Tomography of the ionospheric electron density with geostatistical inversion

نویسندگان

  • D. Minkwitz
  • K. G. van den Boogaart
  • T. Gerzen
  • M. Hoque
چکیده

In relation to satellite applications like global navigation satellite systems (GNSS) and remote sensing, the electron density distribution of the ionosphere has significant influence on trans-ionospheric radio signal propagation. In this paper, we develop a novel ionospheric tomography approach providing the estimation of the electron density’s spatial covariance and based on a best linear unbiased estimator of the 3-D electron density. Therefore a non-stationary and anisotropic covariance model is set up and its parameters are determined within a maximum-likelihood approach incorporating GNSS total electron content measurements and the NeQuick model as background. As a first assessment this 3-D simple kriging approach is applied to a part of Europe. We illustrate the estimated covariance model revealing the different correlation lengths in latitude and longitude direction and its non-stationarity. Furthermore, we show promising improvements of the reconstructed electron densities compared to the background model through the validation of the ionosondes Rome, Italy (RO041), and Dourbes, Belgium (DB049), with electron density profiles for 1 day.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Tomographic Reconstruction of the Ionospheric Electron Density in term of Wavelets

Ionospheric tomography is a method to investigate the ionospheric electron density in two or three dimensions. In this study, the function-based tomographic technique has been used for regional reconstruction of a 3D tomographic model of the ionospheric electron density using the GPS measurements of the Iranian Permanent GPS Network. Two-dimensional Haar wavelets and empirical orthogonal functi...

متن کامل

Application of Wavelet Neural Networks for Improving of Ionospheric Tomography Reconstruction over Iran

In this paper, a new method of ionospheric tomography is developed and evaluated based on the neural networks (NN). This new method is named ITNN. In this method, wavelet neural network (WNN) with particle swarm optimization (PSO) training algorithm is used to solve some of the ionospheric tomography problems. The results of ITNN method are compared with the residual minimization training neura...

متن کامل

A PIM-aided Kalman Filter for GPS Tomography of the Ionospheric Electron Content

We develop the formalism for a PIM-based functional for stochastic tomography with a Kalman filter, in which the inversion problem associated with four-dimensional ionospheric stochastic tomography is regularized. For consistency, GPS data is used to select dynamically the best PIM parameters, in a 3DVAR fashion. We demonstrate the ingestion of GPS (IGS and GPS/MET) data into a parameterized io...

متن کامل

Validation of electron density profiles derived from oblique ionograms over the United Kingdom

Inversion algorithms are available to derive the vertical electron density profile at the mldpoint of an oblique sounder path. The techniques open up the possibility of monitoring the ionosphere at otherwise inaccessible locations, such as over sea or inhospitable terrain. A new method of monitoring the ionosphere based on radio tomography can be used to create two-dimensional images of electro...

متن کامل

1 COSMIC GPS Ionospheric Sensing and Space Weather

As our civilization becomes more dependent on space based technologies, we become more vulnerable to conditions in space weather. Accurate space weather specification and forecasting require proper modeling which account for the coupling between the sun, the magnetosphere, the thermosphere, the ionosphere and the mesosphere. In spite of the tremendous advances that have been made in understandi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015