Ivan A. Nesterov

On generation of an assembly of images in ionospheric tomography

Radio tomography experiments have demonstrated the promising potential of applying tomographic methods in imaging various ionospheric structures. In actual implementation of image reconstructions one is faced with many choices, which include the following: whether to use the total phase, relative phase, or Doppler as the projection data, how to approximate the projection operator, what inversion algorithm to employ, and the choice of how to include the ancillary data and constraints on the constructed image. Each choice results in an image compatible with the given or measured projection data, yet each choice results in an image different from that of the others, with its own attendant artifacts and distortions. Collectively, the images produced by all the possible choices comprise an assembly of images. In this simulation study of one ionospheric model, 113 members of such an assembly are generated. All images look similar in gross features with a root-mean-square deviation not more than 29% from the mean. As expected, the largest deviation occurs near the region of highest gradients. By averaging all of the images in the assembly we show that the mean image is superior because of its smallest root-mean-square deviation from the true image. This conclusion, drawn on the simulation study of one model, may in fact have a general applicability, and we discuss why this may be so.

Ionospheric Sounding and Tomography by GNSS

Studies of the ionosphere and the physics of the ionospheric processes rely on the knowledge of spatial distribution of the ionospheric plasma. Being the propagation medium for radio waves, the ionosphere significantly affects the performance of various navigation, location, and communication systems. Therefore, investigation into the structure of the ionosphere is of interest for many practical applications. Existing satellite navigation systems with corre‐ sponding ground receiving networks are suitable for sounding the ionosphere along different directions, and processing the data by tomographic methods, i.e. reconstructing the spatial distribution of the ionospheric electron density.

Earthquake Prediction Research Using Radio Tomography of the Ionosphere

Under development since its invention in 1990 as an ancillary application of ionospheric radio-tomography (RT), a new earthquake (EQ) prediction system is being evaluated. It has already been deployed along the United States West Coast, from Vancouver in Canada to San Diego in Southern California, and is currently undergoing Beta testing. This Chapter addresses RT–EQ prediction concepts, the underlying RT theory, evolution and implementation, and a few examples of the Beta test system’s performance. This work is an investigation of EQ precursors, which we hope will lead to an operational system. The current system provides a foundation and the tools to study ionospheric effects linked to conditions in the Earth’s crust prior to major earthquakes. Progress toward a fully operational system will require several more years of data acquisition and analysis.

Assessing the degree of ionospheric perturbation from radio tomographic data

The methods are suggested for constructing the ionospheric perturbation indices (IPIs) from the empirical electron density distributions retrieved by the ionospheric radio tomography (RT). The indices take into account the specificity of the low- and high-orbiting (LO and HO) RT data, their spatio-temporal resolution and coverage. We consider and analyze various schemes of IPIs construction, calculate the correlation between the IPIs and geomagnetic Kp index, identify the indices that are most sensitive to the geomagnetic activity factor.

Estimation of sea level variations with GPS/GLONASS-reflectometry technique

In the present paper we study GNSS - reflectometry methods for estimation of sea level variations using a single GNSSreceiver, which are based on the multipath propagation effects caused by the reflection of navigational signals from the sea surface. Such multipath propagation results in the appearance of the interference pattern in the Signal-to-Noise Ratio (SNR) of GNSS signals at small satellite elevation angles, which parameters are determined by the wavelength of the navigational signal and height of the antenna phase center above the reflecting sea surface. In current work we used GPS and GLONASS signals and measurements at two working frequencies of both systems to study sea level variations which almost doubles the amount of observations compared to GPS-only tide gauge. For UNAVCO sc02 station and collocated Friday Harbor NOAA tide gauge we show good agreement between GNSS-reflectometry and traditional mareograph sea level data.

Modeling the problem of low-orbital satellite UV-tomography of the ionosphere

The results of modeling the direct and inverse problems of low-orbital satellite ultraviolet (UV) tomography of the ionospheric 135.6 OI volume emission rate are presented. The direct problem was solved with the orbital geometry of DMSP block 5D3 satellites with SSUSI and SSULI UV spectrographs among the other payloads, the real operating parameters of these instruments (the scan rate and the interval of scan angles), and the set of the model distributions of the volume emission rate that contain irregularities on various scales. The solution of the direct problem yields the radiation intensities in the 135.6 nm line, which is used as the input data for reconstructing the initial (prototype) model distributions of the volume emission rates. The obtained system of linear equations (SLE) was solved using the Algebraic Reconstruction Technique (ART) and Simultaneous Iterative Reconstructive Technique (SIRT) algorithms, which are highly efficient in problems of the low-orbit radio tomography of the ionosphere. It is shown that the initial model distribution can be successively reconstructed if one takes the non-negativity condition of the solution into account, uses weighting functions to decrease the solution in the regions where it is known to be a priori small, and applies inter-iteration smoothing to eliminate the effects of the approximation errors. Here, the averaging parameters should decrease in the course of the iterations. With these constraints fulfilled, the computational costs of the ART- and SIRT-based solutions are similar, while the reconstruction error is approximately 6%. The influence of random errors and bias in the data on the results of the reconstruction is explored. It is shown that with a given error level of the initial data the parameters of the reconstruction algorithms can be adjusted in such a way as to efficiently suppress the influence of the noise with a relative amplitude of 2–3% on the solution.

Radio tomography imaging based on navigation systems

Methods of radio tomography (RT) based on the low- and high-orbital navigational systems and radio occultation data are considered. Examples of RT imaging of the ionosphere in different regions of the world illustrate the use of low-orbital and high-orbital radio tomography (LORT and HORT, respectively) separately and in combination with each other. RT methods allow studying of various ionospheric structures: troughs, travelling ionospheric disturbances (TIDs), spots of enhanced ionizations, patches, blobs, wavelike structures, manifestations of particle precipitation. The possibilities for the application of RT systems together with other methods of UV and radio sounding are discussed.