An efficient offline scheme to compute an FIR controller for active reduction of acoustic reflections in an anechoic chamber

This paper presents an offline iterative scheme to efficiently obtain a fixed controller for larger scale active noise control systems. The approach reduces the computational complexity of the scheme by applying preconditioning and prewhitening via the frequency domain, followed by conversion of the filters to the time domain using the inverse Fourier transform. Although the filters are not necessarily causal, causality is ensured by utilizing delay and truncation techniques. The use of these filters in the iterative scheme leads to improved convergence, lowering computational effort while also being memory efficient. Regularization is applied to maintain convergence while allowing for larger step sizes between iterations. The controller minimizes the reflected sound field, which is measured by the performance sensors. The signals of the performance sensors are computed with the Kirchhoff–Helmholtz integral. The results show that this allows for global control of the reflected sound field within the microphone area. A simulation is shown of a noise control setup with 12 primary sources, 12 secondary sources, 12 reference sensors, 12 error sensors and 37 performance sensors. Although the delay of the filters in the direct path is reflected in the filter coefficients, this delay can be truncated to obtain filter coefficients without any delay. Despite the truncation resulting in an average loss in performance of 1.6 dB, the control system without any delays is able to reduce the average reflected sound at the performance sensors by 13.8 dB, when the reference signal is known.