Physical Sciences and Mathematics Commons^™

Single Object Detection Using Multiple Sensors With Unknown Noise Distributions, Shaofen Chen

Computer Science Theses & Dissertations

We consider the design of an object classification system that identifies single objects using a system of sensors; each sensor outputs a random vector, according to an unknown (noise) probability distribution, in response to a sensed object. We consider a special class of systems, called the linearly separable systems, where the error-free sensor outputs corresponding to distinct objects can be mapped into disjoint intervals on real line. Given a set of sensor outputs corresponding to known objects, we show that a detection rule α_emp that approaches the correct rule with a high probability can be computed. We show …