Applying the remote microphone method in the filtered error least mean squares algorithm

Abstract

An active noise control (ANC) system generates an anti-noise wave to reduce the noise level at a control point, where the error microphone is conventionally placed. Virtual sensing techniques are developed for situations when the error microphone cannot be permanently placed at the control point. The remote microphone (RM) method is one of the most straightforward virtual sensing methods. Previous studies have demonstrated that the performance of the RM method is influenced by the causality between the physical and virtual error microphones, which can be resolved by introducing a delayed version of the virtual error signal. So far, the RM method has mainly been examined with the filtered reference least mean squares (FxLMS) algorithm. This paper applies the RM method in the filtered error least mean squares (FeLMS) algorithm. The FeLMS algorithm introduces an adjoint filter to reduce the computational complexity of the ANC system. The delay incurred by the adjoint filter is just right to implement the delayed virtual error signal of the RM method.