Ionospheric ionogram denoising based on Robust Principal Component Analysis
Shinan Lang, Bo Zhao, Shun Wang, Xiaojun Liu, Guangyou Fang · 2012
This paper proposes a preprocess optimization analysis called Robust Principal Component Analysis (RPCA) to eliminate the noises of ionospheric ionograms. Through the theoretical analysis of the basic principle and validity of this method and simulation results, we point out the feasibility of this method and give a useful algorithm named accelerated proximal gradient method (APGp) to solve this RPCA problem. Finally, we verify the feasibility of this method by some simulation results.