Intelligent Wind Estimation for Chemical Source Localization

Abstract

This paper presents a methodology to sense ambient wind conditions to assist in localizing the source of a released agent using small unmanned aerial systems (sUAS). The technology and methods to detect, localize, and model release and dispersion of chemical, biological, radiological, or nuclear (CBRN) agents have been enhanced by integrating cross-disciplinary solutions using advances from sensor design, intelligent signal processing, control systems, vehicle design, chemical modeling, and atmospheric modeling. The miniaturization of sensors and sUAS has enabled the application of sUAS with a chemical sensor payload to detect and localize the source of CBRN agents. In many instances, this chemotaxis operation can be performed faster and more accurately with the addition of atmospheric information, such as ambient wind condition. The paper provides an overview of chemical source localization and current challenges which motivated this work, including operation in complex settings and turbulence. Analysis of these challenges from an atmospheric science perspective is summarized along with strategies to obtain accurate and useful wind estimates that assist in localizing the source quickly and efficiently. A description of the wind estimation approach, based on Bayesian estimation, is provided along with results from simulation studies utilizing realistic vehicle dynamics, wind, turbulence, and chemical plume models.