Active sonar image enhancement using Wiener filtering on array signals

The noise background suppression of sonar image is crucial to improve the ability of underwater target detection. Some problems often presenting in sonar images, such as strong background speckle noise, blurred edge of target image and low contrast of target echo, need to be well solved. In this paper, the differences between deterministic features of target echo signals and the statistical characteristics of the interference noise are considered, and the Wiener filtering of array signals based on the minimum mean square error (MMSE) criterion is used to remove random noise background through the two-stage processing of active minimum variance distortionless response (MVDR) beamforming and post Wiener filtering. The experimental data processing results show that under the conditions of noise interferences, compared with common beamforming (CBF), the active MVDR processing increases the local signal-to-noise ratio of target echo, and the post-Wiener filter processing reduces the randomly distributed speckle noise, so that the clarity of sonar image is improved.