An automatic scaling technique for obtaining F₂ parameters and F₁ critical frequency from vertical incidence ionograms

Abstract

[1] Recent advances in computing technologies have renewed interest in the intelligent systems for automatic interpretation of ionograms, images obtained by remote sensing of the ionospheric plasma. The ionogram "autoscaling" techniques based on the template matching method, previously rendered unrealistic for their computing complexity, have now become feasible. This work presents an automatic scaling technique for extracting the main features of the F 1 and F 2 layers of the ionosphere, such as critical frequency and virtual height, from vertical incidence ionograms that do not distinguish O/X polarization of the echoes. The proposed technique uses the quasi-parabolic segments (QPS) to model the electron density profile shapes that are used to synthesize a pool of candidate traces. Moreover, the empirical orthogonal functions and image technique are applied to reduce the size of the candidate traces so that the auto-scaling algorithm can run in realistic time. With the template matching algorithm, the technique will provide the initial parameters of the QPS model for the F 1 and F 2 layers, which are then fine-tuned to obtain the better fitting parameters. In order to evaluate the performance of this technique, a large data set of ionograms recorded in Wuhan at daytime and nighttime in winter, summer, and equinoctial months, are analyzed and investigated. The automatic scaling results are compared with manually scaling results. Our results indicate that the proposed technique described in this paper is reliable and efficient and will facilitate the statistical study of temporal and spatial ionospheric characteristics over Wuhan.

A Statistical Study of Autoscaled Data at the Northern Equatorial Ionization Anomaly During the Year 2016

“…The acceptable value of autoscaled h'F2 can reach to about 92.15% for all the autoscaled foF2. (Similar to previous studies (Jiang et al, ), an acceptable value is within ±25 km of the manual value for the height.) Table shows that the accuracy of the autoscaled h'F2 can increase to 95.75% for the acceptable value if ionograms with Es layer were removed (subset F).…”

“…If the ionoScaler and operator did not have the same rule in identifying the F1 layer when the F1 layer develop not well, then it will cause a large error. (Jiang et al, 2013), an acceptable value is within ±25 km of the manual value for the height.) Table 3 shows that the accuracy of the autoscaled h'F2 can increase to 95.75% for the acceptable value if ionograms with Es layer were removed (subset F).…”

“…However, the high accuracy of autoscaled data is always a challenge work for automatic scaling tools. Many studies (Fox & Blundell, ; Galkin, ; Igi et al, ; Jiang et al, , ; Reinisch & Huang, ; Scotto & Pezzopane, ; Tsai & Berkey, ; Zabotin et al, , and references therein) have made efforts to test the performance of autoscaling algorithms/tools. However, the test data are not large enough to reveal statistical accuracy of these autoscaling tools.…”

Automatic Recognition Method of Layer Paths in the Ionogram Based on Mathematical Morphology Method and Inversion Technology

“…The common inversion algorithms include iteration algorithm (IA) [14], Genetic algorithm (GA) [15] and simulated annealing algorithm (SA) [16], etc. According to our previous study, HGA is better than GA and SA on optimizing ability and stability [12].…”

A New Ionogram Automatic Scaling Method

“…Ding et al () presented a method to scale the F2‐layer parameters automatically on the basis of empirical orthogonal functions in combination with an image matching technique. Jiang et al (, ) presented a method to obtain the F2 parameters and F1 critical frequency by using the quasi‐parabolic segment model and empirical orthogonal functions. Harris et al () and Harris and Pederick () developed a new method to separate the O/X mode for vertical and oblique ionosonde based on direct digital receiver technology and algorithm.…”