Improvement in matched field processing using the CLEAN algorithm

Adaptive matched field processing such as the minimum variance distortionless processor (MV) provides excellent sidelobe (or ambiguity) suppression capability in source localization given a perfect knowledge of the ocean environment. Unfortunately, this processing is very sensitive to sources of mismatch and robust adaptive algorithms are then employed such as a white noise constraint (WNC) often at the expense of insufficient sidelobe control. The CLEAN algorithm was introduced in radio astronomy [Astron. Astrophys. Suppl. Ser. 15, 417-426 (1974)] to produce a high quality image of the sky by reducing sidelobe-induced artifacts. In this paper, the CLEAN concept is extended to matched field processing. Numerical simulations and experimental data demonstrate that matched field processing combined with the CLEAN algorithm can improve performance, especially when a weak source is masked by sidelobes from a much stronger source.