Use of random noise for on-line transducer modeling in an adaptive active attenuation system

Abstract

Active sound attenuation systems may be described using a system identification framework in which an adaptive filter is used to model the performance of an unknown acoustical plant. An error signal may be obtained from a location following an acoustical summing junction where the undesired noise is combined with the output of a secondary sound source. For the model output to properly converge to a value that will minimize the error signal, it is frequently necessary to determine the transfer function of the secondary sound source and the path to the error signal measurement. Since these transfer functions are unknown and continuously changing in a real system, it is desirable to perform continuous on-line modeling of the output transducer and error path. In this article, the use of an auxiliary random noise generator for this modeling is described. Based on a Galois sequence, this technique is easy to implement, provides continuous on-line modeling, and has minimal effect on the final value of the error signal.