Minimum-Entropy Autofocusing Based on Re-PSO for Ionospheric Scintillation Mitigation in P-Band SAR Imaging

The spaceborne synthetic aperture radar (SAR) system working at P-band, is vulnerable to the ionospheric effect. The ionospheric scintillation will introduce random phase fluctuations into the SAR signal and deteriorate the imaging performance. In this paper, a minimum-entropy autofocusing method based on the intelligent optimization strategy is proposed to compensate for the scintillation phase error in spaceborne P-band SAR images. A refined particle swarm optimization (Re-PSO) is proposed to provide an intelligent strategy in SAR autofocusing. Compared with the traditional minimum-entropy autofocusing methods, the proposed Re-PSO algorithm is a heuristic method which has extremely strong exploring abilities to the global optimum. The genetic multi-crossover operator and the gradient accelerator are utilized to improve the convergence property of the basic PSO. Furthermore, since the isolate strong scatterers are not required in minimum-entropy SAR autofocusing, the proposed method has strong robustness. The simulations on point and area targets validate the effectiveness and better performance of the proposed method.