HiQuadLoc: A RSS Fingerprinting Based Indoor Localization System for Quadrotors

Indoor localization for quadrotors has attracted much attention recently. While efforts have been made to perform location estimation of quadrotors leveraging dedicated indoor infrastructures, the low-cost and commonly used RSS fingerprinting based approach utilizing existing Wi-Fi APs has yet to be applied. The challenge is that the high-speed flight reduces the RSS measuring opportunities for fingerprints comparison; moreover, the 3D space fingerprints collection incurs more overhead than in the traditional 2D case. In this paper, we present HiQuadLoc, a RSS fingerprinting based indoor localization system for quadrotors. We propose a series of mechanisms including path estimation, path fitting, and location prediction to deal with the negative influence incurred by the high-speed flight; moreover, we develop a 4D RSS interpolation algorithm to reduce the site survey overhead, where 3D is for the indoor physical space and 1D is for the RSS sample space. Experimental results demonstrate that HiQuadLoc reduces the average location error by more than 50 percent compared with simply applying the RSS fingerprinting based approach for 2D localization, and the overhead of RSS training data collection is reduced by more than 80 percent.