Combating Chirp Interference for Multi-target LoRa Localization

The long-range and low-power properties of LoRa facilitate its rapid deployment in many location-based services. However, existing LoRa-based localization techniques assume that the received signal is solely from a single node, without any concurrent transmissions from other LoRa nodes. This is because concurrent transmissions lead to mutual interference that inevitably distorts the estimated channel state information (CSI), resulting in significant localization errors. Although interference caused by concurrent transmissions has been studied and addressed in LoRa communication, none of these methods are effective for LoRa localization. This is because localization relies on distinct features and encounters different challenges compared to LoRa communication. To address this fundamental limitation, we propose CLoc, the first LoRa-based multi-target localization method, which is capable of localizing multiple LoRa nodes simultaneously under concurrent transmissions. Through comprehensive analysis, CLoc classifies the interference into two categories based on the chirp slope, i.e., inter-slope interference (different slopes) and co-slope interference (same slope), and identifies their fundamental impacts on CSI errors. CLoc designs dedicated methods that smartly leverage LoRa chirp characteristics to address CSI distortion caused by inter-slope interference, and tackle CSI ambiguity and errors caused by co-slope interference, thereby enabling accurate CSI estimation. We implement the prototype of CLoc with USRP B210 and commodity LoRa nodes. Evaluations under different settings demonstrate that CLoc achieves median localization errors of 3.3 m in a 293,250 m2 outdoor area and 3.5 m in a 6,750 m2 indoor area, reducing the localization errors by up to 90.6% compared with the state-of-the-art single LoRa node localization method.