Abstract
Abstract. The present standard EISCAT incoherent scatter experiments are based on alternating codes that are decoded in power domain by simple summation and subtraction operations. The signal is first digitised and then different lagged products are calculated and decoded in real time. Only the decoded lagged products are saved for further analysis so that both the original data samples and the undecoded lagged products are lost. A fit of plasma parameters can be later performed using the recorded lagged products. In this paper we describe a different analysis method, which makes use of statistical inversion in removing range ambiguities from the lag profiles. An analysis program carrying out both the lag profile inversion and the fit of the plasma parameters has been constructed. Because recording the received signal itself instead of the lagged products allows very flexible data analysis, the program is constructed to use raw data, i.e. IQ-sampled signal recorded from an IF stage of the radar. The program is now capable of analysing standard alternating-coded EISCAT experiments as well as experiments with any other kind of radar modulation if raw data is available. The program calculates the ambiguous lag profiles and is capable of inverting them as such but, for analysis in real time, time integration is needed before inversion. We demonstrate the method using alternating code experiments in the EISCAT UHF radar and specific hardware connected to the second IF stage of the receiver. This method produces a data stream of complex samples, which are stored for later processing. The raw data is analysed with lag profile inversion and the results are compared to those given by the standard method.
Highlights
In an incoherent scatter radar (ISR) experiment, a radiowave is transmitted to the ionosphere where a small fraction of the original signal is scattered to the receiver antenna
While the lag profile inversion method discussed in this paper can be based on the lagged products, proper handling of some other things such as ground clutter, space debris/satellite echoes and other phenomena with long correlation times are very difficult to analyse from lag profile data
2fs where K=1, 2, 3, . . . and c is the speed of light. Both range and time integration can be performed to improve the accuracy of the autocorrelation function (ACF) estimates
Summary
In an incoherent scatter radar (ISR) experiment, a radiowave is transmitted to the ionosphere where a small fraction of the original signal is scattered to the receiver antenna. The standard EISCAT hardware does not save the received signal itself, but calculates the lagged products in real time and saves them on hard disk after some postintegration. While the lag profile inversion method discussed in this paper can be based on the lagged products, proper handling of some other things such as ground clutter, space debris/satellite echoes and other phenomena with long correlation times are very difficult to analyse from lag profile data This either requires an impractically large number of lag profiles to be stored (so that the storage requirements far exceed those for storage of the IQ-sampled signal itself) or the phenomena are only sub-optimally resolved from the correlated (lag profile) data
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