A hybrid reconstruction algorithm for 3-D ionospheric tomography

In this paper, a hybrid reconstruction algorithm (HRA) is presented to solve the ill-posed inverse problem associated with 3-D ionospheric stochastic tomography. In this new method, the ionospheric electron density (IED) can be inverted by using two steps. First, a truncated singular value decomposition (TSVD) method, whose value is independent on any initial estimation, is used to resolve the ill-posed problem of the tomography system. Second, taking into account the "approximation" of its solution, an iterative improvement process of the solution is then implemented by utilizing the conventional algebraic reconstruction algorithm (ART). The HRA, therefore, offers a more reasonable approach to choose an initial approximate for the ART and to improve the quality of the final reconstructed image. A simulated experiment demonstrates that the HRA method is superior to the TSVD or the ART alone for the tomographic inversion of IED. Finally, the HRA is used to perform GPS-based tomographic reconstruction of the IED at mid- and low-latitude regions

Application of radio tomographic imaging to HF oblique incidence ray tracing

Radio tomography is a technique for generating images of the spatial structure of ionospheric electron density over a wide area. This paper assesses the potential use of radio tomography in HF oblique propagation and ray tracing applications. Synthetic ionograms produced by ray tracing through tomographic images and ionospheric models have been compared with experimental oblique ionograms from six paths lying close to the image plane in the United Kingdom. In particular, study has been made of the effects of various types of input information used to constrain the vertical electron density structure in the tomographic reconstructions. It was found that use of a fine height resolution (5 km) and incorporation of information from one vertical ionosonde in the reconstruction process makes significant improvements to the overall reliability of the tomographic image. As expected, E layer propagation is better defined using a climatological model than by tomography. However, in comparison with three ionospheric models, use of tomographic images can significantly reduce the RMS error in the determination of the F2 layer maximum usable frequency

Ionosphere Model Development using Regression Method

For earth survival an ionosphere is most important and utmost noteworthy for vital satellite communiqué for the navigation positioning exactness persistence. It encompasses different number of layers subject to the quantity of electron density based on distance. So many ionospheric models of its kind are available to guess electron density with temporal determinations based on different research done within this era. GPS data are habitually castoff in these models. Because of that the essentiality is, a required of progressing ionospheric models to cope up with dissimilar time period for low latitudes of nation. Apart from this, an ionospheric tomography is not a well-posed problem. Ionospheric TEC bring into being concurrently in copious locations, which can be determined by a number of methods to overcome electron density. This paper is projected for the research of developing a method to estimate of total electron density which cover entire Indian region. Largely we can utilized satellite data and placed together by number of calculations. The organization of massive figures are intended the usage of data mining algorithms, and artificial neural network algorithms intended to guesstimate. A thorough study on ionospheric model development using regression method and further proposed idea based on literature can be seen in current research paper

Three-dimensional, high resolution, computerized ionospheric tomographic imaging and computational modeling of an artificial ionospheric cavity

Tomographic techniques use line integral measurements to reconstruct local values of the measured parameter. These techniques have been applied to the ionosphere by using radio transmissions to measure the integral of electron density between a satellite and a chain of ground-based receiving stations. The resultant reconstructions form a two-dimensional map of the electron density in the plane of the satellite/receiver chain. Insufficient quantity of receivers and not having a complete range of accessible look angles with the available receivers are responsible for the non-uniqueness in the reconstructions. The limited look angle problem can be alleviated by making use of alternative data sources such as incoherent scatter radars ( ISR) that provide information on the vertical structure of the electron density. The non-optimal receiver placement problem can be alleviated through the use of sophisticated reconstruction algorithms. The computerized ionospheric tomography (CIT) technique has recently been used to image the artificially modified ionosphere above the Arecibo Observatory (AO) HF heating facility. A total of nine radio beacon receivers forming a three by three matrix were deployed across the entire island of Puerto Rico. The arrangement maximizes the likelihood that several of the receiver-to-satellite lines of sight would intersect the heated region of the ionosphere. Several satellite passes associated with such an intersection occurred, and the resultant tomographic inversions indicate the existence of an electron density cavity approximately 45 kilometers in latitudinal extent. The reduction of electron density in this cavity was typically on the order of 20%. The experimental observations were supported by theoretical work using the open-source SAMI2 ionospheric model. Methods were developed to model both the ohmic heating of the electrons and the suprathermal heating caused by nonlinear effects. Modeled ohmic heating values of 941 K/s match the observed heated temperature profiles. Modeled suprathermal electrons effects on the vibrational temperature of N2 indicate a vibrational/translation temperature differential of 308°K

Simultaneous multiplicative column normalized method (SMART) for the 3D ionosphere tomography in comparison with other algebraic methods

The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools to provide link specific ionospheric corrections as well as to study and monitor physical processes in the ionosphere. In this paper, we introduce a simultaneous multiplicative column-normalized method (SMART) for electron density reconstruction. Further, SMART+ is developed by combining SMART with a successive correction method. In this way, a balancing between the measurements of intersected and not intersected voxels is realised. The methods are compared with the well-known algebraic reconstruction techniques ART and SART. All the four methods are applied to reconstruct the 3-D electron density distribution by ingestion of ground-based GNSS TEC data into the NeQuick model. The comparative case study is implemented over Europe during two periods of the year 2011 covering quiet to disturbed ionospheric conditions. In particular, the performance of the methods is compared in terms of the convergence behaviour and the capability to reproduce sTEC and electron density profiles. For this purpose, independent sTEC data of four IGS stations and electron density profiles of four ionosonde stations are taken as reference. The results indicate that SMART significantly reduces the number of iterations necessary to achieve a predefined accuracy level. Further, SMART+ decreases the median of the absolute sTEC error up to 15, 22, 46 and 67% compared to SMART, SART, ART and NeQuick respectively

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

A hybrid reconstruction algorithm for computerized ionospheric tomography

Computerized Ionospheric Tomography (CIT) is a method to reconstruct ionospheric electron density images by using the Global Positioning System data collected by the earth based receivers. In this study, Total Electron Content values obtained from a model based ionosphere and tomographic reconstruction techniques are used together to obtain ionospheric electron density distribution. Algebraic Reconstruction Technique (ART) is one of the most commonly used reconstruction method in medical tomography due to its simplicity in implementation. The performance of ART is independent of basis functions and very sensitive to the initial state. Total Least Squares (TLS) algorithm assumes no regularization and produces the lowest error for Haar basis for a given Latitude interval. The performance of TLS is improved with the number of receivers. If only one receiver is used, TLS algorithm together with Haar basis functions produces a low computational complexity and has a lower reconstruction error compared to Regularized Least Squares Algorithm, When the estimation by TLS is input as the initial state of ART, the overall reconstruction error reduces significantly compared to the reconstruction error of ART only or TLS with Haar basis only. © 2005 IEEE