Sensor fusion for chemical plume detection, classification, and tracking

The Chemical and Biological Detection Early Warning System (CBDEWS) is a multi-modal sensing approach to realtime chemical and biological detection and warning. The system employs a diverse set of standoff sensors (including LIDAR, IR, and acoustic) and UAV-borne point sensors for the purpose of providing sufficient warning and actionable information in response to a chemical or biological event. This paper describes the data fusion algorithm, which fused individual detection data from all sensors in terms of both cloud location and classification. Additionally, numerous sensors were cued to areas of interest in their field of regard based on detections and their fused result. The fusion algorithm employs grid-based recursive Bayesian estimation to compute an estimate of the cloud's location and classification over a discrete spatial grid. Results from a field test performed at the Dugway Proving Ground in October of 2008 and July of 2009 are presented.