Real‐Time Techniques for Interpretation of Ionospheric Backscatter Sounding Data

Abstract

We present techniques and algorithms for automatic processing and interpretation of data of ionospheric backscatter sounding (BS) using a continuous chirp signal. Experimental ionograms are processed based on data filtration with further compression using the cellular automaton method. Interpretation of signals in a backscatter ionogram is carried out by calculating the backscatter leading edge. Slightly changing ratios of frequency dependences for group characteristics of oblique sounding and BS signals in various heliogeophysical conditions are used. Parameters of radio wave propagation are calculated within the waveguide approach using the International Reference Ionosphere model. The results of interpretation for a BS ionogram allow quick determination of maximum usable frequencies, from which characteristics of oblique sounding signals are corrected for given radio paths in the sounding sector of interest.

Inversion of Backscatter Ionograms Into Quasi-Parabolic Ionospheric Layer Parameters

“…An input parameter in the inverse problem is a delay array corresponding to the leading edge of received signals on a BS ionogram. To identify the BS signal leading edge in an ionogram, Ponomarchuk et al [2018] and Penzin et al [2019] have proposed a method of automatic processing and interpretation of ionospheric backscatter sounding data using a continuous chirp signal. Processing of experimental ionograms is based on filtering of raw data with their subsequent compression through cellular automaton.…”

“…Processing of experimental ionograms is based on filtering of raw data with their subsequent compression through cellular automaton. The ionogram interpretation technique relies on results of simulation of BS signal characteristics on the leading edge in the context of the waveguide approach [Ponomarchuk et al, 2009;Penzin et al, 2019] with IRI [Bilitza et al, 2017]. The BS signal leading edge for a frequency f corresponds to the minimum scattered signal propagation delay, or to the minimum group path P m .…”

“…The paper presents a scheme of inversion of the BS signal leading edge into parameters of electron density quasi-parabolic profile by comparing experimental and calculated minimum delays of scattered signals and respective distances to the skip zone border. Input parameters are the results of isolation of the BS signal leading edge, obtained after processing and interpreting BS ionograms [Penzin et al, 2019]. The BS signal leading edge identified by this method is, in fact, a scaled frequency dependence of the minimum group path of signal propagation calculated using the regular predictive ionospheric model without regard to random irregularities.…”

“…To determine the two unknown parameters of the profilecritical frequency and F2layer peak heightalong with the minimum group path the distance to the skip zone border is varied, which allows us to find the unique solution. Unlike [Li et al, 2013], we determine the required real distance to the skip zone border from the ratio of the minimum group path to the distance to the skip zone border, which is an adiabatic invariant, using results of simulation of BS signal characteristics [Penzin et al, 2019]. For a fixed sounding frequency, the pair of ionospheric parameterscritical frequency and F2-layer peak heightis defined as an intersection point of two curves, which are solutions of the problem of minimizing the discrepancy functional for the minimum group path and the distance to the skip zone border.…”

“…For a fixed sounding frequency, the pair of ionospheric parameterscritical frequency and F2-layer peak heightis defined as an intersection point of two curves, which are solutions of the problem of minimizing the discrepancy functional for the minimum group path and the distance to the skip zone border. The inversion scheme developed for BS ionograms is used for real-time calculation of ionospheric parameters from current BS data with the spatially distributed chirp ionosonde developed at ISTP SB RAS [Podlesnyi et al, 2013].…”