Regularised broad-band image reconstruction from sparsely sampled coherent field measurements

Ultrasonic imaging is steadily gaining popularity and sophistication as a nondestructive evaluation (NDE) technique with improvements in array hardware and signal processing. Detection and characterisation of volumetric defects such as cracks in metallic components, and in particular the sizing of these defects, requires specialised signal processing algorithms designed to exploit the maximum information in acoustic field measurements, with minimum distortion due to missing information. This paper highlights a regularised beamforming algorithm adapted from radioastronomy that is generally applicable to inverse problems involving coherent broad-band field data, and is particularly suited to image reconstruction from sparse apertures