We present a new application of a method based on the radon transform for data interpolation and signal-to-noise separation of teleseismic wavefields recorded by regional seismic arrays. The method exploits the plane wave nature of direct arrivals and receiver side scattered arrivals from regional scale structure by decomposing the recorded wavefield into a plane wave basis (linear radon transform). Casting the radon transform as an inversion problem allows the incorporation of time-dependent weighting schemes and model variance tuning which are helpful in minimizing artefacts related to the transform process while enhancing lower amplitude arrivals. The procedure begins with an estimate radon transform of the input data panel. A mute is applied in the radon domain to isolate portions of the radon panel that represent plane waves with different moveouts (similar to +/-.025 s km(-1)) relative to the direct arrival. The inverse transform of the estimated noise is subtracted from the input data to produce an estimate of the desired signal without plane waves following undesired moveouts, white ambient noise, and arrivals not represented well by plane waves (diffractions). Inverse transformation of estimated signal in the radon domain produces a natural way to interpolate in the data domain due to the implicit assumption that a plane wave basis provides the most compact representation of the teleseismic wavefield. This processing scheme presents an important addition to standard teleseismic imaging processing flows that attempt to exploit irregularly, sampled data.
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