Source Localization Using Sparse Large Aperture Arrays

In this paper, a novel source/target localization approach is proposed using a number of sensors (surrounding or not surrounding one or more sources) to form a sparse large aperture array of known geometry. Under a large array aperture, the array response (manifold vector) obeys a spherical wave rather than a plane wave propagation model. By rotating the array reference point to be at each of the array sensors, a number of covariance matrices are constructed. It is shown that the eigenvalues of these covariance matrices are related to the source location with respect to the array reference point. The proposed approach is robust to channel fading and considers both wideband and narrowband assumptions. The performance of the proposed approach is evaluated via simulations as a function of array geometry, number of snapshots (L) and signal to noise ratio (SNR) and is shown to exceed existing techniques.