Structure-Based Subspace Method for Multichannel Blind System Identification

In this work, a novel subspace-based method for blind identification of multichannel finite impulse response systems is presented. Here, we exploit directly the block Toeplitz channel's structure in the signal's linear model to build a quadratic cost function, whose minimization leads to the desired channel estimation up to a scalar factor. This method can be extended to estimate any predefined linear structure, e.g., Hankel, that is usually encountered in linear systems. Simulation findings are provided to highlight the appealing advantages of the new structure-based subspace method over the standard subspace method in certain adverse identification scenarios.