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Performance evaluation of an active headrest system using a filtered-x least mean square/fourth algorithm with

M L N S Karthik¹, Somanath Pradhan², Nithin V George¹

¹Department of Electrical Engineering, Indian Institute of Technology Gandhinagar, Gujarat 382355, India.

The Journal of the Acoustical Society of America

|November 7, 2023

Summary

This summary is machine-generated.

This study introduces an improved virtual sensing method for active headrests, enhancing noise control in the ear canal. The new approach effectively reduces both periodic and broadband noise for better audio experiences.

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Area of Science:

Acoustics
Signal Processing
Active Noise Control

Background:

Virtual sensing in active headrest systems often shifts the zone of quiet from the microphone to the ear canal.
Existing methods face challenges in precisely controlling noise within the ear canal.

Purpose of the Study:

To develop an auxiliary filter-based virtual sensing scheme for active headrests.
To integrate this scheme with the filtered-x least mean square/fourth algorithm.
To evaluate the noise control performance and the impact of causality constraints.

Main Methods:

Development of an auxiliary filter-based virtual sensing scheme.
Integration with the filtered-x least mean square/fourth algorithm.
Experimental validation using periodic and band-limited white noise.

Main Results:

The proposed method demonstrated improved noise control performance for both periodic and broadband noise.
The virtual sensing scheme successfully transferred the zone of quiet to the ear canal.
The effect of causality constraints on performance was analyzed.

Conclusions:

The auxiliary filter-based virtual sensing scheme offers enhanced noise control in active headrest systems.
The integration with filtered-x LMS/L algorithms is effective for real-world applications.
Further research can explore optimizations considering causality constraints.