A truncated singular value decomposition method for angular super-resolution in scanning radar

Angular super-resolution of scanning radar is an important problem in radar system. Some deconvolution methods are used to realize the angular super-resolution in scanning radar. However, the ill-posed nature of the deconvolution problem leads to the noise amplification in the angular super-resolution image. This phenomenon brings the difficulty in signal detection and tracking. In this paper, a deconvolution algorithm based on truncated singular value decomposition is proposed that achieves the angular super-resolution and noise suppression in scanning radar. To this end, we first convert the angular super-resolution task in scanning radar as an equivalent deconvolution problem. Then, the cause of noise amplification is analysed, which leads to the truncation singular value method for solving the deconvolution problem. Simulation results demonstrate that the proposed method is effective in achieving angular resolution with suppressing the noise amplification.