【作者】 马超群； 林巨； 张家铭；

【Author】 MA Chao-qun;LIN ju;ZHANG Jia-ming;Pilot National Laboratory for Marine Science and Tech nology(Qingdao);Ocean University of China;

【机构】 青岛海洋科学与技术试点国家实验室； 中国海洋大学；

【摘要】 由于浅海海域水平传播的航船噪声能量过大,传统被动测深技术经过自适应波束形成方法后仍不能获得很好的反演结果。因此需要对噪声数据进一步优化处理。这篇文章针对青岛近海测得的海洋环境噪声数据在利用奇异值分解(SVD)和经验正交函数(EOF)对噪声数据进行再重构的基础上,结合压缩感知理论,构建了压缩感知测深模型,通过对海底搜索空间进行分层可以将非线性模型转换为线性模型,进而通过凸优化工具箱(CVX)对EOF再重构后的数据进行压缩测深反演,改进了海底分层信息反演准确度。更多还原

【Abstract】 Due to the excessive noise energy of the horizontally propagated ship in shallow seas,the traditional passive sounding technique still cannot obtain good inversion results after the adaptive beam forming method.Therefore,it is necessary to further optimize the noise data.Based on the singular value decomposition(SVD)and empirical orthogonal function(EOF)to reconstruct the noise data,this paper builds a compressed sensing based on the marine environmental noise data measured in Qingdao offshore.In the model,the nonlinear model can be transformed into a linear model by layering the seabed search space,and the compressed depth inversion of the EOF reconstituted data is improved by the convex optimization toolbox(CVX),which improves the seabed stratification.Information inversion accuracy.更多还原