摘要
Standard adaptive beamforming or matched field processing requires accurate replica fields finely gridded over the search parameter space for localization with sidelobe control. This paper presents an Adaptive Matched Field Processing （AMFP） algorithm, which aims at gaining robustness for the environmental mismatch, and simultaneously reducing the real-time computational load. The new method integrates the merits of several AMFP beamformers with neighboring location constraints, environmental perturbation constraints and sector focusing constraints. The robustness and effectiveness of the suggested algorithm has been illustrated through the numerical simulation and the experimental Mediterranean benchmark shallow-water data.
Standard adaptive beamforming or matched field processing requires accurate replica fields finely gridded over the search parameter space for localization with sidelobe control. This paper presents an Adaptive Matched Field Processing （AMFP） algorithm, which aims at gaining robustness for the environmental mismatch, and simultaneously reducing the real-time computational load. The new method integrates the merits of several AMFP beamformers with neighboring location constraints, environmental perturbation constraints and sector focusing constraints. The robustness and effectiveness of the suggested algorithm has been illustrated through the numerical simulation and the experimental Mediterranean benchmark shallow-water data.
基金
This work was supported by the National Natural Science Foundation of China (10304015, 60472073) and the Foundation from State Key Laboratory of Acoustics.
