基于压缩感知的水声数据压缩与重构技术

在水声信号处理中,数据量大造成的数据处理压力不容忽视。为了有效地提取水声数据中的有用信息,同时缓解数据量大带给水声数据传输的压力,研究压缩感知(Compressed Sensing,CS)的基本原理及其关键技术,综述了CS理论框架并着重介绍了稀疏变换、观测矩阵设计和重构算法三个方面。通过仿真实验表明了压缩感知技术能够有效地用于模拟数据的压缩与重构。重点对水声舰船噪声信号进行了基于CS的压缩与重构仿真实验,验证了压缩感知技术运用于水声数据处理的有效性,从而达到提高水声数据传输速率的目的。

Compressed sensing based acoustic data compression and reconstruction technology

In underwater acoustic signal processing, the pressure on data processing due to large amount of data cannot be neglected. In order to effectively extract the useful information in the underwater acoustic data, and meantime to alleviate the pressure of the large amount of data on underwater acoustic data transmission, the basic principle and key technology of CS（Compressed Sensing） are studied in this paper, including that the theoretical framework of CS is reviewed and emphatically three basic aspects of CS technology, such as the sparse transformation, observation matrix design and reconstruction algorithm, are discussed. Simulation experiments show that the CS technology can be effectively applied to simulated data compression and reconstruction. Mainly, the simulation experiment of the CS based compression and reconstruction technology for underwater ship noise signal is conducted in this paper, and the results validate that the compressed sensing technology can be successfully applied in underwater acoustic data processing to achieve the goal of lowering underwater acoustic data transmission rate.