奇异值分解(SVD)在位场数据去噪中的应用

根据奇异值分解原理,分析其在位场去噪中的可行性,提出了一种判断有效阶次k的方法。对多边形厚板模型的重力异常进行奇异值分解去噪和小波去噪效果的对比,证明了奇异值分解去噪的有效性和优势。将其应用于实测重力数据的处理中,取得较好的效果。理论模型和实测资料的处理结果表明:基于奇异值分解的去噪方法可以有效地去除随机噪声,提高数据处理和解释的精度。

Application of singular value decomposition (SVD) de-noising in potential field data

According to the principle of singular value decomposition，the authors analyze its feasibility in po- tential field de-noising，and put forward a judgment method of effective order k． Compared the results between sin- gular value decomposition de-noising and wavelet de-noising of gravity anomalies of polygon plate model，it is proved the validity and advantage of the singular value decomposition de-noising． It is applied in the measurement of gravity data processing，and the good results have been achieved． The theoretical model and the measured data processing results show that the de-noising method based on singular value decomposition can effectively remove the random noise，improve the accuracy of data processing and interpretation．