  This work presents generalized low-rank signal decompositions with the aid of
switching techniques and adaptive algorithms, which do not require
eigen-decompositions, for space-time adaptive processing. A generalized scheme
is proposed to compute low-rank signal decompositions by imposing suitable
constraints on the filtering and by performing iterations between the computed
subspace and the low-rank filter. An alternating optimization strategy based on
recursive least squares algorithms is presented along with switching and
iterations to cost-effectively compute the bases of the decomposition and the
low-rank filter. An application to space-time interference suppression in
DS-CDMA systems is considered. Simulations show that the proposed scheme and
algorithms obtain significant gains in performance over previously reported
low-rank schemes.
