Integrated Multi-Receiver SAS Imaging: Combining Omega-k Algorithm With Two-Stage Motion Compensation and Autofocus

The Omega-k algorithm is an accurate synthetic aperture sonar (SAS) imaging algorithm, and motion compensation (MOCO) is one of the key issues to achieve high-resolution imaging. In order to solve the problem of high-precision SAS imaging of multi-receiver array under non-ideal track, this study proposes an integrated multi-receiver SAS imaging method that combines the Omega-k algorithm with two-stage MOCO and autofocus processing. Firstly, the multi-receiver array SAS echo data is converted into the equivalent data of monostatic SAS. Then, the motion errors are compensated in two stages in the Omega-k algorithm in the form of range-dependent and range-independent. Finally, coarse focused image with residual phase error are processed by block-based phase gradient autofocus (bPGA) to obtain the fine focused SAS image. The point targets simulation data with minor motion error and large motion error are processed respectively. Compared with the results processed only by Omega-k algorithm, the proposed method can effectively compensate the motion errors and remove the defocus of the imaging results caused by the residual motion error. In the case of minor motion error, only two-stage MOCO can significantly improve the focusing effect, and the improvement effect of autofocus processing is not obvious. In the case of large motion error, the entropy and contrast of the simulated data image obtained by this method are increased by about 66 % and 561 %, respectively. The point target integral sidelobe ratio is reduced from 7.37dB to -11.1dB, and the first peak sidelobe ratio is reduced from -0.13dB to -13.18dB. The improvement of these two indicators is mainly due to autofocus processing. The azimuth resolution is improved from 0.75cm to 1.81cm, which is mainly due to motion compensation. These simulation results verify the effectiveness and robustness of the proposed method.