Inversion of oblique ionograms including the Earth's magnetic field

Phanivong, B.; Chen, J.; Dyson, P. L.; Bennett, J. A.

doi:10.1016/0021-9169(95)00092-g

Cited by 11 publications

(10 citation statements)

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“…Gething and Maliphant [] suggested a double‐step method in which an oblique ionogram is converted into a vertical and analyzed by means of inversion techniques developed for vertical ionograms. A further approach is to obtain the electron density profile directly from the oblique ionogram, as has been proposed by Phanivong et al []. This method takes into account the presence of the Earth's magnetic field and is based on the inversion technique developed by Reilly and Kolesar [], which considers the curvature of the ionosphere and handles the ambiguity related to the presence of the valley in the electron density profile.…”

Section: Automatic Scaling Of Oblique Ionogramsmentioning

confidence: 99%

A procedure for the reliability improvement of the oblique ionograms automatic scaling algorithm

et al. 2016

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A procedure made by the combined use of the Oblique Ionogram Automatic Scaling Algorithm (OIASA) and Autoscala program is presented. Using Martyn's equivalent path theorem, 384 oblique soundings from a high-quality data set have been converted into vertical ionograms and analyzed by Autoscala program. The ionograms pertain to the radio link between Curtin W.A. (CUR) and Alice Springs N.T. (MTE), Australia, geographical coordinates (17.60°S; 123.82°E) and (23.52°S; 133.68°E), respectively. The critical frequency f o F 2 values extracted from the converted vertical ionograms by Autoscala were then compared with the f o F 2 values derived from the maximum usable frequencies (MUFs) provided by OIASA. A quality factor Q for the MUF values autoscaled by OIASA has been identified. Q represents the difference between the f o F 2 value scaled by Autoscala from the converted vertical ionogram and the f o F 2 value obtained applying the secant law to the MUF provided by OIASA. Using the receiver operating characteristic curve, an appropriate threshold level Q t was chosen for Q to improve the performance of OIASA.

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Section: Automatic Scaling Of Oblique Ionogramsmentioning

confidence: 99%

A procedure for the reliability improvement of the oblique ionograms automatic scaling algorithm

et al. 2016

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“…Most run in near real time on the sounder system itself, applying a consistent set of conventions (Piggott & Rawer, ) to characterize the propagation characteristics and reduce the ionogram image to a parameterized representation. These automatic techniques generally fall into one of two main categories: Trace extraction or skeletonization, typically using a combination of morphological image operations, computer vision, and tracking algorithms (e.g., Chen et al, ; Galkin & Reinisch, ; Guiducci et al, ; Su et al, ; Zheng et al, ), followed by profile inversion (e.g., Huang & Reinisch, ; Phanivong et al, ; Reilly & Kolesar, ; Titheridge, ). A prominent example is the software package ARTIST (Galkin & Reinisch, ; Reinisch et al, ; Reinisch et al, ; Reinisch & Huang, ), developed for the Lowell Digisonde (Reinisch et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…These automatic techniques generally fall into one of two main categories: 1. Trace extraction or skeletonization, typically using a combination of morphological image operations, computer vision, and tracking algorithms (e.g., Chen et al, 2013;Galkin & Reinisch, 2008;Guiducci et al, 1983;Su et al, 2012;Zheng et al, 2013), followed by profile inversion (e.g., Huang & Reinisch, 1982;Phanivong et al, 1995;Reilly & Kolesar, 1989;Titheridge, 1988). A prominent example is the software package ARTIST (Galkin & Reinisch, 2008;Reinisch et al, 1988;Reinisch et al, 2005;Reinisch & Huang, 1983), developed for the Lowell Digisonde (Reinisch et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

A Robust Feature Extraction and Parameterized Fitting Algorithm for Bottom‐Side Oblique and Vertical Incidence Ionograms

Heitmann

Gardiner-Garden

2019

Radio Science

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Automatic processing of ionograms to extract ionospheric propagation characteristics and electron density profile parameters is an important enabling step toward constructing real time data‐assimilative models of the ionosphere. A robust and reliable feature extraction and fitting algorithm that supports both oblique and vertical incidence ionograms has recently been developed to enhance the regional ionospheric model for Australia's Jindalee Operational Radar Network. The so‐called DST‐IIP algorithm is an autoscaling technique based on a constrained quasi‐parabolic segment profile, which is modified from its climatological estimate to fit a set of key peak, edge, and line features in the ionogram image, representing the E, sporadic‐E (Es), and F2 layers. The F2 fitting, in particular, is performed in the ionogram domain, using analytic ray‐tracing and homing to produce a synthetic trace that reproduces the image features. Following thorough testing on a large database of midlatitude Australian ionograms, the DST‐IIP algorithm now runs routinely on‐board DST Group's Digital Oblique Receiving System. This paper provides an overview of the technique, along with sample results and performance statistics.

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“…Later, Reilly and Kolesar (1989) improved the inversion method proposed by Reilly (1985) (known as the R-K method), it simultaneously solved the equations for group path delay and sounder range by using analytical method which was more accurate than the Breit-Tuve theorem. A technique which was a development of the work of Reilly and Kolesar was presented (Phaninong et al, 1995), it considered the effect of the Earth's magnetic field. An analysis of the inversion results with and without Earth's magnetic field found that the former was closer to the real values.…”

Section: Introductionmentioning

confidence: 99%

Inversion of Oblique Ionograms Based on Hybrid Genetic Algorithm

Song

Zhao

et al. 2014

Chinese J of Geophysics

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The oblique sounding is a powerful tool for acquiring ionospheric information, and we can get the structural parameters related to ionosphere by inversing the oblique ionogram. Genetic algorithm (GA) is a widely used inversion method which can reduce the non-uniqueness of the inversion problems without depending on the initial estimation, but the accuracy and reliability of GA's inversion results may be decreased due to "premature convergence" and inferior local search ability. So an improved hybrid genetic algorithm (HGA) based on simulated annealing algorithm (SA) is proposed and firstly applied to inversion of oblique ionogram. HGA combines the advantages of GA and SA together and makes full use of them, so it has a strong global search ability and local search ability. To verify the reliability and stability of HGA's inversion results, we firstly use GA, SA, and HGA to inversion of the synthetic oblique ionogram and compare the inversion results of the three algorithms, find that HGA's results are nearest to the real values and its needed iterations are also much smaller than others. The inversion results include the critical frequency, the height of maximum electron density and half-thickness. Then, comparing the influences on inversion results by changing the population size and the total iterations, we find that the HGA effectively reduces the influences. Lastly, we use the three algorithms to invert the real ionograms and compare the inversion results with the vertical data in the midpoint of transmitting and receiving site. The results show that the stability and the searching optimal solution ability of HGA are obviously better than the GA and SA, and its inversion results are reliable, so HGA has strong referential significance and practical value for the inversion of real ionograms.

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Inversion of oblique ionograms including the Earth's magnetic field

Cited by 11 publications

References 10 publications

A procedure for the reliability improvement of the oblique ionograms automatic scaling algorithm

A procedure for the reliability improvement of the oblique ionograms automatic scaling algorithm

A Robust Feature Extraction and Parameterized Fitting Algorithm for Bottom‐Side Oblique and Vertical Incidence Ionograms

Inversion of Oblique Ionograms Based on Hybrid Genetic Algorithm

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