Single Reflection Spatial Voting: A Novel Method for Discovering Reflective Surfaces Using Indoor Positioning Systems

We present a novel method of using reflected pulses in indoor ultrasonic positioning systems to infer the details of reflective objects in the environment. The method is termed Single Reflection Spatial Voting (SRSV), and we perceive its major use to be in the field of pervasive computing, where automated object and surface discovery is emerging as an important feature.

We demonstrate use of the method in the case of searching for vertical walls using an existing ultrasonic position sensor system (the Bat system). We find that valuable information can be extracted from reflection data using SRSV, and are able to construct a model of the room using a simple algorithm. We conclude that this method can be used to extract base data upon which to build hypotheses about the environment, given further sensor analysis.

We also briefly address the potential uses of SRSV in Ultra-Wideband positioning, autonomous navigation, and map building.