Noise cancellation over spatial regions using adaptive wave domain processing

This paper proposes wave-domain adaptive processing for noise cancellation within a large spatial region. We use fundamental solutions of the Helmholtz wave-equation as basis functions to express the noise field over a spatial region and show the wave-domain processing directly on the decomposition coefficients to control the entire region. A feedback control system is implemented, where only a single microphone array is placed at the boundary of the control region to measure the residual signals, and a loudspeaker array is used to generate the anti-noise signals. We develop the adaptive wave-domain filtered-x least mean square algorithm. Simulation results show that using the proposed method the noise over the entire control region can be significantly reduced with fast convergence in both free-field and reverberant environmentsThanks to Australian Research Councils Discovery Projects funding scheme (project no. DP140103412). The work of J. Zhang was sponsored by the China Scholarship Council with the Australian National University

Evaluation of spatial active noise cancellation performance using spherical harmonic analysis

This paper presents a novel metric to evaluate the performance of spatial active noise cancellation (ANC) systems. We show that the acoustic potential energy within a spherical region can be expressed by a weighed squared sum of spherical harmonic coefficients. The proposed metric allows convenient evaluation of spatial ANC performance using a spherical microphone array. In order to evaluate the effectiveness of this metric, we set up a experimental ANC system and conducted a series narrow band and wide band ANC experiments, the results show that the proposed potential energy method provides a reliable characterization of the performance of spatial ANC systems.This work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412)

Reproducing the Velocity Vectors in the Listening Region

This paper proposes a sound field reproduction algorithm based on matching the velocity vectors in a spherical listening region. Using the concept of sound field translation, the spherical harmonic coefficients of the velocity vectors in a spherical region are derived from the desired pressure distribution. The desired pressure distribution can either correspond to sources such as plane waves and point sources, or be obtained from measurements using a spherical microphone array. Unlike previous work in which the velocity vectors are only controlled on the boundary of the listening region or at discrete sweet spots, this work directly manipulates the velocity vectors in the whole listening region, which is expected to improve the perception of the desired sound field at low frequencies.Comment:

Active Noise Control Over Space: A Wave Domain Approach

Noise control and cancellation over a spatial region is a fundamental problem in acoustic signal processing. In this paper, we utilize wave-domain adaptive algorithms to iteratively calculate the secondary source driving signals and to cancel the primary noise field over the control region. We propose wave-domain active noise control algorithms based on two minimization problems: first, minimizing the wave-domain residual signal coefficients, and second, minimizing the acoustic potential energy over the region, and derive the update equations with respect to two variables, the loudspeaker weights and wave-domain secondary source coefficients. Simulation results demonstrate the effectiveness of the proposed algorithms, more specifically the convergence speed and the noise cancellation performance in terms of the noise reduction level and acoustic potential energy reduction level over the entire spatial region.DP14010341

Multichannel active noise control for spatially sparse noise fields

Multi-channel active noise control (ANC) is currently an attractive solution for the attenuation of low-frequency noise fields, in three-dimensional space. This paper develops a controller for the case when the noise source components are sparsely distributed in space. The anti-noise signals are designed as in conventional ANC to minimize the residual errors but with an additional term containing an ℓl norm regularization applied to the signal magnitude. This results in that only secondary sources close to the noise sources are required to be active for cancellation of sparse noise fields. Adaptive algorithms with low computational complexity and faster convergence speeds are propose

Power Response and Modal Decay Estimation of Room Reflections from Spherical Microphone Array Measurements using Eigenbeam Spatial Correlation Model

Modal decays and modal power distribution in acoustic environments are key factors in deciding the perceptual quality and performance accuracy of audio applications. This paper presents the application of the eigenbeam spatial correlation method in estimating the time-frequency-dependent directional reflection powers and modal decay times. The experimental results evaluate the application of the proposed technique for two rooms with distinct environments using their room impulse response (RIR) measurements recorded by a spherical microphone array. The paper discusses the classical concepts behind room mode distribution and the reasons behind their complex behavior in real environments. The time-frequency spectrum of room reflections, the dominant reflection locations, and the directional decay rates emulate a realistic response with respect to the theoretical expectations. The experimental observations prove that our model is a promising tool in characterizing early and late reflections, which will be beneficial in controlling the perceptual factors of room acoustics.Research Council (ARC) Discovery Project Grant No. DP180102375

Active Noise Control Over Spatial Regions

This thesis investigates active noise control over a large spatial region using efficient control systems. Active noise control (ANC) utilises secondary sound sources to cancel primary noise based on the principle of destructive interference, and has the advantage of high flexibility and easy adaptability. ANC over a large spatial region (spatial ANC), which requires multiple sensors and multiple secondary sources in the system, creates a large-sized quiet zone for multiple listeners in three-dimensional spaces. The existing multichannel approaches are not very efficient in spatial ANC, as the noise cancellation is optimized only around the error sensors. This thesis provides new adaptive solutions for spatial ANC in general noise fields and optimal methods for spatial ANC in sparse noise fields. In terms of adaptive solutions for spatial ANC in a general noise field, our approach is to utilize the wave-domain signal processing technique. Several outcomes resulting from this approach are (1) the design of the feedback wave-domain ANC system, and derivation of the filtered-x least mean square wave-domain approaches; (2) systematical formulation of the wave-domain ANC into different minimization problems and different updating variables, and derivation of four normalized wave-domain approaches. We show that, compared to the conventional multichannel approaches, the proposed wave-domain ANC approaches can achieve significant noise reduction over the entire spatial region with faster convergence speed. In terms of the optimal methods for spatial ANC in a sparse noise field, our approach is to incorporate the l1-norm constraint from compressive sensing into the spatial ANC. Several outcomes resulting from this approach are (1) derivation of the l1-constrained multichannel approaches; (2) derivation of the l1-constrained wave-domain approach. We show that, compared to the conventional multichannel approaches, the proposed l1-norm constrained approaches can reduce the number of active secondary sources with faster convergence speed. In addition, this thesis investigates the best possible spatial ANC performance for a given system, by analyzing the signal space spanned by the secondary sources within a given acoustic environment. The proposed subspace method can obtain best possible ANC performance and is demonstrated to be a feasible solution, especially when the secondary sources are not sufficient to cover all orthogonal spatial modes according to the spherical harmonic theory

Active noise control over a large region with multiple spherical microphone arrays in wave domain

Active Noise Control (ANC) over large regions of interest (ROI) traditionally requires numerous evenly distributed error microphones, which is often impractical and obstructive for human occupants. In this paper, we proposed a wave domain adaptive ANC algorithm using the joint information from multiple error spherical microphone arrays (SMAs) on the boundary of the ROI. By mapping the SMA recordings to the virtual sound field and introducing ℓ 1 norm on the virtual plane wave weights, the proposed method can achieve good noise reduction over the entire larger ROI, especially when the number of noise sources is finite and sparse. Our finding presents a significant advancement in spatial ANC, paving the way for more effective and unobtrusive solutions in a range of environments.</p

Time-domain wideband image source method for spherical microphone arrays

This paper presents the time-domain wideband spherical microphone array impulse response generator (TDWSMIR generator), which is a time-domain wideband image source method (ISM) for generating the room impulse responsescaptured by an open spherical microphone array. To incorporate loudspeaker directivity, the TDW-SMIR generator considers a source that emits a sequence of spherical wave fronts whose amplitudes are related to the loudspeaker directional impulse responses measured in the far-field. The TDW-SMIR generator uses geometric models to derive the time-domain signals recorded by the spherical microphone array. Comparisons are made with frequency-domain single band ISMs. Simulation results prove the results of the TDW-SMIR generator are similar to those of frequency-domain single band ISMs.Index Terms—Image source method, time-domain, room impulseresponse

Head-related intensity-based transfer function dataset

Recently, there has been growth in 3D audio applications in Helds such as virtual reality (VR) and augmented reality (AR). These fields require highly realistic sound to be delivered binaurally to human users. This has generally been achieved by obtaining scalar measurements of sound pressure in or near the human ear, to create a head-related transfer function (HRTF) dataset that characterises the interference of the human anatomy. This paper presents a novel method of improving HRTF datasets by obtaining a head-related intensity-based transfer function (HRIBTF) that characterises the sound at the entrance to the ear canal in terms of intensity, rather than pressure. The vector properties of sound intensity have been proven to inherently provide more useful information in the subjective perception of the sound, which is highly applicable to experiences such as VR and AR. For each ear, the intensity vectors are measured using three micro-electromechanical systems (MEMS) microphone pairs. An analysis of the HRIBTF dataset presented in this paper provides promising conclusions of the applications of sound intensity measurements, in terms of the relationship between the intensity vector and source locations.</p