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A number of materials used in industry exhibit highly-scattering properties which can reduce the performance of conventional ultrasonic NDE approaches. Moving Bandwidth Polarity Thresholding (MBPT) is a robust frequency diversity based algorithm for scatter noise reduction in single A-scan waveforms, using sign coherence across a range of frequency bands to reduce grain noise and improve Signal to Noise Ratio. Importantly, for this approach to be extended to array applications, spatial variation of noise characteristics must also be considered. This paper presents a new spatial-frequency diversity based algorithm for array imaging, extended from MBPT. Each A-scan in the full matrix capture array dataset is partitioned into a serial of overlapped frequency bands and then undergoes polarity thresholding to generate sign-only coefficients indicating possible flaw locations within each selected band. These coefficients are synthesized to form a coefficient matrix using a delay and sum approach in each frequency band. Matrices produced across the frequency bands are then summed to generate a weighting matrix, which can be applied on any conventional image. A 5MHz linear array has been used to acquire data from both austenitic steel and high nickel alloy (HNA) samples to validate the proposed algorithm. Background noise is significantly suppressed for both samples after applying this approach. Importantly, three side drilled holes and the back wall of the HNA sample are clearly enhanced in the processed image, with a mean 133% Contrast to Noise Ratio improvement when compared to a conventional TFM image

Clutter noise reduction for phased array imaging using frequency-spatial polarity coherence