[1] We present a system that processes phase and group delay time series from a network of dual-frequency GPS receivers and produces a dynamic ionospheric model that is consistent with all the input data. The system is intended for monitoring the ionosphere over a fixed geographical area with dimensions of the order of several thousand kilometers. The inversion technique utilized in this system stems from the inversion technique previously developed by our group within the Coordinate Registration Enhancement by Dynamic Optimization (CREDO) project (a software package for inverting the vertical sounding, backscatter sounding, and satellite total electron content (TEC) data for over-the-horizon radar). The core of this technique is Tikhonov's methodology for solving ill-posed problems. We extended the method to multidimensional nonlinear inverse problems and developed techniques for fast numerical solution. The resulting solution for the ionospheric distribution of electron density is guaranteed to be smooth in space and time and to agree with all input data within errors of measurement. The input data consist of time series of absolute TEC and relative TEC (directly calculated from the raw dual-frequency group delays and phase delays, respectively). The system automatically estimates the measurement noise and receiver-transmitter biases. We test the system using archived data from dual-frequency GPS receivers in the southern California Scripps Orbit and Permanent Array Center (SOPAC) network and data from a vertical sounder.Citation: Fridman, S. V., L. J. Nickisch, M. Aiello, and M. Hausman (2006), Real-time reconstruction of the threedimensional ionosphere using data from a network of GPS receivers, Radio Sci., 41, RS5S12,
An analytical expression for the two‐frequency, two‐position, two‐time mutual coherence function applicable to propagation through thick random media with nonuniform electron density and plasma velocity is derived using the phase‐screen/diffraction method (PDM). In this method the ionization is collapsed to a number of thin screens and diffraction is developed in the free space between. The resulting mutual coherence function converges rapidly to the continuum result as the number of screens representing the medium is increased. The effects of multiple scatter occurring over long distances and varying plasma velocity over the propagation path are shown to be important in HF propagation. Scattering functions (delay‐Doppler power spectra) obtained as Fourier transforms of the PDM mutual coherence function are compared to scattering functions measured by an HF channel probe. Nonuniform velocity profiles are shown to account for the variety of delay‐Doppler couplings observed.
We present new capabilities of our system for monitoring the ionosphere over a fixed geographical area with dimensions of the order of several thousand kilometers. The system employs a nonlinear representation for electron density that ensures a nonnegative solution. The multidimensional nonlinear inverse problem is efficiently solved using a combination of the Newton‐Kontorovich method and Tikhonov's regularization technique for ill‐posed problems. The system is able to utilize a variety of types of ionospheric data, which are as follows: networks of ground‐ and space‐based (satellite mounted) dual‐frequency GPS receivers provide time series of oblique absolute total electron content (TEC) and/or relative TEC data (directly calculated from the raw dual‐frequency group delays and phase delays, respectively), TEC data from ground‐ or space‐based receivers operating with dual‐frequency beacons mounted on low‐Earth orbit (LEO) satellites, vertical TEC data from orbiting radio altimeters (such as Jason satellite), in situ electron density data from plasma probes on LEO satellites (such as Challenging Minisatellite Payload for Geophysical Research and Application), and electron density profiles from sounders. The resulting solution for the distribution of electron density is guaranteed to be smooth in space and time and to agree with all input data within errors of measurement. Real time performance is attained on a single personal computer with 5 min data refreshment period. Operation of the system is tested on real data with various data types simultaneously present. A new form of the stabilizing functional is developed to ensure reasonable assimilation of the in situ electron density data.
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