation,it shows that the proposed algorithm provides a higher spatial resolution and estimation accuracy in comparison to many other current algorithms.

BOWMAN A W , AZZALINI A . Applied smoothing techniques for data analysis:the kernel approach with S-Plus illustrations [M ] . Oxford , UK : Oxford University Press , 1997 .

SHI H J , LI J H , CHANG H , et al. Research on passive localization method of shallow water acoustic source with single hydrophone based on hierarchical grid histogram filtering [J ] . Applied Acoustics , 2022 , 194 : 108812 . DOI: 10.1016/j.apacoust.2022.108812 http://doi.org/10.1016/j.apacoust.2022.108812 https://linkinghub.elsevier.com/retrieve/pii/S0003682X22001864 https://linkinghub.elsevier.com/retrieve/pii/S0003682X22001864