A Comparison of Electron Densities Derived by Tomographic Inversion of the 135.6‐nm Ionospheric Nightglow Emission to Incoherent Scatter Radar Measurements

2019 ◽  
Vol 124 (6) ◽  
pp. 4585-4596 ◽  
Author(s):  
K. F. Dymond ◽  
A. C. Nicholas ◽  
S. A. Budzien ◽  
A. W. Stephan ◽  
C. Coker ◽  
...  
Keyword(s):  
Incoherent Scatter Radar ◽  
Electron Densities ◽  
Tomographic Inversion ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Radar Measurements

scholarly journals Modernization of the Irkutsk Incoherent Scatter Radar

2017 ◽  
Vol 3 (3) ◽  
pp. 76-81
Author(s):  
Дмитрий Кушнарев ◽  
Dmitriy Kushnarev ◽  
Валентин Лебедев ◽  
Valentin Lebedev ◽  
Виталий Хахинов ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Acquisition System ◽  
Incoherent Scatter Radar ◽  
Signal To Noise ◽  
Incoherent Scatter ◽  
Angle Measurements ◽  
Scatter Radar ◽  
Space Experiments ◽  
Radar Measurements ◽  
Noise Ratio

We present the results of modernization of the Irkutsk Incoherent Scatter Radar’s control and acquisition system. The modernization was carried out using results of space experiments Plasma–Progress and Radar–Progress involving Progress cargo spacecraft. The modernization has improved the accuracy of radar measurements of low-orbit spacecraft. For example, with a signal-to-noise ratio equal to10, the accuracy of range and angle measurements is 100–300 m and 1–5 arc min.

scholarly journals Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

2016 ◽  
Vol 9 (4) ◽  
pp. 1859-1869 ◽  
Author(s):  
Johannes Norberg ◽  
Ilkka I. Virtanen ◽  
Lassi Roininen ◽  
Juha Vierinen ◽  
Mikko Orispää ◽  
...  
Keyword(s):  
Markov Random Fields ◽  
Sparse Matrix ◽  
Ground Truth ◽  
Accurate Information ◽  
Inversion Algorithm ◽  
Incoherent Scatter Radar ◽  
Ionospheric Tomography ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Radar Measurements

Abstract. We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultra-high-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.

scholarly journals Estimating the vector electric field using monostatic, multibeam incoherent scatter radar measurements

Radio Science ◽  
2014 ◽  
Vol 49 (11) ◽  
pp. 1124-1139 ◽  
Author(s):  
Michael J. Nicolls ◽  
Russell Cosgrove ◽  
Hasan Bahcivan
Keyword(s):  
Electric Field ◽  
Incoherent Scatter Radar ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Radar Measurements

scholarly journals Ionosonde measurements in Bayesian statistical ionospheric tomography with incoherent scatter radar validation

2015 ◽  
Vol 8 (9) ◽  
pp. 9823-9851
Author(s):  
J. Norberg ◽  
I. I. Virtanen ◽  
L. Roininen ◽  
J. Vierinen ◽  
M. Orispää ◽  
...  
Keyword(s):  
Markov Random Fields ◽  
Sparse Matrix ◽  
Accurate Information ◽  
Height Distribution ◽  
Inversion Algorithm ◽  
Incoherent Scatter Radar ◽  
Ionospheric Tomography ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Radar Measurements

Abstract. We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters, and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient and statistically clear inversion algorithm for tomography. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT UHF incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the height distribution of electron density, and outperforms the alternative prior information sources. With an ionosonde at continuous disposal, the presented method enhances stand-alone near real-time ionospheric tomography for the given conditions significantly.

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