Tracking more targets with less antenna: An investigation into the co-array concept

In this paper, two compressive DoA estimation algorithms are investigated, namely the sparse ruler, and the coprime sampling array. These algorithms explore the eigen matrix structure of a non uniform linear array in order to artificially synthesize a larger uniform linear array, in this way boosting the capability of a DoA tracking system beyond the theoretical limit of the number of sources that can be detected with a certain number of antenna elements. In other words, we can detect the Direction of Arrival (DoA) of more sources with less antenna elements. Crucial is that the study is based on real measurements conducted on a real demonstrator platform. The key parameters that affect the DoA estimation are investigated. The results show clearly that the sparse ruler algorithm has a better performance.