Online Sparse reconstruction for scanning radar based on Generalized SParse Iterative Covariance-based Estimation

摘要

Scanning radar is of considerable interest in Earth observation mission. However, the coarse azimuth resolution of scanning radar is not sufficient for practical applications. Recently, the generalized sparse iterative covariance-based estimation (SPICE) algorithm was extended for scanning radar angular super-resolution, which could notably improve the angular resolution and suppress the noise amplification. In this work, further to this development, we propose an online generalized SPICE method. The implementation could update and refine the super-resolution result for each obtained data sample along beam scanning, offering a significant reduction in the required computational complexity, as compared to forming the batch implementation of the generalized SPICE method. Simulation and real data processing results are provided to validate the effectiveness of the proposed approach.