Abstract

Imaging efficiency has become a key problem for the application of synthetic aperture sonar (SAS) as the volume of raw data to be processed increases. In order to solve the imaging problem of low efficiency, a fast parallel range Doppler imaging algorithm for synthetic aperture sonar based on multicore platform with shared memory is presented. The time-consuming processing steps such as range compression, fixed phase compensation, range cell migration compensation and azimuth compression are parallelized by OpenMP instructions in the shared memory environment, which greatly speeds up the imaging process. The imaging tests performed on simulated and real SAS data confirm the validity and efficiency of the proposed method.

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