Automotive acoustic channel equalization method using convex optimization in modal domain

Qian Y, Qu T, Tang W, Chen S, Shen W, Guo X, Chai H. Automotive acoustic channel equalization method using convex optimization in modal domain. In: Convention Paper. Audio Engineering Society; 2024. Paper 10696. Available from: https://aes.org/publications/elibrary-page/?id=22509

@inproceedings{Qian2024_22509,
  author = {Qian, Yufan and Qu, Tianshu and Tang, Wei and Chen, Shiyu and Shen, Weihua and Guo, Xiang and Chai, Hua},
  title = {{Automotive acoustic channel equalization method using convex optimization in modal domain}},
  note = {Paper 10696},
  year = {2024},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22509}
}

TY  - CPAPER
TI  - Automotive acoustic channel equalization method using convex optimization in modal domain
AU  - Qian, Yufan
AU  - Qu, Tianshu
AU  - Tang, Wei
AU  - Chen, Shiyu
AU  - Shen, Weihua
AU  - Guo, Xiang
AU  - Chai, Hua
M1  - Paper 10696
PY  - 2024
DA  - 2024/06/06
UR  - https://aes.org/publications/elibrary-page/?id=22509
PB  - Audio Engineering Society
LA  - en
AB  - Automotive audio systems often face sub-optimal sound quality due to the intricate acoustic properties of car cabins. Acoustic channel equalization methods are generally employed to improve sound reproduction quality in such environments. In this paper, we propose an acoustic channel equalization method using convex optimization in the modal domain. The modal domain representation is used to model the whole sound field to be equalized. Besides integrating it into the convex formulation of the acoustic channel reshaping problem, to further control the prering artifacts, the temporal window function modified according to the backward masking effect of the human auditory system is used during equalizer design. Objective and subjective experiments in a real automotive cabin proved that the proposed method enhances spatial robustness and avoids the audible prering artifacts.
ER  -