水中高速小目标被动检测模型及其应用

胡 桥; 郝保安; 易 红; 杨云川

doi:10.11993/j.issn.1673-1948.2012.04.005

水中高速小目标被动检测模型及其应用

doi: 10.11993/j.issn.1673-1948.2012.04.005

胡桥^1,2,
郝保安^1,2,
易红²,
杨云川^1,2

1.
水下信息与控制重点实验室, 陕西西安, 710075
2.
中国船舶重工集团公司第705研究所, 陕西西安, 710075

基金项目: 陕西省科学技术研究发展计划(2010KJXX-09)

详细信息

作者简介:
胡桥(1977-), 男, 博士后, 高工, 研究方向为现代信号处理、水声目标检测及智能识别、系统工程.

中图分类号: TJ630.34; TN911.7
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- 文章访问数: 1060
- HTML全文浏览量: 1
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- 被引次数: 0
出版历程
- 收稿日期: 2011-05-23
- 修回日期: 2011-08-23
- 刊出日期: 2012-08-20

Passive Detection Model for Underwater High-speed Small Targets with Application

1.
Science and Technology on Underwater Information and Control Laboratory, Xi′an 710075, China
2.
The 705 Re-search Institute, China Shipbuilding Industry Corporation, Xi′an 710075, China

摘要

摘要: 针对水中高速小目标难以准确检测的问题, 结合3D超波束形成(3D-HBF)方法具有灵活控制窄波束和低旁瓣的特性, 以及模糊支持向量数据描述(FSVDD)检测器具有优良的目标检测性能这两者的优势, 构建了水中高速小目标被动检测模型和具体实施方法。在该方法中, 高速小目标的辐射噪声信号经过3D-HBF后, 将获得的波束响应输出向量输入到FSVDD检测器中, 从而实现目标的自动检测和测向。将该方法应用于水下高速小目标检测的实航试验中, 结果表明, 同基于常规波束形成的检测器相比, 其具有更好的检测性能、目标检测准确率和较高的方位估计精度。
- 水中高速小目标 /
- 被动检测 /
- 超波束形成 /
- 支持向量数据描述
Abstract: For accurately detecting underwater high-speed small targets, a novel passive detection model is proposed based on the three-dimensional hyper beam forming (3D-HBF)method with flexible control of beam width and side lobe, and the fuzzy support vector data description (FSVDD) detector with excellent target detection capability. And its im-plementation method is also discussed. In the scheme, 3D-HBF is carried out to obtain the beam response vectors (BSV) from original underwater acoustic signals, and then the BSV are input to the FSVDD detector to detect and orient the underwater targets intelligently. The application of the proposed model to target detection of underwater high-speed small targets in sea trial demonstrates its better detection performance and higher detection success rate and localization accuracy, compared with the conventional beam forming based detection method.
- underwater high-speed small target /
- passive detection /
- hyper beam forming /
- support vector data descrip-tion(SVDD)

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参考文献(7)

[1]	Schlieter H, Eigenbrod H. Method for the Formation of Radiated Beams in Direction Finder Systems[P]. United States Patent: US 6021096.
[2]	Schlieter H. Passive Sonar Detection Improvement by HyperbeamTM Technique[C]//UDT, Europe 2006, Ham-burg, Germany, 2006: 7A-2.
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[4]	胡桥. 水中目标新型被动检测理论及方法研究[D]. 西安: 中国船舶重工集团公司第705研究所, 2008. Hu Qiao. Research on New Passive Detecting Theories and Methods for Underwater Targets[D]. Xi′an: The 705 Research Institute, 2008.
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[7]	胡桥, 何正嘉, 訾艳阳,等. 基于模糊支持矢量数据描述的早期故障智能监测诊断[J]. 机械工程学报, 2005, 41(12): 145-150. Hu Qiao, He Zheng-jia, Zi Yan-yang, et al. Incipient Fault In-telligent Monitoring and Diagnosis Based on Fuzzy Support Vector Data Description[J]. Chinese Journal of Mechanical Engineering, 2005, 41(12): 145- 150.