Song H C, de Rosny J, Kuperman W A
Marine Physical Laboratory, Scripps Institute of Oceanography, University of California-San Diego, La Jolla, California 92093-0238, USA.
J Acoust Soc Am. 2003 Mar;113(3):1379-86. doi: 10.1121/1.1531510.
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.
自适应匹配场处理，如最小方差无失真处理器（MV），在对海洋环境有完美了解的情况下，能在源定位中提供出色的旁瓣（或模糊度）抑制能力。不幸的是，这种处理对失配源非常敏感，因此常采用稳健的自适应算法，如白噪声约束（WNC），但这往往以旁瓣控制不足为代价。CLEAN算法是在射电天文学中引入的[Astron. Astrophys. Suppl. Ser. 15, 417 - 426 (1974)]，通过减少旁瓣引起的伪像来生成高质量的天空图像。在本文中，CLEAN概念被扩展到匹配场处理。数值模拟和实验数据表明，匹配场处理与CLEAN算法相结合可以提高性能，特别是当一个弱源被一个强得多的源的旁瓣掩盖时。
