Recursive filter estimation for feedforward noise cancellation with acoustic coupling

The basic principle of feedforward noise cancellation for broadband active noise reduction is based on the availability of a reliable measurement of the noise source. Reliability is compromised in case the noise measurement is acoustically coupled to the actual active noise cancellation (ANC), as stability and performance of the feedforward compensation becomes ambiguous. This paper presents a framework to recursively estimate a feedforward filter in the presence of acoustic coupling, addressing both stability and performance of the active feedforward noise cancellation algorithm. The framework is based on fractional model representations in which a feedforward filter is parameterized by coprime factorization. Conditions on the parameterization of the coprime factorization formulated by the existence of a stable perturbation enables stability in the presence of acoustic coupling. In addition, the paper shows how the stable perturbation can be estimated on-line via a recursive least-squares estimation of a generalized FIR filter to improve the performance of the feedforward filter for ANC.