A robust FLS algorithm for linearly-constrained adaptive filtering

A robust approach to implement the FLS algorithm for linearly constrained adaptive filtering is derived in this work. The robustness is provided by means of an additional correcting term which is also updated by a LS procedure. In fact, the novel algorithm works as the LS version of the classical LMS-based Frost algorithm. Simulation results with a long data input sequence show the performance of the proposed technique.<>