New interference robust block adaptive filter with correlated signal input

In many applications of adaptive system identification, the output signal of an unknown system is corrupted by additive noise. When the additive noise is strong, the estimated weights of the adaptive filter cannot converge to desired weights with sufficient accuracy. In this report, we propose an interference robust block adaptive digital filter (BADF) which can improve the accuracy of the estimated weights by averaging the adaptive weight vectors. We also formulate the error variance of the estimated weights of the proposed method