A minmax approach to adaptive matched field processing in an uncertain propagation environment

Adaptive array processing algorithms have achieved widespread use because they are very effective at rejecting unwanted signals (i.e., controlling sidelobe levels) and in general have very good resolution (i.e., have narrow mainlobes). However, many adaptive high-resolution array processing algorithms suffer a significant degradation in performance in the presence of environmental mismatch. This sensitivity to environmental mismatch is of particular concern in problems such as long-range acoustic array processing in the ocean where the array processor´s knowledge of the propagation characteristics of the ocean is imperfect. An adaptive minmax matched field processor is formulated which combines adaptive matched field processing and minmax approximation techniques to achieve the effective interference rejection characteristic of adaptive processors, while limiting the sensitivity of the processor to environmental mismatch. An efficient implementation and alternative interpretation of the processor are developed. The performance of the processor is analyzed using numerical simulations