Scanning radar angular super-resolution using fast split spice

Recently, a split sparse iterative covariance-based estimation (Split SPICE) method has been proposed for synthetic aperture radar (SAR) imaging to enhance the azimuth resolution. However, this method suffers the significant high computational complexity, which is caused by the high-dimensional matrix inversion. To this end, a fast Split SPICE approach is proposed to reduce the tricky complexity of the traditional ones for airborne scanning radar super-resolution imaging. It takes advantage of the low displacement rank feature of the Toeplitz matrix to solve the matrix inversion by Gohberg-Semencul (GS) representation efficiently. Compared with traditional methods, the proposed method offers higher computational efficiency for scanning radar super-resolution imaging with marginal resolution loss. The simulation results verify the effectiveness of the proposed method.