Blind source extraction using spatio-temporal inverse filter

Blind source extraction is one of the most important problems for multi-sensor networks. We propose a blind source extraction and deconvolution method in the presence of noise. We use MA-model for the signal generation model, and the convolutive observation model. The parameter of MA-model and the observations are obtained from an alternating least square (ALS) algorithm. The reconstruction is done by an spatiotemporal inverse filter such that it minimizes the Euclidean distance between the original signal and the reconstruction signal. Experimental results demonstrate advantages of the proposed method.