Due to strong interchannel interference in multichannel active noise control (ANC), there are fundamental problems associated with the filter adaptation and online secondary path modeling remains a major challenge. This paper proposes a wave-domain adaptation algorithm for multichannel ANC with online secondary path modelling to cancel tonal noise over an extended region of two-dimensional plane in a reverberant room. The design is based on exploiting the diagonal-dominance property of the secondary path in the wave domain. The proposed wave-domain secondary path model is applicable to both concentric and nonconcentric circular loudspeakers and microphone array placement, and is also robust against array positioning errors. Normalized least mean squares-type algorithms are adopted for adaptive feedback control. Computational complexity is analyzed and compared with the conventional time-domain and frequency-domain multichannel ANCs. Through simulation-based verification in comparison with existing methods, the proposed algorithm demonstrates more efficient adaptation with low-level auxiliary noise.

The performance of an ANC system largely depends on the availability of an accurate secondary path model. This is however a major challenge in multichannel ANC where the computational complexity increases significantly with the number of secondary sources and error sensors. This paper proposes wave-domain adaptive processing algorithm for multichannel ANC with online secondary modelling to cancel a tonal noise over a region of space within a reverberant room. The design is based on exploiting a special property of the secondary path model in the wave domain. A feedback control system is implemented, where a single microphone array is placed at the boundary of the control region to measure the residual signals, and a loudspeaker array reproduces secondary sources to generate the anti-noise signals and auxiliary noise for secondary path modelling. Through experimental verification in comparison with existing methods the proposed algorithm demonstrates more efficient adaptation with low-level auxiliary noise.

The performance of sound reproduction systems for spatial audio is impaired by time-variant, reverberant listening environments. To tackle this issue, the Loudspeaker-Enclosure-Microphone System (LEMS) between the loudspeakers and reference microphones in the listening environment can be identified adaptively to allow an LEMS-specific pre-processing of the loudspeaker signals. This contribution introduces a broadband implementation of a narrowband Listening Room Compensation (LRC) method with additive compensation signals, recently proposed by Talagala et al. [1], it extends the concept to higher-order compensation, and compares LRC to Listening Room Equalization (LRE) analytically. Evaluations in an image-source environment confirm the efficacy of higher-order LRC and its suitability as a complexity-reduced alternative to LRE.

Polynomial broadband beamforming designs enable an easy, smooth, and dynamic steering of the main beam. A number of design methods based on constrained optimization have been proposed recently which allow for the control of the robustness of these designs. Of course, the addition of robustness constraints reduces the number of degrees of freedom of the design. In this paper, we present a method to enhance the spatial selectivity of the robust polynomial beamformer design by exploiting the structure of symmetric arrays while still satisfying the robustness constraints. The effectiveness of this method is shown in design examples for symmetric linear and circular arrays.

Directional Audio Coding (DirAC) represents an efficient scheme to analyze and reproduce spatial sound; the coded stream consists of a single-channel audio signal and few parameters. Estimation of these parameters ideally relies on figure-of-eight microphones and one omnidirectional microphone. The figure-of-eight directivity can be efficiently approximated by first-order differential microphone arrays. However, due to spatial sampling, there are considerable deviations from the required directivity at high frequencies. These deviations lead to incorrect spatial parameter estimates; especially, the instantaneous direction-of-arrival (DOA) becomes biased and - beyond a certain aliasing frequency - ambiguous. Parameters like the DOA drive subsequent processing units, e. g., for spatial filtering. In this paper we propose a novel strategy to compensate bias and ambiguity not directly w. r. t. the DOA but the output parameters of a spatial filtering processing unit. Simulation results confirm the benefits of the novel method, which does not involve additional computational load at run-time.