Radar angular superresolution algorithm based on Bayesian approach

Angular resolution is the key parameter of radar. Conventional means of increasing angular resolution are dependent on the size of the antenna aperture. In framework of maximum likelihood, this paper presents an iterative algorithm to restore the target location information and then to obtain angular superresolution. Theoretical analyses indicate that algorithm accelerates convergence speed and achieves angular superresolution efficiently, and computational burden is relatively small. Simulation results show that the algorithm can efficiently attenuate the effect of antenna pattern convolution and highly enhance angular resolution; test data results show an order of improvement in angular resolution over real aperture image, also confirm that the method could obtain angular superresolution.