壓縮感知方法及在探地雷達(dá)信號(hào)采集中的模擬研究
[Abstract]:Because of the difference in dielectric properties of different subterranean media, GPR can react underground by excitation and reception of electromagnetic waves. In order to follow the Nyquist sampling law and the large amount of data collected from it, it makes a lot of difficulties in the R & D of radar instruments. Compression perception is made. It is a new signal acquisition and imaging technique, which can recover the original signal by collecting far less than Nyquist's data in the condition that the signal is sparse or sparse in the transform domain. This is of practical significance to reduce the storage pressure of the instrument and equipment. The sparsity of the ground penetrating radar signal is discussed. The characteristics of the underdetermined linear system and the sparsity of the undetermined linear system are improved by the p norm. The compressed sensing is actually compressing the data at the same time when the signal is collected, it is a path of reducing the dimension of the sampling, not the compression of the source code. It is mainly composed of signal sparse representation, signal acquisition and recovery three parts. This paper makes a comparative study on the reconstruction algorithm of compressed sensing (orthogonal matching tracking and base tracking) in the recovery signal, the correct probability of the support set, and the computational complexity. A simulation model containing the underground target body is established in this paper. At the same time, the subsurface space is discretized and the radar signal is associated with the underground target body by creating a dictionary. The low dimensional Gauss random matrix is used to collect the signal. The simulation experiment shows that the data acquisition can be greatly reduced and the reconstruction imaging of the underground target body can be realized by compression perception.
【學(xué)位授予單位】:中國(guó)地質(zhì)大學(xué)(北京)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:P631.3
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