Azimuth angular superresolution of real-beam scanning radar for sea-surface target

This paper presents a deconvolution algorithm based on the Maximum likelihood (ML) criterion to realize azimuth angular superresolution of sea-surface target in the background of sea clutter. Firstly, the received signal of real-beam image in azimuth dimension was modeled as the convolution of antenna pattern and target scattering. Then the ML objective function was built according to the assumption that the sea clutter obeys Rayleigh distribution. Finally, the iterative expression was derived to recover the original scattering of sea-surface target. Compared to Poisson-based ML deconvolution method, the assumption of clutter distribution is more reasonable for the practical background. Simulations are given to verify the effectiveness of the algorithm.