High-accuracy indoor positioning is a demanding but challenging technology. In the Internet of Things applications, the existing indoor positioning schemes face the following challenges: 1) for the active positioning schemes, e.g., WiFi, Bluetooth, etc., the targets need power supply to emit signals; and 2) for the passive positioning schemes, e.g., Radar, Lidar, etc., the base station usually needs beam-steering control to aim at the targets for receiving sufficient reflective signals. Here, we propose a passive 3-dimensional monocular positioning scheme, resonant beam based positioning (RBP), which adopts a resonant beam for angle-of-arrival estimation and a time-of-flight module for distance estimation. We present the principle of the proposed scheme and establish analytical models and simulation tools for evaluating the impacting factors on the positioning accuracy including sensing noises, signal power, etc. To verify the RBP performance, we also present a testbed. Both numerical analysis and experimental measurements demonstrate that the positioning accuracy can be less than 1cm over 2m distance in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$15^{\circ }$</tex-math></inline-formula> field of view. With RBP, high-accuracy and monocular without computation and high complexity positioning can be achieved while the target needs no power supply and the base station needs no beam-steering control. RBP is an important candidate for providing location-aware services in the Internet of everything and the proposed simulation models provide guidelines for system analysis and design.
Read full abstract