LTrack: A LoRa-Based Indoor Tracking System for Mobile Robots

The robot’s mobility and intelligence have expanded its application in recent years. Specifically, indoor tracking is a fundamental function of public service robots in nursing homes, hospitals, and warehouses. Existing vision-based tracking requires visual information, which may be unavailable and introduce privacy issues in practical deployment. To this end, in this paper, we propose
$\mathsf {LTrack}$
, a long-range tracking system based on LoRa, an emerging low-power wide-area networking (LPWAN) technology, with a single transceiver pair. Note that commodity LoRa devices cannot estimate the angle of arrival (AoA) of signals due to hardware limitations. We design a virtual circular antenna array in the mobile rotating anchor via a lightweight hardware modification to multiplex the only RF channel in the low-cost LoRa device. The difference of time of flight (TDoF) measured in the circular antenna array is fused with the rotating orientation to estimate the target AoA. We also redesign and optimize the primitive LoRa ranging engine based on systematic analysis. Further, we present a real-time mobile target tracking algorithm based on the Doppler frequency shift to combat the uncertainty introduced by the target movement. We have developed the prototype of
$\mathsf {LTrack}$
, which consists of a mobile rotating anchor, a LoRa tag, and a commercial robot. The system is evaluated in both LOS and NOLS indoor scenarios. Experiments show that
$\mathsf {LTrack}$
supports robust tracking with a median error of 0.12 m and 0.45 m in a
$\text{137}\,\text{m}^2$
lab space and a
$\text{600}\,\text{m}^2$
corridor, respectively.