Abstract
In order to effectively suppress large-scale strong interference and retain the useful low-frequency information of the measured magnetotelluric (MT) data, a new method of MT signal-noise separation based on sparsity adaptive stage-wise orthogonal matching pursuit (SAStOMP) is proposed. To demonstrate this technique, pulse atoms, cosine atoms and other atoms were used to build an over-complete dictionary, and fuzzy entropy was applied to control the sparsity of improved stage-wise orthogonal matching pursuit (IStOMP) algorithm, thereby realizing adaptive sparse representation. Then, we utilized SAStOMP to suppress strong electromagnetic interference and reconstruct useful MT signals. The technique was validated through simulated typical strong interference and measured MT data in ore district. The findings have proved that the proposed method can effectively eliminate large-scale strong interference and retain low-frequency useful signals in comparison with conventional methods such as remote reference (RR), orthogonal matching pursuit (OMP), and stage-wise orthogonal matching pursuit (StOMP). The obtained apparent resistivity-phase curve is smoother and more consistent, and the reflected underground electrical structure is more realistic and reliable.
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