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摘要: 小波多尺度分析方法在位场数据处理领域得到了广泛关注.目前,人们对利用该方法分离位场数据所得到的小波细节横向边缘信息认知不够深入,有必要做进一步探究.本文首先采用小波多尺度位场分离方法分离出区域和局部重力异常,然后利用haar小波变换HVD模法对局部异常信息进行多尺度分析,将所得到的小波细节信息进行水平、垂直和对角线方向分解,探测出局部异常体的横向边缘特征,并利用频谱分析方法估测出场源深度.最后,通过理论模型和南非Witwatersrand Basin航空实测重力数据进行分析,表明小波多尺度分析方法不仅能很好地实现位场分离、近似提取异常体场源深度,还可以利用小波细节信息有效地分辨出局部异常体的横向边缘特征,提高其识别精度.Abstract: Wavelet multi-scale analysis method has received extensive attention in the field of geophysical data processing. Currently, it is necessary to further explore the application of wavelet detail information based on the lack of understanding horizontal edge information of wavelet details. In this paper, the regional and local gravity anomalies were firstly separated by the wavelet multi-scale analysis, then the local anomaly information was analyzed again using the haar wavelet transform HVD method, besides, the obtained wavelet details were decomposed horizontally, vertically and diagonally. The characteristics of the lateral edges of the local anomaly were analyzed, moreover, the depth of the field source was estimated using the spectrum analysis method. Finally, through the theoretical model and the airborne measured gravity data of the Witwatersrand Basin in South Africa, it's shown that wavelet multi-scale analysis can not only realize the separation of the potential field well, but also estimate the depth of source field. What's more, it can also distinguish the lateral edge features of the local anomalies by using the wavelet detail information effectively, and improve its recognition accuracy.
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Key words:
- Gravity anomaly /
- Wavelet multi-scale analysis /
- Wavelet details /
- Depth of source field /
- Edge features
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