An Enhanced Subspace-based Optimization Method with the Cross-correlated Term

In this paper, we proposed the cross-correlated subspace-based optimization method (CC-SOM) to solve inverse scattering problems. CC-SOM combines the concept of subspace partition and the cross-correlated cost function, which can determine the deterministic part of the induced current by spectrum analysis and the rest part by an iterative method. It enables higher inversion accuracy, faster convergence, and better robustness than the classical SOM and cross-correlated contrast source inversion (CC-CSI).