Title of Presentation: Autonomous Disturbance Detection and Monitoring System with UAVSAR

Primary (Corresponding) Author: Yunling Lou

Organization of Primary Author: NASA Jet Propulsion Laboratory

Co-Authors: Steve Chien, Ron Muellerschoen, and Sassan Saatchi


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 will modify the high rate data interface to ingest UAVSAR data and modify the onboard SAR processor software by adding motion compensation and antenna beam steering capabilities.  We will also improve the fidelity of the onboard SAR processor by implementing polarimetric calibration capabilities and science algorithms for detecting and monitoring fire and hurricane-induced disturbances over the US forests. We will develop artificial intelligence for decision-making, and adapt existing onboard activity replanning and execution software to interface with UAVSAR.  The product of this development is a prototype smart sensor for demonstration on NASA’s UAVSAR, a compact, L-band polarimetric repeat-pass InSAR, which will begin engineering flights in 2007 and science data collection in 2008.  We will use UAVSAR to demonstrate a closed loop smart sensor concept and as an element of a larger sensor web. 

In this paper, we will describe the system architecture of the smart sensor and report progress of the smart sensor development.