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FRL: Fast and Reconfigurable Accelerator for Distributed Sound Source Localization.

Authors :
Ding, Xiaofeng
Wang, Chengliang
Liu, Heping
Zhang, Zhihai
Chen, Xianzhang
Tan, Yujuan
Liu, Duo
Ren, Ao
Source :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems. Nov2022, Vol. 41 Issue 11, p3922-3933. 12p.
Publication Year :
2022

Abstract

Sound source localization (SSL) has been widely applied in industrial and civil fields. And with the development of wearable devices and the Internet of Things (IoT), it is attractive to deploy the SSL system onto embedded and portable devices. However, the software-based SSL system causes excessive response delay and is often affected by environmental noise. To overcome this obstacle, we propose the fast and precise localization (FPL) algorithm for distributed SSL systems. It combines the benefits of both time difference of arrival (TDOA) and steered response power (SRP) methods, and thus it is able to localize sound sources fast and precisely. To further improve the localization speed, we propose the fast and reconfigurable localization (FRL) accelerator, which is an algorithm-hardware co-designed SSL accelerator. It adopts multiple distributed localization nodes for higher localization precision and higher robustness to environmental interference, and it can be configured into either the fast or precise mode to adapt to various environments. Experimental evaluations show that our proposed FPL algorithm can achieve high localization speed and precision, and the field-programmable gate array (FPGA)-based FRL accelerator outperforms the software implementation by $48.6\times $ and outperforms the prior FPGA-based SSL accelerators by $20\times \sim 838.2\times $. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02780070
Volume :
41
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems
Publication Type :
Academic Journal
Accession number :
160652729
Full Text :
https://doi.org/10.1109/TCAD.2022.3197537