This paper discusses an indoor positioning technique aimed at human-centric services such as pedestrian navigation or service robots. The method is called “CEPHEID” and uses a light flickering pattern as an environmental fingerprint. The authors found that each lighting fixture has unique and distinguishable flickering characteristics. In this paper, CEPHEID is introduced as a “classifier” and its validity is shown based on experimental results. Additionally, an approach for improving the positional precision is proposed. The classifier and regressor are combined to create a zone-classified regressor model for CEPHEID. The basic performance of this concept is also tested using an experiment.

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