A stochastic subspace algorithm for blind channel identification in noise fields with unknown spatial color
P. Vandaele, Marc Moonen · 1999
The blind channel identification problem is formulated in a stochastic state space framework. Starting from a state space model we present a preprocessing step based on two orthogonal subspace projections. Using these orthogonal projections, we derive an algorithm for blind channel estimation which is insensitive to the spatial color of the noise. The performance of this new algorithm is demonstrated through simulation examples.