LoBaCa: Super-Resolution LoRa Backscatter Localization for Low-Cost Tags

Long-range(LoRa) backscatter has shown great potential in many applications. However, the narrow bandwidth of LoRa and the unstable backscatter tag make localization challenging in practice. This paper presents LoBaCa, the first super-resolution LoRa backscatter localization system for low-cost tags. To increase the overall bandwidth, LoBaCa utilizes the frequency hopping technique and exploits the phase slope to synchronize multiple frequency bands. We further show that the unstable low-cost backscatter tag causes additional phase error in the weak backscatter signal and thus introduces significant localization error. We use the upper and lower sideband signals to improve the SNR and correct the phase error. Finally, LoBaCa adopts a super-resolution ESPRIT algorithm to solve the complex multipath effect, estimate the angle of arrival (AoA), and localize the backscatter tag. We prototype LoBaCa and conduct extensive experiments to evaluate LoBaCa in both indoor and outdoor scenarios. Our results show that the localization error of LoBaCa is 5.0 cm and 71 cm when the LoBaCa tag is 5m and 40m away, which is 4.3x and 1.7x better than the state-of-the-art.