A PSEUDOINVERSE UPDATE ALGORITHM FOR RANK-REDUCED COVARIANCE MATRICESFROM 2-D DATA

A number of algorithms have a higher resolution than the common beamfo rmer, These often require the calculation of a pseudoinverse of a matr ix, which makes the algorithm very slow for repeated applications, We consider updating the pseudoinverse for window motions either in time or in space for two dimensional (2-D) data taken from a linear array, Our results are shown to reduce the computational complexity of the mu ltiple sidelobe canceller (MSC) [1], for example, by more than 75% for a downward window movement (with time) and more than 55% For a sidewa ys window movement (across traces).