Applications of cumulants to array processing: direction-finding in coherent signal environment

Dogan and Mendel (see IEEE Trans. on Signal Processing, 1994) have developed the virtual-ESPRIT algorithm (VESPA) for direction-finding and recovery of independent sources. VESPA can calibrate an array of unknown configuration and arbitrary response by using just one additional pair of identical sensors (instead of a copy of the entire array or storage of the entire array response for every possible scenario, which is required by existing alternatives). We present an approach that generalizes VESPA to handle the case of highly correlated or coherent sources. Unlike existing methods, our method is not restricted to linear arrays, and no search procedure is needed. Just as in VESPA, it is still possible to detect more sources than sensors, and suppress both Gaussian as well as non-Gaussian noise. A simulation experiment supporting our conclusions is provided