Preestimation-Based Array Interpolation Approach to Coherent Source Localization Using Multiple Sparse Subarrays

In application to coherent source localization using multiple sparse uniform linear subarrays (ULSAs), the array interpolation technique with Lau or Pesavento formulation causes unacceptable interpolation errors over the entire field of view because of high sparseness of ULSAs. In this letter, we propose a modified array interpolation approach by specifying a union of nonoverlapping narrow subsectors as the in-sector to cover only the source locations preestimated roughly on an assumption that at least a single ULSA is available for coherent source localization. Furthermore, we skip noise prewhitening and employ more subarrays of the virtual uniform linear array (VULA) for forward-backward spatial smoothing (FBSS) that plays a key role in noise floor reduction as well as coherent source decorrelation.