阵列信号维纳滤波用于主动声呐图像增强处理

声呐图像的噪声背景抑制是提高水下目标检测能力的重要问题。针对声呐图像背景斑点噪声强、目标轮廓模糊、目标回波对比度低等问题，利用确定性目标回波信号与随机分布的干扰噪声之间的相关统计特性差异，采用基于最小均方差准则的阵列信号维纳滤波器，通过主动最小方差无畸变响应（Minimum Variance Distortionless Response，MVDR）波束形成和后置维纳滤波的两级处理，去除声呐随机噪声背景。试验数据的处理结果表明：在噪声干扰条件下，相比于常规波束形成（Common Beamforming，CBF），主动MVDR处理提高了目标回波的局部信噪比，后置维纳滤波处理降低了随机分布的斑点噪声，使声呐图像的清晰度得到增强。

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.