A single station ionospheric empirical model using GPS-TEC observations based on nonlinear least square estimation method

Fixed-frequency monitoring and early warning technology of machine-card separation based on improved least square method

“…To realize the efficient monitoring and early warning of the separation of machine and card, this paper fits the early warning function of the separation of machine and card in the fixed frequency environment under the monitoring protocol [10]. In this paper, through the monitoring protocol, it is preliminarily determined that the early warning function curve of machine-card separation is a combination of a straight line and a quadratic curve, and the early warning function is determined as follows:…”

“…In the formula (4-6), ( ) f x is the early warning function of the machine-card separation under the condition of straight line; ( )' f x is the early warning function of the machine-card separation under the condition of quadratic curve; a , b , and c are linear fitting parameters [10]. The warning function is improved by the least square method, and the following results are obtained:…”

Comparison of the Performance of the Regression Models in GPS-Total Electron Content Prediction

“…The models are based on the ionospheric maps or TEC data obtained from GNSS. In [7], the nonlinear least square estimation technique is used to allow the TEC modelling for a single-station. In the literature, several studies have focused on comprehension of storm-time behavior of the ionosphere to reduce the influence of ionospheric anomalies and irregularities on global positioning services and to advance the performance of the ionospheric models during the major geomagnetic storms [8,9,10,11].…”