Environment-assisted passive wifi tracking with self-localizing asynchronous sniffers

Navod Suraweera*, Shenghong Li, Mark Johnson, Iain B. Collings, Stephen V. Hanly, Wei Ni, Mark Hedley

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This article considers the problem of passive tracking of a noncooperating target indoors. We develop a novel system to localize a moving target using asynchronous self-localizing sniffer nodes, which passively listen to WiFi signals transmitted by the target. The proposed system uses only the time-difference-of-arrival between multipath components (multipath TDoA) at each receiver. This does not require phase synchronization. We develop two novel localization algorithms; one uses batch processing and the other is online. We also design a novel multipath association algorithm. A custom-designed hardware platform is developed to prototype the proposed system. The accuracy of the proposed system is verified experimentally. For signal-to-noise ratio of 10 dB, both proposed algorithms achieve target localization accuracies better than 40 cm with probability 0.95 without needing any knowledge of target or sniffer locations. If the location of one sniffer node is known, the accuracy improves to 15 cm.

Original languageEnglish
Pages (from-to)4798-4809
Number of pages12
JournalIEEE Systems Journal
Issue number4
Publication statusPublished - Dec 2020


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