Improving Signal Separation Accuracy Using Prior Information of Arrival Direction

Abstract

Various methods are proposed to estimate the DOA (direction of arrival) of source signal. MUSIC method uses the peak point of MUSIC spectrum to estimate DOA. The method that uses the image of video camera to estimate DOA is also proposed. Mixing matrix can be calculated by arranging the frequency transfer function calculated from DOA and separation matrix of source signal is equal to the inverse of mixing matrix. However, if the frequency range of source signal is wide, calculation accuracy of the separation matrix is worse since mixing matrix becomes adverse condition in low frequency. ILRMA can estimate wideband source signals precisely by updating signal power and separation matrix alternatively. ILRMA is characterized by learning the signal power in time-frequency domain using low rank approximation. However, if source signals are high rank, the learning error of signal power occurs in using ILRMA. To resolve these problems, this paper proposes a new method, which can improve separation accuracy by using the prior information of DOA. In this method, regularization term calculated from DOA is added to NMF's objective function. By adding this regularization term, signal power can be calculated correctly even if source signals are high rank. In order to verify the estimation accuracy of source signals in using proposed method, numerical experiment was conducted and the estimation accuracy in using proposed method was compared with that in using ILRMA under the condition that DOA was already-known. In this experiment, three source signals and six noises were mixed and three sensors received the mixed signals. The estimation accuracy of source signals by proposed method was better than ILRMA. This experimental result proves that proposed method can improve the estimation accuracy of source signals by using DOA even if source signals are high rank and exist in wideband frequency range.