CrossTrack: Device-Free Cross-Link Tracking With Commodity Wi-Fi

Abstract

Device-free Wi-Fi tracking has become essential for ubiquitous wireless sensing. However, current device-free Wi-Fi tracking systems suffer from two limitations: First, Abnormal signals interfere with tracking performance when the user walks across the direct link of the transceivers; Second, The tracking error based on the velocity integral accumulates over time. This paper proposes CrossTrack, the first device-free cross-link tracking system with commodity Wi-Fi. Our inspiration is to regard the cross-link behavior as an opportunity to correct the trajectory instead of disturbing noise like previous work. Our approach involves three main steps. First, we devise a metric that is capable of detecting cross-link behavior. Second, we propose a new theoretical model that identifies the cross-link position as a landmark. Third, we develop a path revision technique that utilizes this landmark to optimize the trajectory. The technique innovation of the paper is to reveal the theoretical approach to transform cross-link interference into optimization in device-free tracking for the first time. We implement CrossTrack based on commercial Wi-Fi devices and conduct comprehensive experiments. Our results show that CrossTrack can reduce tracking errors by 48.75%, and the median tracking error is 0.41m.