High-order subspace-based algorithms for passive localization of near-field sources

A vast majority of the existing eigen-decomposition based localization schemes invoke the plane-wave assumption when estimating the direction-of-arrival of multiple sources. A fourth-order cumulant based TLS-ESPRIT like algorithm is proposed for passive localization of near-field sources using observations collected from a single uniform linear sensor array. The new approach exploits the multiple-rotational invariance among certain cumulant-domain signal sub-spaces for passive range and bearing estimation. The algorithm combines the Gaussian noise insensitivity and higher resolution capabilities of cumulants with the improved precision, accuracy and computational advantages of invariance and total least squares methods to yield simultaneous, search free estimates of near-field location parameters.