Title of Presentation: A Forest Fire Smart Sensor Concept with UAVSAR

Primary (Corresponding) Author: Yunling Lou

Organization of Primary Author: Jet Propulsion Lab

Co-Authors: Steve Chien, Duane Clark, Joshua Doubleday, Ron Muellerschoen, Sassan Saatchi, Daniel Tran, Yang Zheng

Abstract: We are developing an autonomous disturbance detection and monitoring system with imaging radar that combines the unique capabilities of imaging radar with high throughput onboard processing technology and onboard automated response capability based on specific science algorithms. This smart sensor development leverages off recently developed technologies in real-time onboard synthetic aperture radar (SAR) processor and onboard automated response software as well as science algorithms previously developed for radar remote sensing applications. In this project, we use a high rate data interface to ingest NASAís UAVSAR data and compute SAR imagery in real-time complete with motion compensation and antenna beam steering capabilities. NASAís UAVSAR is a compact, L-band 80 MHz bandwidth, fully polarimetric radar. It is designed for repeat-pass InSAR and has had engineering flights in 2007 and successful science data collections in 2008. The fidelity of the onboard SAR processor is tuned by implementing polarimetric calibration capabilities. Science algorithms are implemented for detecting and monitoring fire disturbances over the US forests. We additionally developed artificial intelligence for decision-making, and adapted existing onboard activity re-planning and execution software to interface with the UAVSAR radar controller. The product of this development is a prototype close loop smart sensor.