A power-aware, satellite-based parallel signal processing scheme

Authors:
Patrick M. Shriver;Maya B. Gokhale;Scott D. Briles;Dong-In Kang;Michael Cai;Kevin McCabe;Stephen P. Crago;Jinwoo Suh
Affiliations:
Los Alamos Nat'l. Lab.;Los Alamos Nat'l. Lab.;Los Alamos Nat'l. Lab.;Information Sciences Institute;Los Alamos Nat'l. Lab.;Los Alamos Nat'l. Lab.;Information Sciences Institute;Information Sciences Institute
Venue:
Power aware computing
Year:
2002

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Abstract

Satellite subsystem power budgets typically have strict margin allocations that limit the on-board processing capability of the spacecraft. Subsystems are assigned a fixed, maximum power allocation and are managed in an on/off manner according to available power and operations schedule. For a remote-sensing satellite, this limitation can result in poorer detection performance of interesting signal events as well as static instrument or data collection settings. Power-aware computation techniques can be utilized to increase the capability of on-board processing of science data and give the remote-sensing system a greater degree of flexibility.We investigate a power-aware, signal processing scheme used to study signals from lightning events in the Earth's atmosphere. Detection and analysis of these lightning signals is complicated by the frequency dispersion experienced by the signal in the ionosphere as well as the interfering anthropogenic signals. We outline a method using multiprocessor architecture to run processing algorithms which have varying rates of power consumption. A 6 order magnitude spectrum of energy usage for these algorithms is obtained from experiment results.