Page 13 - 《应用声学》2022年第4期

第 41 卷 第 4 期 沈同圣等： 可靠声路径传播特性及目标定位方法研究现状 511

[27] 王梦圆, 李整林, 吴双林, 等. 深海大深度声传播特性及直达 [42] 王鸿吉, 杨日杰, 桂晨阳. 基于 RAP 的水雷引信作用范围计
声区水下声源距离估计 [J]. 声学学报, 2019, 44(5): 905–912. 算方法 [C]//2014 年水声对抗技术学术交流会论文集, 2014:
Wang Mengyuan, Li Zhenglin, Wu Shuanglin, et al. The 262–264.
characteristics of sound propagation in deep water and un- [43] 王鸿吉, 韩建辉, 杨日杰. 基于 RAP 的水平线列阵时反定位
derwater sound source ranging in the direct zone[J]. Acta 研究 [J]. 压电与声光, 2015, 37(3): 456–459, 463.
Acustica, 2019, 44(5): 905–912. Wang Hongji, Han Jianhui, Yang Rijie. Research on
[28] 王梦圆, 李整林, 秦继兴, 等. 深海直达声区水下声源距离深 time reversal positioning of horizontal line array based
度联合估计 [J]. 信号处理, 2019, 35(9): 1535–1543. on RAP[J]. Piezoelectrics & Acoustooptics, 2015, 37(3):
Wang Mengyuan, Li Zhenglin, Qin Jixing, et al. Com- 456–459, 463.
bined estimation of range and depth for underwater source [44] 王鸿吉, 韩建辉, 杨日杰. 基于 RAP 的垂直线列阵时反定位
in the direct zone in deep water[J]. Journal of Signal Pro- 研究 [J]. 传感器与微系统, 2015, 34(4): 56–58.
cessing, 2019, 35(9): 1535–1543. Wang Hongji, Han Jianhui, Yang Rijie. Research on time
[29] Li H, Xu Z Z, Yang K D, et al. Use of multipath time- reversal positioning of vertical line array based on RAP[J].
delay ratio for source depth estimation with a vertical line Transducer and Microsystem Technologies, 2015, 34(4):
array in deep water[J]. The Journal of the Acoustical So- 56–58.
[45] 牛海强, 李整林, 王海斌, 等. 水声被动定位中的机器学习方
ciety of America, 2021, 149(1): 524–539.
[30] McCargar R, Zurk L M. Depth-based signal separation 法研究进展综述 [J]. 信号处理, 2019, 35(9): 1450–1459.
with vertical line arrays in the deep ocean[J]. The Jour- Niu Haiqiang, Li Zhenglin, Wang Haibin, et al. Overview
nal of the Acoustical Society of America, 2013, 133(4): of machine learning methods in underwater source lo-
calization[J]. Journal of Signal Processing, 2019, 35(9):
320–325.
[31] Kniffin G P, Boyle J K, Zurk L M, et al. Performance 1450–1459.
[46] Steinberg B Z, Beran M J, Chin S H, et al．A neural net-
metrics for depth-based signal separation using deep ver-
work approach to source localization[J]. The Journal of the
tical line arrays[J]. The Journal of the Acoustical Society
Acoustical Society of America, 1991, 90(4): 2081–2090.
of America, 2016, 139(1): 418–425.
[47] Ozard J M, Zakarauskas P, Ko P. An artificial neural
[32] Duan R, Yang K D, Li H, et al. A performance study
network for range and depth discrimination in matched
of acoustic interference structure applications on source
field processing[J]. The Journal of the Acoustical Society
depth estimation in deep water[J]. The Journal of the
of America, 1991, 90(5): 2658–2663.
Acoustical Society of America, 2019, 145(2): 903–916.
[48] Niu H, Reeves E, Gerstoft P. Source localization in an
[33] Qi Y B, Zhou S H, Liang Y Q, et al. Passive broadband
ocean waveguide using supervised machine learning[J].
source depth estimation in the deep ocean using a single
The Journal of the Acoustical Society of America, 2017,
vector sensor[J]. The Journal of the Acoustical Society of
142(3): 1176–1188.
America, 2020, 148(1): 88.
[49] Niu H, Ozanich E, Gerstoft P. Ship localization in Santa
[34] 翁晋宝, 李风华, 郭永刚. 典型深海声场频率 -距离干涉结构分
Barbara Channel using machine learning classifiers[J]. The
析及实验研究 [J]. 声学学报, 2016, 41(3): 330–342.
Journal of the Acoustical Society of America, 2017, 142(5):
Weng Jinbao, Li Fenghua, Guo Yonggang. The sound
455–460.
field frequency-range interference patterns in deep wa-
[50] Wang Y, Peng H. Underwater acoustic source localization
ter theory and experiment[J]. Acta Acustica, 2016, 41(3):
using generalized regression neural network[J]. The Jour-
330–342.
nal of the Acoustical Society of America, 2018, 143(4):
[35] 李浩琦, 王海斌, 张仁和. 一种声场干涉结构条纹增强方
2321–2331.
法 [C]// 2013 中国西部声学学术交流会论文集 (下), 2013:
[51] Huang Z, Xu J, Gong Z, et al. Source localization using
7–10. deep neural networks in a shallow water environment[J].
[36] 唐浩, 王方勇. 浅海主动声呐混响干涉结构特性及增强方
The Journal of the Acoustical Society of America, 2018,
法 [J]. 声学与电子工程, 2020(2): 1–5. 143(5): 2922–2932.
[37] Fizell R G, Wales S C. Source localization in range and [52] Liu Y, Niu H, Li Z. Source ranging using ensemble con-
depth in an Arctic environment[J]. The Journal of the volutional networks in the direct zone of deep water[J].
Acoustical Society of America, 1985, 78(S1): 57–58. Chinese Physics Letters, 2019, 36(4): 47–50.
[38] Lei Z, Yang K D, Ma Y L. Passive localization in the [53] Liu W X, Yang Y X, Xu M Q, et al. Source localization
deep ocean based on cross-correlation function match- in the deep ocean using a convolutional neural network[J].
ing[J]. The Journal of the Acoustical Society of America, The Journal of the Acoustical Society of America, 2020,
2016, 139(6): 196–201. 147(4): 314.
[39] Yang K D, Xu L, Yang Q, et al. Striation-based source [54] 张仁和. 水声物理、信号处理与海洋环境紧密结合是水声技术
depth estimation with a vertical linearray in the deep 发展的趋势 [J]. 应用声学, 2006, 25(6): 325–327.
ocean[J]. The Journal of the Acoustical Society of Amer- Zhang Renhe. The development trend of underwater
ica, 2018, 143(1): 8–12. acoustic technology is osculatory combination of under-
[40] 惠俊英, 生雪莉. 水下声信道 [M]. 哈尔滨: 哈尔滨工程大学出 water acoustic physics, signal processing and ocean en-
版社, 2011: 43. vironment[J]. Journal of Applied Acoustics, 2006, 25(6):
[41] 刘雄厚, 孙超, 杨益新, 等. 深海水下目标大深度主动探测性 325–327.
能评估 [C]//中国声学学会水声学分会 2019 年学术会议论文 [55] 李整林, 杨益新, 秦继兴, 等. 深海声学与探测技术 [M]. 上海
集, 2019: 451–453. 科学技术出版社, 2020: 266–267.