Virtual sensing at low computational cost for active noise control

In active noise control, global noise attenuation is not achievable when the size of the controlled environment is significantly larger than the wave length of the noise, and satisfactory performance is obtained only in the immediate vicinity of the sensors. There is therefore need for methods that can extend the control to positions that are different from the sensor locations, such as virtual sensing. The latter, unfortunately, requires a model to determine the control, which entails a high computational cost if the system dynamics are identified from data. This paper deals with the problem of reducing the computational cost required for the system identification of a one dimensional enclosure. First, an analytical model for virtual sensing is proposed that employs two microphones instead of one as in the usual virtual sensor schemes. A system identification procedure is then used to obtain the virtual sensor. Both techniques (the analytical and the identification-based) are finally evaluated, by comparing the estimated signal to the measured one.