A Small Target Detection Method in Sea Clutter Based on Feature Manifold

Target detection methods based on multidimensional features are often applied to the detection of small targets in sea clutter. However, existing algorithms do not fully utilize the correlation information between features, which to some extent limits their performance. To address this issue, this paper proposes a small target detection method in sea clutter using feature manifolds. By establishing a high-dimensional manifold representation of radar echo feature data, the radar target detection problem is transformed into a discrimination problem between two geometric points on a feature matrix manifold. This method integrates the use of multidimensional features and their correlation information, thereby effectively improving target detection performance. Experimental results on the SDRDSP dataset demonstrate that the proposed detection approach outperforms existing feature-based methods in terms of detection accuracy.