MDPI - Publisher of Open Access Journals

22 pages, 11982 KB

Open AccessReview

Sound Field Reproduction Research and Its Applications in Cabin Noise Reproduction of Vehicles: A Review

by Peilin Zheng, Xu Zheng and Yi Qiu

Machines 2026, 14(5), 493; https://doi.org/10.3390/machines14050493 - 28 Apr 2026

Viewed by 530

Sound field reproduction (SFR) is vital for noise simulation and acoustic comfort optimization in vehicle cabins. This paper reviews three core SFR techniques: Wave Field Synthesis (WFS), Higher-Order Ambisonics (HOA), and Pressure Matching (PM). Their theoretical fundamentals, engineering optimizations, and adaptability to narrow enclosed cabins are analyzed. We compare the three methods in terms of reproduction accuracy, system complexity, and cost. Key challenges in vehicular applications are summarized, including strong reverberation, multi-source coupling, and the mismatch between physical reproduction and subjective perception. Future directions are proposed, such as physics-data hybrid optimization, low-cost lightweight design, and personalized acoustic comfort. This review offers a practical reference for the engineering application of SFR in vehicle cabin acoustic optimization. Full article

(This article belongs to the Special Issue Advanced NVH, Human Factors, and Intelligent Control in New Energy Vehicles)

► Show Figures

Figure 1

15 pages, 4269 KB

Open AccessArticle

Assessing Ambisonics Sound Source Localization by Means of Virtual Reality and Gamification Tools

by Esaú Medina, Rhoddy Viveros-Muñoz and Felipe Otondo

Appl. Sci. 2024, 14(17), 7986; https://doi.org/10.3390/app14177986 - 6 Sep 2024

Cited by 2 | Viewed by 4047

Abstract

Sound localization is a key area of interest in auditory research, especially in complex acoustic environments. This study evaluates the impact of incorporating higher-order Ambisonics (HOA) with virtual reality (VR) and gamification tools on sound source localization. The research addresses the current limitations in VR audio systems, particularly the lack of native support for HOA in game engines like Unreal Engine (UE). A novel framework was developed, combining UE for VR graphics rendering and Max for HOA audio processing. Participants performed sound source localization tasks in two VR environments using a head-mounted display (HMD). The assessment included both horizontal and vertical plane localization. Gamification elements were introduced to improve engagement and task comprehension. Results showed significant improvements in horizontal localization accuracy, although challenges remained in back localization. The findings underscore the potential of VR and gamification to enhance auditory tests, reducing test duration and participant fatigue. This research contributes to the development of immersive and interactive audio experiences, highlighting the broader applications of VR beyond entertainment. Full article

(This article belongs to the Special Issue Enhancing User Experience in Virtual Reality Environments: Innovative Interaction Design Strategies)

► Show Figures

Figure 1

16 pages, 1632 KB

Open AccessArticle

Upmix B-Format Ambisonic Room Impulse Responses Using a Generative Model

by Jiawei Xia and Wen Zhang

Appl. Sci. 2023, 13(21), 11810; https://doi.org/10.3390/app132111810 - 29 Oct 2023

Cited by 4 | Viewed by 3492

Abstract

Ambisonic room impulse responses (ARIRs) are recorded to capture the spatial acoustic characteristics of specific rooms, with widespread applications in virtual and augmented reality. While the first-order Ambisonics (FOA) microphone array is commonly employed for three-dimensional (3D) room acoustics recording due to its easy accessibility, higher spatial resolution necessitates using higher-order Ambisonics (HOA) in applications such as binaural rendering and sound field reconstruction. This paper introduces a novel approach, leveraging generative models to upmix ARIRs. The evaluation results validate the model’s effectiveness at upmixing first-order ARIRs to higher-order representations, surpassing the aliasing frequency limitations. Furthermore, the spectral errors observed in the Binaural Room Transfer Functions (BRTFs) indicate the potential benefits of using upmixed ARIRs for binaural rendering, significantly improving rendering accuracy. Full article

(This article belongs to the Section Acoustics and Vibrations)

► Show Figures

Figure 1

14 pages, 2426 KB

Open AccessArticle

A Measure Based on Beamforming Power for Evaluation of Sound Field Reproduction Performance

by Ji-Ho Chang and Cheol-Ho Jeong

Appl. Sci. 2017, 7(3), 249; https://doi.org/10.3390/app7030249 - 3 Mar 2017

Cited by 5 | Viewed by 5139

Abstract

This paper proposes a measure to evaluate sound field reproduction systems with an array of loudspeakers. The spatially-averaged squared error of the sound pressure between the desired and the reproduced field, namely the spatial error, has been widely used, which has considerable problems in two conditions. First, in non-anechoic conditions, room reflections substantially deteriorate the spatial error, although these room reflections affect human localization to a lesser degree. Second, for 2.5-dimensional reproduction of spherical waves, the spatial error increases consistently due to the difference in the amplitude decay rate, whereas the degradation of human localization performance is limited. The measure proposed in this study is based on the beamforming powers of the desired and the reproduced fields. Simulation and experimental results show that the proposed measure is less sensitive to room reflections and the amplitude decay than the spatial error, which is likely to agree better with the human perception of source localization. Full article

(This article belongs to the Special Issue Spatial Audio)

► Show Figures

Figure 1

Search Results (4)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI

Saved Queries

Search Filter Reset All

Years

Feature Papers

Subjects

Journals

Article Types

Countries / Regions

Search Results (4)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI