mmPhone: Sound Recovery Using Millimeter-Wave Radios With Adaptive Fusion Enhanced Vibration Sensing

Although electret condenser microphone (ECM) has been widely used in sound acquisition, sound capture techniques still attract growing interests. To this end, the emerging techniques of laser microphone and visual microphone have been developed, but they suffer from numerous fundamental problems. In...

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Bibliographic Details
Published inIEEE transactions on microwave theory and techniques Vol. 70; no. 8; pp. 4045 - 4055
Main Authors Li, Songxu, Xiong, Yuyong, Zhou, Peng, Ren, Zesheng, Peng, Zhike
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Acoustic excitation
Acoustics
Frequency response
Internet of Things
Microphones
Microwave theory and techniques
Millimeter wave technology
Millimeter waves
millimeter-wave
multitarget fusion
Recovery
Sensors
Signal quality
Sound
sound acquisition
Vibration measurement
Vibration perception
Vibration response
Vibrations
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Summary:Although electret condenser microphone (ECM) has been widely used in sound acquisition, sound capture techniques still attract growing interests. To this end, the emerging techniques of laser microphone and visual microphone have been developed, but they suffer from numerous fundamental problems. In this article, a novel concept, called millimeter-wave microphone (mmPhone), is proposed, which can recover sound signals with high quality via millimeter-wave vibration perception. In mmPhone, with acoustic excitation, the vibration response of multiple light objects can be perceived, but different objects have different frequency response bandwidths. Thus, we propose a sound recovery method of multitarget adaptive fusion enhancement (MAFE), allowing reconstruction of the real full band sound signals. The overview of the mmPhone system and principle is first depicted. The detailed procedures including object selection, denoise, and adaptively fusion enhancement for implementing the MAFE method are then illustrated. Finally, experimental results with different scenarios are presented to validate the performance of mmPhone, showing that the proposed method is promising for sound acquisition in the Internet of Things (IoT).
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2022.3183575