Latency constrained device positioning using a visible light communication two-phase received signal strength - angle of arrival algorithm

In positioning systems there is a fundamental tradeoff between accuracy and latency. A latency constrained optimization algorithm is proposed to be employed in conjunction with a prior published two-phase algorithm for estimating the location of a mobile node over the visible light channel. Instead of solely relying on triangulation, the mobile nodes estimate their locations through a two phase algorithm in which they firstly exploit the signal strength observables with unique IDs to establish a coarse estimate, and secondly use the azimuth and elevation observables to establish a fine estimate. In many cases, the fine estimate will improve upon the coarse estimate; however when triangulation fails, the algorithm yields the coarse estimate rather than a localization failure. Since the environment model relies on the primary requirement of adequate illumination, the number of LED anchors, and transmit power for communication functions are determined. The advantage of the two-phase algorithm is that it provides a framework to provide rapid RSS based positional estimates with accuracies bounded to within the illumination projection radius (48 cm median) of the distributed luminaries (anchor nodes) within less than 17 nanoseconds while requiring only a single luminaire in its field of view. However, when there are a sufficient number of luminaires in view the positioning algorithm can further improve the accuracy (14 cm median) through application of triangulation via angle of arrival measurements, at the expense of latency (upto tenths of seconds). The proposed framework allows a fundamental trade of accuracy and latency to be made depending on the observable parameters known to the positioning algorithm at run time.