Sparse MIMO architectures for through-the-wall imaging

Compressive sensing and sparse array processing has provided new approaches to improve radar imaging systems. This paper, explores the potential of sparse Multiple-Input-Multiple-Output (MIMO) radar arrays to significantly reduce the cost of through-the-wall imaging (TWI). We analyze three well-known sparse array structures-nested arrays, co-prime arrays and random arrays-and examine their performance in the presence of common types of layered walls. The reconstruction is performed by formulating and solving a wall parameter estimation problem in conjunction with a sparse reconstruction problem that takes the wall parameters into account. Our simulation results demonstrate the effectiveness of our approach and validate the performance of the system for the three different MIMO sparse array structures.