Physical Microphone Research Articles

Virtual feedback control of interior road noise based on headrest loudspeakers

This paper analyzes the factors that affect the noise reduction performance of feedback control based on remote microphone technique (RMT) and how these factors can be exploited to improve the control performance. First, simulations were conducted to compare the noise reduction performance of employing feedback control directly at the virtual microphone (located at the ear position) and on the physical microphone (located on the headrest), as well as the RMT-based feedback control system. Then the impact of the delay of the virtual secondary path and the coherence between physical and virtual signals on the noise reduction performance of the RMT-based feedback control system was analyzed. It is found that the noise reduction performance can be improved by reducing the delay of the virtual secondary path or increasing the number of physical microphones. Finally, experiments of a dual-channel control system conducted inside an electric car cabin demonstrate that the feedback control strategy based on RMT achieves a binaural noise reduction of 3.4 dBA when employing 4 physical microphones to estimate sound pressure at the ear positions. This approach achieves similar performance but is more cost-effective than a feedforward system using multiple reference sensors.

A circular microphone array with virtual microphones based on acoustics-informed neural networks.

Acoustic beamforming aims to focus acoustic signals to a specific direction and suppress undesirable interferences from other directions. Despite its flexibility and steerability, beamforming with circular microphone arrays suffers from significant performance degradation at frequencies corresponding to zeros of the Bessel functions. To conquer this constraint, baffled or concentric circular microphone arrays have been studied; however, the former need a bulky baffle that interferes with the original sound field, whereas the latter require more microphones that increase the complexity and cost, both of which are undesirable in practical applications. To tackle this challenge, this paper proposes a circular microphone array equipped with virtual microphones, which resolves the performance degradation commonly associated with circular microphone arrays without resorting to physical modifications. The sound pressures at the virtual microphones are predicted from those measured by the physical microphones based on an acoustics-informed neural network, and then the sound pressures measured by the physical microphones and those predicted at the virtual microphones are integrated to design the beamformer. Experimental results demonstrate that the proposed approach not only eliminates the performance degradation but also suppresses spatial aliasing at high frequencies, thereby underscoring its promising potential.

A further study on coherence between virtual signal and physical signals in remote acoustic sensing (L)

A recent paper by Zhang, Wang, Duan, Tao, Zou, and Qiu [(2022). J. Acoust. Soc. Am. 152, 2840–2848] proposed that the average distance between physical microphones in remote acoustic sensing should be no larger than half the wavelength to ensure the coherence between the virtual signal and physical signals no less than 0.9 in complex sound fields. In this letter, the effects of the sound sources' distance on the coherence between the virtual signal and physical signals are further investigated, and it is found that the required average distance among physical microphones becomes smaller when sound sources are closer to the microphones.

An analysis of a feedback active noise control system using the remote microphone technique

This paper examines strategies in virtual sensing feedback active noise control systems and compares the noise reduction performance of three strategies: using physical microphones for direct feedback control, using virtual microphones for direct feedback control, and using physical microphones for indirect virtual feedback control. For a primary sound field with incident waves in a single direction, simulation results indicate that employing a physical microphone for indirect virtual feedback control consistently yields superior noise reduction performance than that using a physical microphone for direct feedback control. However, if the causal requirement between physical and virtual microphones is not satisfied, the increase in the equivalent secondary path delay deteriorates noise reduction performance while utilizing physical microphones for indirect virtual feedback control. For a primary sound field containing waves from multiple directions, the simulation results show that the noise reduction performance is affected by both the coherence and causality between the physical and virtual microphone signals.

Evaluation of virtual sensing with spherical array surrounding head for directional noise

Active noise control (ANC) is expected to be applicable to public transportation modalities such as airplanes and trains. In these application systems, passengers may need to avoid wearing devices such as earphones and ear microphones. However, in conventional ANC systems, it is necessary to locate a physical microphone at the ear positions as an error sensor. To overcome this problem, virtual sensing techniques have been studied for estimating sound pressures at ear positions using remote microphones. In this study, we investigated the performance of a virtual sensing method for interpolating the sound pressures at ear positions using a spherical microphone array surrounding the head, based on a spherical harmonic expansion. The experiments were conducted using a rigid sphere instead of a head and dodecahedral spherical microphone array surrounding the sphere. The estimation errors were evaluated for various noise directions at low frequencies (100, 300, 500, and 700 Hz). The experimental results showed that the estimation errors were less than -20 dB for almost all conditions below 500 Hz. By comparison with other virtual sensing methods using a few microphones in the vicinity of the ear positions, we confirmed that our proposed method was effective for any noise direction.

Active control of impulsive scattered sound based on virtual sensing

Active control method is an important way to reduce the scattered radiation of 3D objects and render them acoustically invisible. Traditional active control requires the error sensor to be sufficiently close to the target area because the zone of quiet (ZoQ) is generated around the sensor; thus, the scattered noise cannot be eliminated at the remote position in situations wherein the microphone can only be placed near the scatterer. To solve this dilemma, this study proposed two methods of predicting and controlling the scattered sound, combined with adaptations of two commonly used virtual sensing (VS) methods: the auxiliary-filter-based virtual-sensing (AF-VS) and the remote microphone technique (RMT). Both methods are based on the correlation between signals to predict the scattered noise; therefore, ZoQ can be transferred to the non-near-field target position with fewer physical microphones. Further, the causal constraints need not be satisfied in the former method, which uses pre-trained auxiliary filters to implicitly estimate and control the scattered pressure at the target point. Whereas, the latter explicitly estimates the scattered component instead of the total sound pressure with the pre-modeled observation matrix, thereby avoiding the causality limitation of the RMT and reducing one estimation process. Experiments were conducted to suppress impulsive scattered sound using a dual-channel feedforward adaptive ANC system, and the attenuation performances of the two proposed methods were compared with those of the direct control of the desired noise with the optimal Wiener solution and the method without combining the VS. The results demonstrated the feasibility and effectiveness of the two active control methods for scattered sound using virtual sensors. Moreover, in the impulsive scattered sound control with a 300 Hz-1000 Hz carrier, the average noise reduction (NR) at the observation points reached approximately 18 dB, and a more stable and excellent performance was obtained using the latter method based on RMT. Therefore, this research provides a solution for the case of limited error sensor placement in scattered sound active control systems; and in addition, can be used to guide the choice of VS methods in scattered sound control applications.

Time domain virtual sensing method based on a rigid-sphere transfer function for active noise control headrests

Active noise control (ANC) is expected to be used in public transportation such as airplanes and trains. While using these applications, passengers prefer not to wear earphones or ear microphones, if possible, to reduce ear strain. However, conventional ANC systems require a physical microphone, which acts as an error sensor, at the ear position. To address this issue, a virtual sensing technique has been studied that uses a microphone mounted on a seat’s headrest to estimate the sound pressure at the ear position. In this study, we propose a virtual sensing technique that interpolates the sound pressure at the ear position using a spherical microphone array surrounding the head. This method improves robustness to variations in noise arrival direction using spherical harmonic coefficients without directional dependence. In general, the interpolation formula using spherical harmonic expansion is obtained in the frequency domain. By contrast, the proposed method designs the interpolation process as an IIR filter by considering the minimum phase and estimates the noise signal directly in the time domain, achieving the real-time processing required for ANC. The effectiveness of the proposed method in reducing noise was investigated for various noise arrival directions.

A Virtual Sensing Active Noise Control System Based on a Functional Link Neural Network for an Aircraft Seat Headrest

PurposeThe goal of this work is to propose a local Active Noise Control system for an aircraft seat’s headrest. This system should be able to extend the quiet zone beyond the physical microphones that can be placed behind the passenger’s head due to space constraints. Furthermore, the control algorithm should perform efficiently when non-linear phenomena exist during the sound propagation.MethodsA functional link neural network and a computationally efficient Multiple Input Multiple Output approach are used for the system’s implementation. The quiet zone is extended by linearly estimating the acoustic pressure in front of the headrest surface. The main novelty of this paper is the combination of these methods in an attempt to improve acoustic pressure attenuation performance, while keeping computational complexity low.ResultsThe proposed control algorithm has been evaluated through numerical simulations, including Finite Element Method and experimental tests at an aircraft cabin mock-up. The results show that for a real-world acoustic disturbance, a 10 dB reduction in sound pressure level was achieved 10 cm away from the headrest surface. In addition, the attenuation of some harmonics can reach 20 dB and in most cases is bigger than the linear FxLMS algorithm.ConclusionsTo summarize, it has been demonstrated that a multichannel functional link neural network using a simple virtual sensing technique can efficiently attenuate synthesized and real world acoustic disturbances captured in a tilt-rotor aircraft’s cabin. Finally, it can create an adequate quiet zone for gentle head movement while maintaining its stability.

A study on coherence between virtual signal and physical signals in remote acoustic sensing.

Remote acoustic sensing can be used to estimate the error signals in human ears without placing any physical microphones there. In this paper, the coherence between the signals picked up by physical microphones over a sphere surface and the signal obtained at the sphere center is investigated. Based on the multiple channel coherence formulas in the time domain and frequency domain, the relationship between the coherence and the placement of physical microphones is analyzed by numerical simulations first, then the experimental results obtained in a reverberation chamber and a car cabin are presented to verify the simulation results. Finally, a placement of physical microphones for active control of road noise in car cabins is discussed. Both the numerical and experimental results show that an upper limit frequency exists for accurate sound pressure estimation at the center of a sphere with the sound pressure on the sphere surface. For a sufficiently complex sound field such as that in a reverberation room or in a car, half the wavelength of the upper limit frequency is about the average distance among the physical microphones.

Robust feedback controller combined with the remote microphone method for broadband active noise control in headrest

This paper proposes a design method combining the remote microphone method (RMM) with a robust fixed feedback controller to achieve active noise control in a headrest with physical microphones situated far from the target zone. Design objectives of the controller are based on a mixed H2/H∞ method and the proposed closed-loop gain margin constraint, which consider noise reduction performance, waterbed lift, and robustness against plant perturbations due to slight rotations of the head. Meanwhile, the design objectives are constructed with RMM to create a local zone of quiet far away from the physical monitoring microphone. Particle swarm optimization algorithm is employed for this multi-objective design problem to efficiently generate the feedback controller consisting of cascade second-order sections infinite-impulse-response (IIR) filters. Simulations and real-time experiments were conducted to demonstrate the superior noise reduction performance and robust stability of the designed IIR feedback controller in attenuating broadband disturbances measured in a vehicle.

Predicting traffic noise using land-use regression\u2014a scalable approach

BackgroundIn modern societies, noise is ubiquitous. It is an annoyance and can have a negative impact on human health as well as on the environment. Despite increasing evidence of its negative impacts, spatial knowledge about noise distribution remains limited. Up to now, noise mapping is frequently inhibited by the necessary resources and therefore limited to selected areas.ObjectiveBased on the assumption, that prevalent noise is determined by the arrangement of sources and the surrounding environment in which the sound propagates, we build a geostatistical model representing these parameters. Aiming for a large-scale noise mapping approach, we utilize publicly available data, context-aware feature engineering and a linear land-use regression (LUR) model.MethodsCompliant to the European Noise Directive 2002/49/EG, we work at a high spatial granularity of 10 × 10-m resolution. As reference, we use the day–evening–night noise level indicator Lden. Therewith, we carry out 2000 virtual field campaigns simulating different sampling schemes and introduce spatial cross-validation concepts to test the transferability to new areas.ResultsThe experimental results suggest the necessity for more than 500 samples stratified over the different noise levels to produce a representative model. Eventually, using 21 selected variables, our model was able to explain large proportions of the yearly averaged road noise (Lden) variability (R2 = 0.702) with a mean absolute error of 4.24 dB(A), 3.84 dB(A) for build-up areas, respectively. In applying this best performing model for an area-wide prediction, we spatially close the blank spots in existing noise maps with continuous noise levels for the entire range from 24 to 106 dB(A).SignificanceThis data is new, particular for small communities that have not been mapped sufficiently in Europe so far. In conjunction, our findings also supplement conventionally sampled studies using physical microphones and spatially blocked cross-validations.

Implementation of robust virtual sensing algorithm in active noise control to improve silence zone

Active noise control (ANC) is a successful technique to reduce unwanted noise based on the superposition principle. In a conventional ANC system, the extent of unwanted noise can be attenuated at the error microphone location, thus making a silent zone at the desired location. However, in certain situations, it is impossible to place the error microphone at the desired location. In that case, the error microphone cannot assure adequate noise suppression at the desired location. To overcome that, the virtual sensing technique (VST) has been implemented in ANC to shift the zone of silence to the desired position. This paper proposes a supplemental filter in VST to avoid interference issues between secondary and virtual paths..In the virtual ANC, the supplemental filter H provides the required information to measure optimal noise control filter and also increases noise reduction in the ANC system at the virtual location. A Real-Time Simulink model is designed for the proposed virtual sensing ANC and evaluate its efficiency. The computer simulation findings showed that the ANC system performance with the proposed virtual sensing method had good noise reduction at the virtual location compared to the physical location. The proposed supplemental filter preserves reasonable noise reduction efficiency in the ANC system if the physical microphone is positioned far from the location of the silence zone.

Wave Digital Implementation of Robust First-Order Differential Microphone Arrays

In this letter, a novel time-domain implementation of robust first-order differential microphone arrays (DMAs), based on wave digital filters, is presented. The proposed beamforming method is extremely efficient, as it requires at most two multipliers and one delay for each filter, where the necessary number of filters equals the number of physical microphones of the array, and it avoids the use of fractional delays. The update of the coefficients of the filters, required for reshaping the beampattern, has a significantly lower computational cost with respect to the time-domain methods presented in the literature. This makes the proposed method suitable for real-time DMA applications with time-varying beampatterns.

Efficient Continuous Beam Steering for Planar Arrays of Differential Microphones

Performing continuous beam steering, from planar arrays of high-order differential microphones, is not trivial. The main problem is that shape-preserving beams can be steered only in a finite set of privileged directions, which depend on the position and the number of physical microphones. In this letter, we propose a simple and computationally inexpensive method for alleviating this problem using planar microphone arrays. Given two identical reference beams pointing in two different directions, we show how to build a beam of nearly constant shape, which can be continuously steered between such two directions. The proposed method, unlike the diffused steering approaches based on linear combinations of eigenbeams (spherical harmonics), is applicable to planar arrays also if we deal with beams characterized by high-order polar patterns. Using the coefficients of the Fourier series of the polar patterns, we also show how to find a tradeoff between shape invariance of the steered beam, and maximum angular displacement between the two reference beams. We show the effectiveness of the proposed method through the analysis of models based on first-, second-, and third-order differential microphones.

Considerations regarding the equalization for spatial playback from spherical microphone array recordings

The encoding of spatial sound fields captured by spherical microphone arrays into Eigenbeams (HOA signals) provides a compact representation of the sound field that facilitates spatially realistic audio playback in Higher-Order Ambisonics (HOA) applications. For spatial audio reproduction, a typical Ambisonics decoder generates the loudspeaker signals from the HOA signals by applying only simple scalar weights. However, since the HOA signals derived from physical microphone arrays are frequency dependent, such a frequency independent scalar weighting scheme will not result in the desired loudspeaker sound field reproduction. An analysis of this frequency dependency and some equalization schemes to mitigate detrimental effects resulting from frequency independent loudspeaker decoding will be discussed.

FIR-based symmetrical acoustic beamformer with a constant beamwidth

Traditional beamformer design methods suffer from a frequency varying beamwidth, making them less effective for wideband applications. Existing approaches that try to solve this problem demonstrate degraded beamformer performance in terms of sidelobe level attenuation and sensitivity, making them less robust to interference and array attribute perturbations. Another common issue for existing approaches is high computational complexity, resulting in the ability to implement these approaches only for small microphone arrays, directly affecting the beamformer spatial resolution. In this paper, we introduce a new approach for designing a constant beamwidth beamformer. The proposed approach utilizes custom-tailored finite impulse response (FIR) filters for each microphone channel, manipulating the beampattern to achieve a desired beamwidth. The manipulated beampattern has approximately a constant beamwidth over a wide frequency band. Additionally, a post-summing output normalization filter is used to ensure a frequency invariant gain of the beampattern. By exploiting the physical microphone array configuration and attributes, we shape accordingly the frequency response of the FIR filters and control the beamformer beamwidth. The proposed approach demonstrates improved array response results in various scenarios, compared to available methods in the field, especially in terms of sensitivity to parameters mismatch, noise robustness and sidelobe attenuation.

Multi-Domain Processing for Micropower Sensors

Multi-Domain Processing for Micropower Sensors

Nonlinear active noise control for headrest using virtual microphone control

In this paper, a feed-forward nonlinear active noise control algorithm is developed using the Filtered-S LMS (FSLMS) algorithm and virtual microphone control for an active headrest application. Virtual microphone control is implemented to attenuate noise at the ears of the headrest occupant using the physical microphones placed at remote locations. The proposed nonlinear virtual microphone control algorithm is verified in real-time in a headrest. Different nonlinear noise processes are studied and it is shown that in all cases, the FSLMS algorithm outperforms the FXLMS algorithm in controlling nonlinear primary noise at a virtual location.

A nonlinear active noise control algorithm for virtual microphones controlling chaotic noise

In active noise control (ANC) systems, virtual microphones provide a means of projecting the zone of quiet away from the physical microphone to a remote location. To date, linear ANC algorithms, such as the filtered-x least mean square (FXLMS) algorithm, have been used with virtual sensing techniques. In this paper, a nonlinear ANC algorithm is developed for a virtual microphone by integrating the remote microphone technique with the filtered-s least mean square (FSLMS) algorithm. The proposed algorithm is evaluated experimentally in the cancellation of chaotic noise in a one-dimensional duct. The secondary paths evaluated experimentally exhibit non-minimum phase response and hence poor performance is obtained with the conventional FXLMS algorithm compared to the proposed FSLMS based algorithm. This is because the latter is capable of predicting the chaotic signal found in many physical processes responsible for noise. In addition, the proposed algorithm is shown to outperform the FXLMS based remote microphone technique under the causality constraint (when the propagation delay of the secondary path is greater than the primary path). A number of experimental results are presented in this paper to compare the performance of the FSLMS algorithm based virtual ANC algorithm with the FXLMS based virtual ANC algorithm.

MULTI-POD CONFERENCE SYSTEMS

This disclosure describes a multi-pod conferencing system for local conference participants to communicate with remote conference participants that includes a plurality of pods for local conference participants where an individual pod connects to one or more plurality of pods through a data communication means. The individual pods further include the following: pod processor means; an input device and a display; a loudspeaker that couples to a digital to analog converter; 3 physical bi-polar microphones positioned at 120 degree intervals in the horizontal resting plane of the pod, each individual physical microphone connects to a pair of audio ports with each audio port being equal distance from the loudspeaker, the physical microphones couple to analog to digital converting mean and pod processor means; 3 virtual microphones; pod echo cancellation means; and microphone gating means. The disclosed system further includes a base unit that couples to the plurality of pods through the data communication means. The base unit further includes base controller means, where the base controller means couples to the converting means. The system further includes the command input and display information from the individual pod that distributed to the plurality of pods such that the plurality of pods can be operated in tandem and where the computed values of the pod gating means is distributed to other pods to gate the pods on and or off.