Underwater acoustic imaging (UAI) can be utilised to observe the spatial distribution of a near-field sound source. The image quality depends on the resolution and sidelobe level of conventional beamforming. The linear array-based UAI can be considered as deconvolution of a two-dimensional point spread function shift-variant model. The performance of UAI can be improved via innovative deconvolution algorithms. In this study, a non-uniform spatial resampling Richardson–Lucy (RL) fast algorithm is designed in which the amount of samples is determined by the power of the UAI output. This allows for a significant decrease in the number of samples compared to the traditional RL algorithm with similar positioning accuracy. Computer simulations and sea trials are performed to validate the effectiveness and feasibility of the proposed method.

中文翻译：

---

具有非均匀空间重采样RL反卷积的改进的水下声成像

水下声成像（UAI）可用于观察近场声源的空间分布。图像质量取决于常规波束成形的分辨率和旁瓣水平。基于线性阵列的UAI可以看作是二维点扩展函数平移变量模型的反卷积。UAI的性能可以通过创新的反卷积算法来提高。在这项研究中，设计了一种非均匀空间重采样的Richardson-Lucy（RL）快速算法，其中样本量由UAI输出的功率决定。与具有相似定位精度的传统RL算法相比，这可以大大减少样本数量。进行计算机模拟和海试以验证所提出方法的有效性和可行性。