Application of the Non-Local Log-Euclidean Mean to Radar Target Detection in NonHomogeneous Sea Clutter

In order to effectively detect moving targets in a nonhomogeneous sea clutter, the non-local Log-Euclidean mean is studied and an effective algorithm based on non-local Log-Euclidean mean is proposed. Firstly, the mathematical model of the received signal returned from a target is established. Then, the Log-Euclidean distance is introduced and the non-local method is employed for computing the Log-Euclidean mean. Furthermore, an adaptive matched filter with non-local Log-Euclidean mean is investigated. As the non-local method adopts samples similar to a given sample to estimate the Log-Euclidean mean, a robust covariance matrix estimation is obtained in a nonhomogeneous sea clutter. In the end, numerical simulations and real High-Frequency radar datasets are used to verify the validity of this proposed algorithm, and the results demonstrate that the proposed method not only outperforms the conventional detection method but also exhibits more robustness in a nonhomogeneous environment.