Calibration-Free Indoor Positioning via Regional Channel Tracing

The traditional construction of radio maps demands extensive radio measurement data accompanied by precise location labels, thus necessitating considerable calibration. This article presents a calibration-free radio map construction method that relies solely on received signal strength (RSS) measurements, obviating the need for location labels. In this method, multiple mobile users traverse an indoor environment equipped with WiFi sensors, generating RSS measurement sequences. We estimate RSS collection locations along trajectories using prior knowledge of the layout, principles of signal propagation, and user mobility patterns. The challenge of estimating these locations based purely on RSS measurements is met by conforming to the intricate indoor layout and adhering to signal propagation models. Traditional calibration-free approaches often depend on inertial measurement units (IMUs) for real-time location estimation, but such reliance on IMUs is both cumbersome and encumbered by privacy concerns. We introduce a regional channel tracing (RCT) method, employing a signal subspace model and a subspace segmental clustering algorithm to classify RSS measurements and map them to regions. This method further includes a location tagging technique that, given the region labels, estimates RSS collection locations and regional path-loss models. Empirical results in an office setting demonstrate that our RCT-based radio map achieves performance comparable to advanced IMU-assisted methods.