Abstract

From the very beginning of modern ionospheric science, different radar applications have been utilised in ionospheric measurements. The most sophisticated ionospheric radars are the incoherent scatter radars, which detect the extremely weak scattering of radio waves from thermal fluctuations in the ionospheric plasma. Besides the low signal level, the stochastic nature of the scattering process causes further complications to the measurements. The scattering produces a zero-mean random signal, whose autocorrelation function contains the information of the ionospheric plasma parameters. Incoherent scatter radars have been used for about half a century, but the demanding task of developing transmission modulation and data analysis is still in progress.

In this thesis, a statistical inversion based method for removing range ambiguities from the autocorrelation functions, lag profile inversion, is applied to incoherent scatter radar data. The data have been recorded with the EISCAT incoherent scatter radars, located in Northern Fennoscandia. The method is first applied to standard EISCAT experiments, the results giving strong evidence that the method is applicable for the purpose, and it provides results of at least equal quality with the present standard methods. In subsequent studies, new radar modulation methods are developed, which may provide significant improvements to the present incoherent scatter radar experiments. All the methods have been tested with a real radar, and lag profile inversion has been successfully applied to the recorded data. The methods are also put to use in order to measure the predicted effects of artificial heating of the free electrons in the D-region of the ionosphere.