地层传播弹性波接收端的多径分离与分集接收方法的研究
[Abstract]:In this paper, according to the multipath propagation characteristics of elastic wave in geodetic channel, the multipath separation and diversity reception of elastic wave signal are carried out by using RAKE receiver and blind source separation under the condition of inherent source signal and mutation source signal, respectively. The signal-to-noise ratio of the elastic wave receiver is improved and the communication quality is improved. (1) the multipath propagation characteristics of the elastic wave in the geodetic channel are analyzed. Firstly, the basic theory of elastic wave propagation is studied, and then the propagation characteristics of elastic wave in strata are analyzed. Finally, the multipath propagation model of elastic wave propagation in strata is established. The multi-path propagation of elastic wave is simulated by Matlab and Comsol, and the correctness of the model is verified. The results show that with the increase of coal seam thickness, the time delay of each reflection wave of elastic wave is longer than that of direct wave. With the increase of time, the energy of elastic wave decays close to exponential law. (2) multipath separation and diversity reception of elastic wave with inherent source characteristics are studied. The existing diversity and merging methods are analyzed and compared. The path diversity is selected to obtain the independent multipath signal, and the maximum ratio combination is used to receive the multipath signal. The RAKE receiving scheme of elastic wave multipath signal is designed. The elastic wave RAKE receiving model is established and simulated by Matlab software. The results show that the elastic wave multipath problem can be effectively solved by RAKE receiver. The signal-to-noise ratio (SNR) of the receiver is improved. (3) the multipath separation and diversity reception of elastic waves with variable source characteristics are studied. Firstly, the blind source separation model of elastic multi-path signal is established. The blind source separation algorithm based on the global optimal algorithm and the blind source separation algorithm based on the maximum signal-to-noise ratio are studied. The two algorithms are simulated by Matlab software. The results show that both algorithms can separate multipath signals, but the blind source separation algorithm based on the maximum signal-to-noise ratio is better than the blind source separation algorithm based on global optimization.
【学位授予单位】:山东科技大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TD65
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