3D Reconstruction of Indoor Geometry using Electromagnetic Multipath Fingerprints

Knowing the location and the dimensions of walls and objects in an indoor environment is extremely important for both human and robot navigation. Precise blueprints are often not available, and constructing a map of the indoor geometry by hand may not be feasible. Fingerprinting-based localization systems rely on the data received by the user from the access points (APs). Before a system can be deployed, certain properties of the received electromagnetic signal have to be measured at a number of locations throughout the indoor environment. The approach presented in this paper uses the resulting fingerprint map to reconstruct the 3D indoor geometry. The novel approach first calculates the positions of the virtual transmitters (VTs), the reflections of the APs, and then uses the VT positions to reconstruct the indoor geometry. The scheme is designed for multipath-based fingerprints. Several metrics for evaluating the performance of an indoor reconstruction algorithm are also derived. The performance of the proposed approach is validated through simulation. The proposed algorithm is shown to correctly reconstruct up to 66% of the 3D indoor geometry and up to 81% of its 2D perimeter.