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Regional ionospheric model response of geomagnetic storm during March 2015 using data fusion mechanism: GPS, COSMIC RO and SWARM

Emmela Suneetha, Ratnam Devanaboyina Venkata

Acta Geophysica

2023

Vol. 71, no. 1

553--566

The total electron content (TEC) maps are chosen as the elementary structures to provide ionospheric corrections for improving the positional accuracy for Global Navigational Satellite Systems (GNSS) users. Availability of total electron content data from a multi-constellation of satellite systems and various ground-based instruments possess an ability to monitor, nowcast and forecast the behavior of the ionosphere region. Conversely, combining ionospheric TEC data from different temporal and spatial scales is a difficult task to augment either ground or space-based ionospheric model's accuracy. And hence, a method like data fusion is essential to illustrate the ionospheric variability and to improve the accuracy of ionospheric models under equatorial ionization anomaly (EIA) conditions. This paper presented the weighted least square data fusion method with multi-instrument TEC data to analyze the EIA TEC structures in the low-latitude Indian region. Both ground-based (GPS TEC from 26 stations in the Indian region) and space-based (FORMOSAT-3/COSMIC RO and SWARM mini satellite constellation) observations are used for the analysis. The spherical harmonic function (SHF) model of order 2, which gives nine SHF coefficients, is implemented. The analysis illustrates that the SHF coefficients followed by TEC data fusion would be useful to investigate the entry, occupancy and exit TEC structures of EIA during geomagnetic storm conditions.

Problems in Modelling Charge Output Accelerometers

Tomczyk K.

Metrology and Measurement Systems

2016

Vol. 23, nr 4

645--659

The paper presents major issues associated with the problem of modelling change output accelerometers. The presented solutions are based on the weighted least squares (WLS) method using transformation of the complex frequency response of the sensors. The main assumptions of the WLS method and a mathematical model of charge output accelerometers are presented in first two sections of this paper. In the next sections applying the WLS method to estimation of the accelerometer model parameters is discussed and the associated uncertainties are determined. Finally, the results of modelling a PCB357B73 charge output accelerometer are analysed in the last section of this paper. All calculations were executed using the MathCad software program. The main stages of these calculations are presented in Appendices A−E.