Light-matching: A new signal of opportunity for pedestrian indoor navigation

This paper presents a new indoor location concept named Light-matching which uses the perceived gradient in the illumination from unmodified indoor lights to achieve accurate physical location. The proposed method does not require any illumination calibration, just the pre-storage of the position and size of all lights in a building, irrespective of their current on/off state. The Light-matching method also requires the estimation of the relative displacement and orientation change of a person which is done by inertial Pedestrian Dead-Reckoning (PDR). Even from an initially unknown location and orientation, whenever the person passes below a switched-on light spot, the location likelihood is iteratively updated until it potentially converges to an unimodal probability density function. The time to converge to an unimodal position hypothesis depends on the number of lights detected and the asymmetries/irregularities of light distributions. The light-matching technique can be used alone or in cooperation with other signals of opportunity (WiFi, Magnetometers or Map-matching) to obtain a continuous high accuracy indoor localization system. This paper presents the basic description of the light-matching concept, the implementation details using a particle filter, and the evaluation of the method by simulation. The performance of the integrated solution can achieve a localization error lower than 1 m in most of the cases.