随钻测量用MEMS陀螺信号稀疏提取

Signal Extraction of MEMS Gyro Utilized in MWD Based on Sparse Representation

针对随钻测量用MEMS陀螺检测信号特性,提出采用稀疏表示的方法进行信号提取。首先从检测的陀螺调制信号构成角度,分析其信号稀疏特性;然后分析检测信号特性,构造与之最相似的过完备词典;比较已有稀疏重构算法优劣性,提出一种改进的稀疏度自适应匹配追踪算法对陀螺调制信号进行稀疏提取,进而解调真实陀螺信号;最后采用提出的改进SAMP算法于新构造的过完备字典中进行陀螺信号稀疏提取实验,并与小波阈值提取法进行实验对比,实验结果表明:采用新构造的字典和改进的SAMP算法,可以有效提取MEMS陀螺真实信号,提取效果优于传统小波阈值法。

According to the characteristics of the detected signal from MEMS gyro utilized in measurement while drilling（ MWD）,a kind of sparse representation-based gyro signal extraction method is proposed. Firstly,the sparse characteristics about the gyro detection signal is analyzed from the perceptive of the signal compositions; Secondly,the atom dictionary most similar to the gyro detection signal is designed; Thirdly,by comparing the advantages and disadvantages of the existing sparse reconstruction algorithms,a novel sparse adaptive matching pursuit algorithm is proposed to extract the real detection signals of the gyro; Finally,the proposed sparse reconstruction algorithm based on the newly designed atom dictionary was used to extract the actual gyro signal,compared with the wavelet threshold extraction method. Substantial experiments results indicate that the proposed sparse extraction-based outperformes wavelet threshold method.