Articles | Volume 26, issue 8
https://doi.org/10.5194/angeo-26-2281-2008
https://doi.org/10.5194/angeo-26-2281-2008
05 Aug 2008
 | 05 Aug 2008

Towards multi-purpose IS radar experiments

I. I. Virtanen, M. S. Lehtinen, and J. Vierinen

Abstract. The EISCAT incoherent scatter radars routinely perform simultaneous measurements of E- and F-regions of the ionosphere. In addition several experiments exist for measuring pulse-to-pulse correlations from the D-region. However, the D-region experiments have quite limited range extents and the short lags suffer from F-region echoes, which are difficult to properly handle with standard decoding methods.

In this paper it is demonstrated with real data how D-region experiments can be designed to produce continuous lag profiles extending above the F-region maximum. The large range coverage is attained for all lags shorter than the longest transmission pulse and it allows one to properly include the F-region echoes in the analysis. The large coverage is not needed for pulse-to-pulse lags because E- and F-regions do not have this long correlation times. The lag profiles with large range extent also provide a useful measurement of the upper parts of the ionosphere.

The experiments utilise new kind of phase coding technique, which has estimation accuracy comparable to that of alternating codes though the code sequence is very short. No special decoding method is applied to the codes, because the lag profile inversion method automatically adapts to any kind of transmission codes provided transmission samples are available.

The computing resources needed for real-time lag profile inversion with two different kinds of goals are also discussed here: 1) real-time monitoring of the results and 2) use of inverted lag profiles as a way to permanently store the data. While it was possible to accomplish real-time monitoring with a standard high-end desktop workstation, the higher resolution requirement for permanent data storage purposes is a much more critical task, requiring the use of larger-scale parallel processing.