Neural Network System for the Analysis of Transient Phenomena on Board the DEMETER Micro-Satellite

Franck ELIE  Masashi HAYAKAWA  Michel PARROT  Jean-Louis PINÇON  Francois LEFEUVRE  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E82-A   No.8   pp.1575-1581
Publication Date: 1999/08/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
DEMETER,  seismic related phenomena,  neural network,  whistler,  

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In 2001, the DEMETER micro-satellite will be launched to perform Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions. Its main scientific objective is related to the investigation of the ionospheric perturbations due to the seismic and volcanic activity. A system allowing an onboard identification and characterization of spatially and temporally coherent structures associated with the measurement of one or several electromagnetic wave field components is used. It is based on neural networks. The choice and training of the neural network are done on the ground from available waveforms. The parameters of the neural network system are then transmitted to the satellite. This reconfiguration process can be repeated whenever necessary during the space mission. Details about the functioning and coding optimization for DSP implementation is presented. The first function of this system which will be performed on the satellite DEMETER is the real-time identification and characterization of whistler phenomena. An application to the analysis of such phenomena observed in data from the AUREOL-3 satellite is exposed.