Project Description:

Temperature is significant for many applications such as weather forecasting, precision agriculture, and building management. Indoor localization is crucial to enable context-aware applications, but existing solutions mostly require a user to carry a device, so as to actively sense location-discriminating signals. However, many applications do not prefer user involvement due to, e.g., the cumbersome of carrying a device. Therefore, solutions that track user locations passively can be desirable, yet lack of active user involvement has made passive indoor localization very challenging even for a single person. To this end, we propose Passive Acoustic loCalization of multiple walking pErsons (PACE) as a solution for small-scale indoor scenarios: it passively locates users by pinpointing the positions of their footsteps. In particular, PACE leverages both structure-borne and air-borne footstep impact sounds (FIS); it uses structure-borne FIS for range estimations exploiting their acoustic dispersion nature, and it employs air-borne FIS for Angle-of-Arrival (AoA) estimations and person identifications. To combat the low-SNR nature of FIS, PACE innovatively employs domain adversarial adaptation and spectral weighting to ranging/identification and AoA estimations, respectively. We implement a PACE prototype and extensively evaluate its performance in representative environments. The results demonstrate a promising sub-meter localization accuracy with a median error of 30cm.

Acknowledgement:

• This project was filed when I was a Post Doc. at Nanyang Technological University.

People:

• Dr. Chao Cai (Research Fellow, Computer Science & Engineering) - Nanyang Technological University
• Henglin Pu (UG student, Electronic Information & Engineering) - HUST
• Peng Wang (Master student, Electronic Information & Engineering) - HUST
• Dr. Jun Luo (Associate Professor, Computer Science & Engineering) - Nanyang Technological University

Related Publications:

• [1] C. Cai, H. Pu, P. Wang, and J. Luo. "We Hear Your PACE: Passive Acoustic Localization of Multiple Walking Persons", in ACM UbiComp, 2021.