Project Description:

Recently, acoustic-based indoor localization has attracted much attention due to its affordable infrastructure costs and high localization accuracy. However, previous work is infeasible in mobile target tracking for its long latency in obtaining sufficient beacon messages. In addition, the performance can further deteriorate due to device diversity, varying channel gains, and background noises. To this end, we propose an asynchronous acoustic localization and tracking system (AALTS), which utilizes distributed acoustic anchor nodes to locate passive off-the-shelf mobile devices. In AALTS, we propose an orthogonal chirp spread spectrum (OCSS) modulation technique, which doubles the data rate and thus mitigates the latency. We design a more robust method to capture acoustic signals which embody timestamps for localization, accounting for device diversity, varying channel gains, and the multipath effect. Finally, we incorporate an acoustic Doppler speed estimation module with a path-based particle filter framework to accurately track the moving targets. We have evaluated AALTS in an indoor testbed of size 8×12 m 2 with commodity mobile phones and customized acoustic anchors. Our evaluation results demonstrate remarkable performance: AALTS achieves 90-percentile tracking errors of 0.49 m for mobile targets and a median of 0.12 m for stationary ones with only four anchor nodes.

Acknowledgement:

• This project is accomplished when I was a Ph.D student at Huazhong University of Science and Technology. For more information please visit our git repository

  People:

  • Dr. Chao Cai (Electronic Information & Engineering) - HUST
  • Ruinan Jin (Master student, Electronic Information & Engineering) - HUST
  • Yan Yan (Master student, Electronic Information & Engineering) - HUST
  • Pei Rao (Master student, Electronic Information & Engineering) - HUST
  • Peng Wang (Master student, Electronic Information & Engineering) - HUST
  • Liyuan Ye (Master student, Electronic Information & Engineering) - HUST
  • Jun Li (Master student, Software Computing & Engineering) - Mcmaster University
  • Dr. Rong Zheng (Professor, Software Computing & Engineering) - Mcmaster University

  Related Publications:

• [1] C. Cai, R. Zheng, J. Li, L. Zhu, H. Pu and M. Hu, "Asynchronous Acoustic Localization and Tracking for Mobile Targets", in IEEE Internet of Things Journal, vol. 7, no. 2, pp. 830-845, Feb. 2020, doi: 10.1109/JIOT.2019.2945054.
• [2] C. Cai, M. Hu, D. Cao, X. Ma, Q. Li and J. Liu, "Self-Deployable Indoor Localization With Acoustic-Enabled IoT Devices Exploiting Participatory Sensing", in IEEE Internet of Things Journal, vol. 6, no. 3, pp. 5297-5311, June 2019, doi: 10.1109/JIOT.2019.2900524..