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基于多源信息融合的浅海超低频声源目标探测关键技术及实现
孙显彬,郑轶,于非
1.山东省科学院 海洋仪器仪表研究所;2.中国科学院海洋研究所
摘要:
掌握浅海复杂水下环境中超低频声波传播规律是实现探测目标距离和深度准确估计的基础。前期研究发现:现有的声传播模型研究浅海超低频声波的传播特性与海试中发现的传播特性吻合度较差,声源在不同深度运动时的信号特征明显不同。本文以多传感器信息融合理论为指导,结合现代信息处理技术与数据驱动建模及科学计算技术,研究浅海超低频声源目标激发共存地震波的复合声场中超低频声波传播特性和数据驱动建模的水下目标深度识别等关键技术是一种新的科研思路。在浅海超低频声源目标探测、改善海洋水下声学监测手段、提高声呐探测设备的测量准确度、精度方面具有重要的理论意义,对周边海域为浅海的我国海防具有实战价值。
关键词:  多源信息融合  浅海  超低频  目标探测
DOI:10.11759/hykx20180511001
分类号:O427.1
基金项目:山东省自主创新重大关键技术项目(2014GJJS0101),山东省自然科学(ZR2013DM014)
Research on Techniques of Ultra-low Frequency Source Target Detectionin Shallow Sea Based on Multi-source Information Fusion
SUN Xian-bin1, ZHENG Yi2, YU Fei3
1.Shandong Academy of Sciences;2.Institute of Oceanographic Instrumentation,Shandong Academy of Sciences;3.Institute of Oceanography,Chinese Academy of Sciences
Abstract:
In shallow sea complex underwater environment to master the law of ultra -low frequency acoustic propagation is the basis for the accurate estimation of detection target distance and depth. The previous study found that the existing acoustic propagation model studied the propagation characteristics of shallow ultra-low frequency acoustic waves and the propagation characteristics found in the sea tests were less consistent, and the signal characteristics of the acoustic sources were significantly different when moving at different depths.This paper is guided by multi-sensor information fusion theory, combined with modern information processing technology and data-driven modeling and scientific computing technology. It is a new research idea to study the characteristics of super low frequency acoustic wave propagation and the underwater target depth recognition of data-driven modeling in shallow sea ultra-low frequency acoustic source. In shallow sea ultra-low frequency acoustic source target detection, improving underwater acoustic monitoring means, improving the measurement accuracy and precision of Sonar detection equipment has important theoretical significance, and it has practical value for Chienes coastal defense with shallow sea area.
Key words:  Multi-source Information Fusion  Shallow Sea  Ultra-low Frequency Source  Depth Classification
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