LIPO: Indoor position and orientation estimation via superposed reflected light

Owing to the widespread use of LED lighting and multipath-free propagation, light-to-camera communications (LCC) hold potential in the deployment of ubiquitous, robust, and accurate indoor positioning systems. However, existing LCC-based positioning systems require the presence of the luminaires in the image, which limits the light-to-camera distance and the range of orientation estimation. We propose LIPO, which uses a smartphone to measure the signal strengths of reflections from the user’s chest. We design a set of modulation, sampling and signal recovery mechanisms, which resolves the received signal strength (RSS) of each beacon. Given the RSS measurements, LIPO estimates the user’s 3D location and heading direction via a simple trilateration algorithm. Our design overcomes the light-to-camera distance limitation which exists in most photogrammetry-based positioning approaches and extends the range of orientation estimation to full 360 ∘ . We implement LIPO and extensively evaluate its performance in a 72-m 2 room and a corridor. Our experiments demonstrate that LIPO can achieve decimeter location error and around 6 ∘ orientation error.