Abstract
The limited bandwidth of a single source normally restricts the imaging resolution for the subsurface target. Multi-frequency acquisition is a promising way to enhance the resolution with reasonable data fusion. An Ormsby wavelet based theoretical study confirms the significance of both the low and high frequencies for improving the resolution by means of peak duration and side-lobe oscillation level. To avoid over-boosting the noise during the data fusion, we propose a joint deconvolution approach to associate the single-frequency data with the target function directly. A weighted matched filter is accordingly derived based on the signal-to-noise ratio of the multi-frequency data. Error analysis shows that the joint weighted deconvolution based data fusion achieves better noise control compared to the direct-summation based deconvolution. Both wedge model based synthetic result and ground penetrating radar acquired field data example confirm the effectiveness of the proposed data fusion approach on resolution enhancement.
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