Subspace Direction Finding With an Auxiliary-Vector Basis
Rohan Grover, Dimitris A. Pados, Michael J. Medley · IEEE Transactions on Signal Processing · 2007
We develop a new subspace direction-of-arrival (DOA) estimation procedure that utilizes a noneigenvector basis. Computation of the basis is carried out by a modified version of the orthogonal auxiliary-vector (AV) filtering algorithm. The procedure starts with the linear transformation of the array response scanning vector by the input autocorrelation matrix. Then, successive orthogonal maximum cross-correlation auxiliary vectors are calculated to form a basis for the scanner-extended signal subspace. As a performance evaluation example, our studies for uncorrelated sources demonstrate a gain in the order of 15 dB over MUSIC, 7 dB over ESPRIT, and 3 dB over the grid-search maximum likelihood DOA estimator at probability of resolution 0.9 with a ten-element array and reasonably small observation data records. Results for correlated sources are reported as well