Next Article in Journal
Utilization of Blended Waste Materials in Bricks
Next Article in Special Issue
On the Throughput Region of Wireless Random Access Protocols with Multi-Packet Reception Using Multi-Objective Optimization
Previous Article in Journal
The Design of New Technology Supporting Wellbeing, Independence and Social Participation, for Older Adults Domiciled in Residential Homes and/or Assisted Living Communities
Previous Article in Special Issue
Facial Expression Emotion Detection for Real-Time Embedded Systems
Open AccessArticle

Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method

School of Computing, Science & Engineering, University of Salford, Manchester M5 4WT, UK
*
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in Proceedings of the Seventh International Conference on Innovative Computing Technology (INTECH 2017), Luton, UK, 16–18 August 2017.
Technologies 2018, 6(1), 19; https://doi.org/10.3390/technologies6010019
Received: 15 December 2017 / Revised: 21 January 2018 / Accepted: 25 January 2018 / Published: 28 January 2018
Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications. View Full-Text
Keywords: microphone; wind noise; matrix decomposition and reconstruction; separability; weighted correlation; acoustic sensing; acoustic signals; environmental noise; monitoring microphone; wind noise; matrix decomposition and reconstruction; separability; weighted correlation; acoustic sensing; acoustic signals; environmental noise; monitoring
Show Figures

Figure 1

MDPI and ACS Style

Eldwaik, O.; F. Li, F. Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method. Technologies 2018, 6, 19.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop