Optimal MIMO array for compressive sensing image formation

Abstract

Many studies have addressed compressive sensing (CS) theory in recent years, especially the use of CS in radar 2D and 3D image formation. Much of this research suggests that sparse targets can be perfectly reconstructed according to the CS theory. However, most of these studies did not examine the design of antenna array for CS reconstruction of sparse targets. Therefore, this study investigates the design method of the Multiple-input/multiple-output (MIMO) antenna array for reconstructing sparse targets. Based on CS theory, mutual coherence of the dictionary matrix was selected as the criteria for evaluating the MIMO antenna array. The analytical expression of the criteria was derived from the MIMO echo signal. Due to the complex mathematical expression of the criteria, the genetic algorithm was used to find the optimal MIMO antenna array. Finally, a comparative simulation and a Monte-Carlo experiment were performed to validate the proposed optimal solution.

Keywords:

• multiple-input/multiple-output (MIMO)
• compressive sensing
• image formation
• optimal antenna array

Notes

This work was supported by the China Postdoctoral Science Foundation [grant number 2013M530723].