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An extension of the PASTd algorithm to both rank and subspace tracking

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1 Author(s)
Bin Yang ; Dept. of Electr. Eng., Ruhr-Univ., Bochum, Germany

In this letter, we present an extension of the PASTd algorithm to both rank and signal subspace tracking. It has a low computational complexity O(nr), where n is the input vector length, and r denotes the signal subspace dimension. Its performance in tracking time-varying direction of arrival is comparable with that of the expensive eigenvalue decomposition and more robust than the O(n/sup 2/) rank revealing URV updating algorithm proposed by Stewart.<>

Published in:

Signal Processing Letters, IEEE  (Volume:2 ,  Issue: 9 )