Conjugate gradient projection subspace tracking

We present a conjugate gradient subspace projection algorithm for subspace tracking. We base the algorithm on the subspace projection cost function introduced by B. Yang (see IEEE ICASSP, p.IV145-IV148, 1993 ), and use a conjugate gradient iteration to provide rapid convergence. The update complexity is O(r/sup 2/m) where r is the dimension of the tracked subspace which is assumed to be much smaller than m. The algorithm has immediate application in radar and sonar array signal processing systems. >