Modeling the Ionosphere Using Extended Spherical Harmonics Approach for Generation of IRNSS/NavIC based Precise Ionospheric Maps/Products (NPIM) over Indian Region
01 Feb 2020-
TL;DR: A novel technique based on spherical harmonics with an extended polynomial fit is designed for generating NavIC based Precise Ionospheric Maps (NPIM), which is found that NPIM provides better accuracy than GIM data over Indian region.
Abstract: IRNSS (Indian Regional Navigation Satellite System)/NavIC (Navigation with Indian Constellation) is a regional satellite based navigation system over Indian region being developed by Indian Space Research Organisation (ISRO). There are many error sources affecting the navigation performance of satellite based navigation systems. Among them, the error due to ionosphere is the pre dominant source of error especially while working with radio frequencies in real time as well as in post processing mode for areas of ionospheric research. In real time mode, ionospheric error corrections are available to users as broadcast ionospheric corrections for single frequency users and frequency dependent advantage for dual frequency users to correct the ionospheric delay in their line of sight. But there are some applications where precise ionospheric corrections are required in post processed mode for their scientific research and analysis which is a global requirement over equatorial region which is more prone to ionospheric anomalies and high ionospheric variations. Precise ionospheric products in general provide precise total electron content (TEC) values for the identified grid points over the globe at a specified height above the earth considering a thin shell approximation of the ionosphere. These precise ionospheric products are usually generated by monitoring the ionosphere using ground station network ranging to navigation satellites orbiting the earth i.e., GNSS (Global Navigation Satellite System) data. A perfect example is the Global Ionosphere Maps (GIM) generated using IGS (International GNSS Service) stations network. In this paper, effort has been made to generate precise ionospheric products similar to GIM using NavIC ionospheric data for grid points identified over Indian region. A novel technique based on spherical harmonics with an extended polynomial fit is designed for generating NavIC based Precise Ionospheric Maps (NPIM). The generated NPIM over Indian region using this technique is then compared and evaluated with GIM data over Indian region. It is found that NPIM provides better accuracy of 2 to 4 TECU (TEC units) as against 5 to 6 TECU by GIM data over Indian region.
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TL;DR: In this paper, a technique for retrieving the global distribution of vertical total electron content (TEC) from GPS-based measurements is described, based on interpolating TEC within triangular tiles that tessellate the ionosphere modeled as a thin spherical shell.
Abstract: A worldwide network of receivers tracking the transmissions of Global Positioning System (GPS) satellites represents a new source of ionospheric data that is globally distributed and continuously available. We describe a technique for retrieving the global distribution of vertical total electron content (TEC) from GPS-based measurements. The approach is based on interpolating TEC within triangular tiles that tessellate the ionosphere modeled as a thin spherical shell. The high spatial resolution of pixel-based methods, where widely separated regions can be retrieved independently of each other, is combined with the efficient retrieval of gradients characteristic of polynomial fitting. TEC predictions from climatological models are incorporated as simulated data to bridge significant gaps between measurements. Time sequences of global TEC maps are formed by incrementally updating the most recent retrieval with the newest data as it becomes available. This Kalman filtering approach smooths the maps in time, and provides time-resolved covariance information, useful for mapping the formal error of each global TEC retrieval. Preliminary comparisons with independent vertical TEC data, available from the TOPEX dual-frequency altimeter, suggest that the maps can accurately reproduce spatial and temporal ionospheric variations over latitudes ranging from equatorial to about ±65°.
1,148 citations
01 Jan 2009
TL;DR: In this paper, the authors describe the major effects of the ionosphere on GPS performance, including the following: 1) group delay of the signal modulation, or absolute range error, 2) carrier phase advance, or relative range error; 3) Doppler shift, or range-rate errors; 4) Faraday rotation of linearly polarized signals; 5) refraction or bending of the radio wave; 6) distortion of pulse waveforms; 7) signal amplitude fading or amplitude scintillation; and 8) phase scintillations.
Abstract: T HE ionosphere is an important source of range and range-rate errors for users of the global positioning system (GPS) satellites who require highaccuracy measurements. At times, the range errors of the troposphere and the ionosphere can be comparable, but the variability of the Earth's ionosphere is much larger than that of the troposphere, and it is more difficult to model. The ionospheric range error can vary from only a few meters, to many tens of meters at the zenith, whereas the tropospheric range error at the zenith is generally between two to three meters. Fortunately, the ionosphere is a dispersive medium; that is, the refractive index is a function of the operating frequency, and twofrequency GPS users can take advantage of this property of the ionosphere to measure and correct for the first-order ionospheric range and range-rate effects directly. Unlike the troposphere, the ionosphere can change rapidly in absolute value. Although the range error of the troposphere generally does not change by more than ±10%, even over long periods of time, the ionosphere frequently changes by at least one order of magnitude during the course of each day. The major effects the ionosphere can have on GPS are the following: 1) group delay of the signal modulation, or absolute range error; 2) carrier phase advance, or relative range error; 3) Doppler shift, or range-rate errors; 4) Faraday rotation of linearly polarized signals; 5) refraction or bending of the radio wave; 6) distortion of pulse waveforms; 7) signal amplitude fading or amplitude scintillation; and 8) phase scintillations. In order to understand the reasons for these potential effects on GPS performance, a brief description of the major characteristics of the ionosphere is necessary.
380 citations
"Modeling the Ionosphere Using Exten..." refers methods in this paper
...The NPIM data can replace GPS (Global Positioning System) [4], GIM (Global Ionosphere Maps) [5] and IRI (International Reference Ionosphere) Model [6] ionospheric data over Indian region, as all of these models utilize data from mid-latitude stations as against NPIM which uses the Indian stations (low latitude) data....
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TL;DR: In this paper, the authors presented the strategy and algorithms related to such a preliminary product, its calibration with synthetic observations generated from the International Reference Ionosphere (IRI), and the comparison with TOPEX TEC data.
331 citations
"Modeling the Ionosphere Using Exten..." refers methods in this paper
...Many approaches are made to map the global ionosphere using GPS (Global Positioning System) as in [7], [8] and [9]....
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Journal Article•
TL;DR: A novel algorithm has been designed and developed which will estimate the ionospheric delay, thereby providing ionsospheric corrections even at times of depletions, and is proposed to be implemented in IRNSS single frequency (L5/S) receivers.
Abstract: The IRNSS (Indian Regional Navigation System) navigation users estimate their position by using a receiver which receives the navigation signal from the IRNSS satellites which will be operating on L5 (1176.45MHz) and S (2492.028MHz) frequencies. There are 3 types of IRNSS users: 1) Dual frequency (L5 and S), 2) Single frequency (L5) and 3) Single frequency (S). The signal from the satellites before reaching the user receiver passes through the ionospheric layer of the atmosphere and suffers a delay. The delay in the signal introduces error in the position computed by the user. The dual frequency users of IRNSS correct the ionospheric error by taking advantage of the dispersive nature of ionosphere. On the other hand, single frequency user requisite an algorithm for computing the ionospheric delay along his line of sight. In IRNSS, the ionospheric error corrections for single frequency (L5 or S) users will be provided by two ways: 1) Grid based and 2) Coefficient based. These corrections may not be valid when an abnormal behavior of ionosphere occurs due to geomagnetic storm, solar coronal mass ejections or any other disturbances in the earth’s magnetic field. The abnormal behavior may result in increase or decrease of the TEC (Total Electron Content) in the ionosphere. Ionospheric depletion event is one such, where there is a sudden drop in TEC forming plasma bubbles travelling through the ionosphere. A user, whose line-of-sight when crosses such a TEC depleted area of ionosphere suffers from an extra error due to depletion. The amount of error is proportional to the depth of depletion. This error in the range ultimately results in the user position accuracy degradation. In this paper a novel algorithm has been designed and developed which will estimate the ionospheric delay, thereby providing ionospheric corrections even at times of depletions. The developed technique in turn provides achievable position accuracy during times of ionospheric depletions. The developed technique has been tested with GAGAN (GPS Aided GEO Augmented Navigation) INRES (Indian Reference Stations) data and IRNSS IRIMS (IRNSS Range and Integrity Monitoring Stations) data having deep ionospheric depletions. The fully tested and validated ionospheric delay estimation algorithm is proposed to be implemented in IRNSS single frequency (L5/S) receivers. Keywords: IRNSS Single Frequency User, Ionospheric Error, Ionospheric Depletion, Ionospheric Delay Estimation, Kalman Filter
8 citations
Additional excerpts
...Measuring Ionospheric error [3]...
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