CAJ | 학술논문

时间域航空电磁数据经预处理后，存在残余噪声，严重影响晚期道数据质量。提出一种基于主成分分析的去噪方法，通过对航空电磁剖面数据的自相关矩阵进行奇异值分解，得到特征值及对应的特征向量，将电磁数据通过旋转矩阵（特征向量矩阵的转置）进行线性映射，得到其主成分。大特征值对应的低阶主成分反映相关性较强的电磁信号，而小特征值对应的高阶主成分反映不相关噪声。采用低阶主成分与特征向量重构电磁数据能够去除不相关噪声。采用主成分分析法分别进行了仿真数据与实测数据的主成分特征分析与噪声去除。仿真数据去噪后，信噪比提高了13 dB；而野外飞行实测数据的噪声水平也由±25 nT/s 降低到±8 nT/s。
시간역항공전자수거경예처리후，존재잔여조성，엄중영향만기도수거질량。제출일충기우주성분분석적거조방법，통과대항공전자부면수거적자상관구진진행기이치분해，득도특정치급대응적특정향량，장전자수거통과선전구진（특정향량구진적전치）진행선성영사，득도기주성분。대특정치대응적저계주성분반영상관성교강적전자신호，이소특정치대응적고계주성분반영불상관조성。채용저계주성분여특정향량중구전자수거능구거제불상관조성。채용주성분분석법분별진행료방진수거여실측수거적주성분특정분석여조성거제。방진수거거조후，신조비제고료13 dB；이야외비행실측수거적조성수평야유±25 nT/s 강저도±8 nT/s。
There is still residual noise which affects the quality of later channel data after preprocessing for time domain airborne electromagnetic data. An approach was proposed to remove the residual noise based on principal component analysis. The principal components were computed through the rotation matrix which is the transpose of eigenvectors matrix. The low-order principle components associated with the big eigenvalues reflect the correlated electromagnetic signals, while high-order principle components associated with the small eigenvalues are corresponding to the uncorrelated the noise. Therefore, the electromagnetic data are reconstructed by suitable number of the low-order components to remove uncorrelated noise. The experimental results of the simulation data show that the SNR is improved of 13 dB. The peak to peak value of the latest two channels for the field survey profile data is reduced from ±25 nT/s to ±8 nT/s after noise removal.