Adaptive Techniques for Intelligent Onboard Magnetospheric/Ionospheric Radar

Rapid detection and response to sudden changes in the space plasma surrounding the Earth is instrumental to achieving the strategic goals in Sun-Earth Connection and Space Weather research conducted by NASA. It also provides important knowledge for adaptive planning of the science instrument operations that have to accommodate tremendous plasma variability along the orbit. Radio sounding has been used by multiple space missions to accurately determine plasma density, both locally and remotely. Its major science product, however, is an image of signal strength in the frequency vs. travel time frame, whose autonomous analysis onboard is a non-trivial, intelligent system task. We present a fully-autonomous technique for analysis of relaxation sounding data collected by the Radio Plasma Imager (RPI) on IMAGE satellite during 2000-2005. The technique interprets data by detecting signatures of major plasma resonances in the image and then interpreting them by seeking the best match to the theoretical model of resonance inter-dependencies. Testing of the algorithm against collected RPI data indicate partial success in evaluation of resonance frequencies. Whereas robust and accurate determination of the electron gyro-frequency from RPI data appears possible, the plasma frequency signatures can often be too weak to be detected and interpreted automatically. We discuss the conditions for correct evaluation of the plasma frequency in the RPI data, derive requirements to the radar instrument design from the analysis results, and outline potential for onboard implementation and utility in subsequent decision making process.