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Foot-mounted inertial positioning (FMIP) can face problems of inertial driftsand unknown initial states in real applications, which renders the estimatedtrajectories inaccurate and not obtained in a well defined coordinate systemfor matching trajectories of different users. In this paper, an approachadopting received signal strength (RSS) measurements for Wifi access points(APs) are proposed to align and calibrate the trajectories estimated from footmounted inertial measurement units (IMUs). A crowd-sourced radio map (RM) canbe built subsequently and can be used for fingerprinting based Wifi indoorpositioning (FWIP). The foundation of the proposed approach is graph basedsimultaneously localization and mapping (SLAM). The nodes in the graph denoteusers poses and the edges denote the pairwise constrains between the nodes. Theconstrains are derived from: (1) inertial estimated trajectories; (2) vicinityin the RSS space. With these constrains, an error functions is defined. Byminimizing the error function, the graph is optimized and thealigned/calibrated trajectories along with the RM are acquired. Theexperimental results have corroborated the effectiveness of the approach fortrajectory alignment, calibration as well as RM construction.

WiFi based trajectory alignment, calibration and easy site survey using smart phones and foot-mounted IMUs