新概念认知声纳初步研究

李晓花; 李亚安; 崔 琳; 刘望生

doi:10.11993/j.issn.1673-1948.2011.05.004

新概念认知声纳初步研究

doi: 10.11993/j.issn.1673-1948.2011.05.004

西北工业大学航海学院, 陕西西安, 710072

基金项目: 陕西省留学回国人员科研基金(SLZ2008006), 声纳技术国防科技重点实验室基金

详细信息

作者简介:
李晓花(1986-), 女, 在读硕士, 研究方向为水下信号与信息处理、目标检测与跟踪.

中图分类号: TJ630.34; U666.7
计量
- 文章访问数: 1737
- HTML全文浏览量: 4
- PDF下载量: 715
- 被引次数: 0
出版历程
- 收稿日期: 2011-01-11
- 修回日期: 2011-03-20
- 刊出日期: 2011-10-31

A New Concept Sonar —— Cognitive Sonar

College of Marine Engineering, Northwestern Polytechnical University, Xi’an 710072, China

摘要

摘要: 传统主动声纳系统在处理目标反射回波时, 没有考虑到声纳接收机感知的环境信息和目标特性的先验知识对发射机的影响, 发射信号参数固定, 因此很难获得理想的探测结果。本文通过对声纳基本原理和关键技术的深入研究, 受蝙蝠回声定位系统的启发, 从理论上提出了一种基于知识理论的智能声纳系统方案——认知声纳。它能够根据环境变化和对目标特性的先验知识对发射机和接收机进行联合自适应控制, 使声纳系统工作处于最优状态, 提高对水下目标信号的探测和识别能力。
- 水下目标 /
- 蝙蝠回声定位 /
- 认知声纳 /
- 目标特性
Abstract: Sonar system performance to some extent depends on the marine environment and the target characteristics from sonar receiver．In dealing with echoes, a conventional active sonar system takes no account of the influences of environmental information and prior knowledge of target characteristics perceived by sonar receiver on the transmitter, and its transmitting signal parameters are fixed, which leads to a difficulty in obtaining desired detection. In this paper, inspired by bat’s echolocation system, a cognition-based intelligent sonar system, named cognitive sonar (CS), is proposed based on the basic principle and key technology of sonar. The cognitive sonar is capable of jointly optimizing the transmitted waveforms and received echoes according to the environmental variation and the prior knowledge to significantly improve its target detection and identification performance underwater.
- underwater target /
- bat echolocation /
- cognitive sonar(CS) /
- target characteristic

HTML全文

参考文献(24)

[1]	李爱玲.声纳技术及其在军事上的应用[J]. 现代物理知识, 2003, 15(3): 47-48.
[2]	刘伯胜, 雷家煜.水声学原理[M]. 哈尔滨: 哈尔滨船舶工程学院出版社, 1993.
[3]	李启虎.数字式声纳设计原理[M]. 合肥: 安徽教育出版社, 2002.
[4]	Mitola J, Gerald Q, Maguire J. Cognitive Radio: Making Software Radios More Personal[J]. IEEE Personal Co- mmunications, 1999, 6(4): 13-18.
[5]	Haykin S. Cognitive Radio: Brain-empowered Wireless Communications[J]. IEEE Journal on Selected Areas in Communications, 2005, 23(2): 201-218.
[6]	田坦, 刘国枝, 孙大军. 声纳技术[M]. 哈尔滨: 哈尔滨工程大学出版社, 2000.
[7]	Etter C. Paul. 水声建模与仿真[M]. 蔡志明, 译. 北京: 电子工业出版社, 2005.
[8]	赵艳芳.认知的发展与隐喻[J].外语与外语教学, 1998,(10):8-10.
[9]	Haykin S. Cognitive Radar: A Way of the Future[J]. IEEE Signal Processing Magazine. 2006, 23(1): 30-40
[10]	郑南宁. 认知过程的信息处理和新型人工智能基础[J]. 中国基础科学, 2000, 2(8): 9-18. Zheng Nan-ning. Information Processing for Cognition Process and New Artificial Intelligent Systems [J]. China Basic Science, 2000, 2(8): 9-18.
[11]	白敏丹. 从软件无线电到认知无线电的无线通信发展现状[J]. 信息通信, 2010, (1): 72-76. Bai Min-dan. Base on Software Radio and Cognitive Radio Actuality of Wireless Communication[J]. Informa- tion & Communications, 2010, (1): 72-76.
[12]	曹华孝, 鲜永菊, 徐昌彪.认知无线电技术的国内外发展与研究现状[J]. 数字通信, 2009, 36(2): 51-57. Cao Hua-xiao, Xian Yong-ju, Xu Chang-biao. Survey on Development and Research of Cognitive Radio Net- works at Home and Abroad [J]. Digital Communication, 2009, 36 (2): 51-57.
[13]	Haykin S. Radar Vision[C]//IEEE International Radar Conference, 1990: 585-588.
[14]	Haykin S. Adaptive Radar: Evolution to Cognitive Radar [C]//IEEE International Symposium on Phased Array Systems and Technology, 2003: 613.
[15]	Haykin S. Cognitive Radar Networks[C]//IEEE SAM 2006 Conference, Waltham, MA, 2006: 12-14.
[16]	Hagino T, Hiryu S, Fujioka S, et al. Adaptive Sonar Sounds by Echolocating Bats[C]//IEEE Symposium on Underwater Technology and Workshop on Scientific Use of Submarine Cables and Related Technologies, 2007: 647-651.
[17]	Kalman R E. A New Approach to Linear Filtering and Prediction Problems[J]. Transactions of the ASME: Journal of Basic Engineering, 1960, 82(Series D): 35-45.
[18]	Rhodes I. A Tutorial Introduction to Estimation and Filtering[J]. IEEE Transactions on Automatic Control, 1971, 16(6): 688-706.
[19]	Julier S J, Uhlmann J K. A New Extension of the Kalman Filter to Nonlinear Systems[J]. Department of Enginee- ring Science, The University of Oxford, 1997, 66-76.
[20]	Villares J, Vazquez G. The Quadratic Extend Kalman Filter[C]//IEEE Sensor Array and Multichannel Signal Processing Workshop, 2004: 4-6.
[21]	Julier S J, Uhlmann J K. Unscented Filtering and Non- linear Estimation[J]. Proceedings of the IEEE, 2004, 92(3): 401-422.
[22]	Li Wan-chun, Wei Ping, Xiao Xian-ci. A Novel Simplex Unscented Transform and Filter[C]// IEEE International Symposium on Communications and Information Tech- nologies, 2007: 926-931.
[23]	Doucet A, Godsill S J, Andreu C. On Sequential Monte Carlo Sampling Methods for Bayesian Filtering[J]. Statiscs and Computing, 2000, 10(3):197-208.
[24]	Arulampalam M S, Maskell S, Gordon N, et al. A Tutor- ial on Particle Filters for Online Nonliear/Non Gaussian Bayesian Tracking[J]. IEEE Transactions on Signal Processing, 2002, 50(2): 174-188.