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.

The simultaneous measurement of five field components (three magnetic and two electric components) was carried out on board the ionospheric Aureol-3 satellite in a frequency range from 10 Hz to 1.5 kHz, and we have developed a systematic signal processing of direction finding for ionospheric and magnetospheric ELF emissions at eight selected frequencies mainly based on the likelihood concept. So, the purpose of this paper is to present the detailed description of those systematic direction finding measurements at frequencies above and below the proton gyrofrequency, but more emphasis is placed on the latter frequency range where two possible modes of propagation may coexist. This kind of systematic analyses will be of great use in the future wave analysis system on the spacecrafts.