Contaminant cloud boundary monitoring using network of UAV sensors

Abstract

We describe research work currently being undertaken to detect, model, and track the shape of a contaminant cloud boundary using air borne sensor swarms. A model of the contaminant cloud boundary is first developed using a splinegon, defined by a set of vertices linked by segments of constant curvature. This model is then used in an estimator to predict the evolution of the contaminant cloud. This approach is efficient in that only the vertices and segment curvatures are required to define the cloud boundary, rather than using a distribution function to represent the dispersion density.