Target detection in sea clutter via weighted averaging filter on the Riemannian manifold

This paper proposes a weighted averaging filter procedure combined with a Riemannian geometry method to carry out a target detection in sea clutter. In particular, the weighted averaging filter, conceived from a philosophy of the bilateral filtering in image denoising, is presented on a Riemannian manifold of Hermitian positive-definite matrix. This filter acts as a clutter suppression procedure in the detection framework of the algorithm proposed in this paper, and can improve the detection performance. The principle of detection is that if a location has enough dissimilarity from the Riemannian mean or median estimated by its neighboring locations, targets are supposed to appear at this location. Numerical experiments and real sea clutter data are given to demonstrate the effectiveness of the proposed target detection algorithm.