Fast robust adaptive array processing using feedback orthogonalization

The aim of this paper is to present a new fast robust adaptive array processing algorithm. The key advantage of the algorithm is in its high stability to numerical errors and digital noises that enables real-time implementations on substantially faster and cheaper standard fixed-point ASIP/ASIC multi-core systems. The algorithm computes the conjugate direction decomposition (CDD) of the optimum weight vector using a novel feedback version of the modified Gram-Schmidt orthogonalization (MGSO) method to suppress propagation and accumulation of numerical errors and noises. Overall the new algorithm outperforms other known fast adaptive algorithms in terms of actual convergence time, reliability and computational cost.