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The paper presents a general framework for spatial wavelet processing in the context of a uniform linear array. By defining the scale in terms of the spatial sampling resolution, the spatial multi-resolution structure inherent in the array signal has an explicit representation based on the wavelet decomposition. Beamforming can then be implemented on the subband data. The new framework is applied to a real sonar target detection problem, and the traditional time-delay beamformer shows an improved computational efficiency. The efficiency gain is proportional to the number of sensors for targets near the broadside direction.