Cluster-driven non-uniform characteristic analysis of underwater target acoustic scattering field

Underwater small targets typically exhibit non-centrosymmetric geometries, resulting in a highly spatially inhomogeneous acoustic scattering field under active sonar detection. Addressing these challenges, this paper takes the hemispherical cylindrical shell as the research object, considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of the target echo angles. First, the target echo features are extracted and feature vectors are constructed. Secondly, the t-distributed stochastic neighbor embedding algorithm is employed to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visualized feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised conditions by cluster analysis. The reconstructed local geometric structures corresponding to different categories demonstrate that the method effectively segments the angular intervals of local target structures based on their natural acoustic scattering characteristics. The study overcomes the inherent subjectivity of traditional methods for dividing angular intervals of target echoes, providing a more objective foundation for segmenting and analyzing the target’s geometrical structure.