Time-Domain-Agnostic Contactless Fingerprinting Localization via LoRa Frequency-Hopping

LoRa technology provides new potentials for long-range localization. Unlike previous works which attach a device to a person for active localization, this paper presents a cross-temporal domain device-free fingerprinting localization system based on LoRa technology. The rationale of this work is that the person standing on different positions can induce different multipaths, and the challenge is to extract locations from receiving signals over time. Through careful mathematical analysis, we observe the key factors that can characterize the location features and then propose a novel fingerprinting construction method leveraging frequency-hopping to expand the locations' resolution. Considering the temporal instability of the signal, we establish a domain adversarial-based localization model for position estimation. Extensive experiments have been conducted to evaluate our design, and results indicate that the fingerprinting construction approach can well express the location diversity even across different time and the designed model achieves decimeter-level localization in long-range indoor and multipath environments.