Toward Reliable Non-Line-of-Sight Localization Using Multipath Reflections

Abstract

The past decade's research in RF indoor localization has led to technologies with decimeter-level accuracy under controlled experimental settings. However, existing solutions are not reliable in challenging environments with rich multipath and various occlusions. The errors can be 3-5 times compared to settings with clear LoS paths. In addition, when the direct path is completely blocked, such approaches would generate wrong location estimates. In this paper, we present NLoc, a reliable non-line-of-sight localization system that overcomes the above limitations. The key innovation of NLoc is to convert multipath reflections to virtual direct paths to enhance the localization performance. To this end, NLoc first extracts reliable multi-dimensional parameters by characterizing phase variations. Then, it models the relation between the target location and the geometric features of multipath reflections to obtain virtual direct paths. Finally, it incorporates novel algorithms to remove random ToF offsets due to lack of synchronization and compensate target orientation that determines the geometric features, for accurate location estimates. We implement NLoc on commercial off-the-shelf WiFi devices. Our experiments in multipath challenged environments with dozens of obstacles and occlusions demonstrate that NLoc outperforms state-of-the-art approaches by 44% at the median and 200% at 90% percentile.