IN33A-3755:
Adaptive Sparse Signal Processing for Discrimination of Satellite-based Radiofrequency (RF) Recordings of Lightning Events
Wednesday, 17 December 2014
David A Smith1, Daniela I Moody2, Matthew Heavner2 and Timothy Hamlin3, (1)Los Alamos Natl Lab, Los Alamos, NM, United States, (2)Los Alamos National Laboratory, Los Alamos, NM, United States, (3)Los Alamos National Lab, Los Alamos, NM, United States
Abstract:
Ongoing research at Los Alamos National Laboratory studies the Earth’s radiofrequency (RF) background utilizing satellite-based RF observations of terrestrial lightning. The Fast On-orbit Recording of Transient Events (FORTE) satellite, launched in 1997, provided a rich RF lightning database. Application of modern pattern recognition techniques to this dataset may further lightning research in the scientific community, and potentially improve on-orbit processing and event discrimination capabilities for future satellite payloads. We extend sparse signal processing techniques to radiofrequency (RF) transient signals, and specifically focus on improved signature extraction using sparse representations in data-adaptive dictionaries. We present various processing options and classification results for on-board discharges, and discuss robustness and potential for capability development.
