REAL-TIME ESTIMATION OF IONOSPHERIC DELAY USING DUAL FREQUENCY GPS OBSERVATIONS

Abstract

The Global Navigation Satellite System (GNSS) is a space-based radio positioning system that includes one or more satellite constellations capable of providing three-dimensional position, velocity and time information continuously to users anywhere on, or near, the surface of the earth. The Global Positioning System (GPS) is the most well known GNSS and is operated by the U.S. Department of Defense. A GPS receiver uses two types of measurements, viz. code and carrier phase for determining its (user) position. The positional accuracy of GNSS is limited by several sources of error such as satellite and receiver clock offsets, signal propagation delays due to ionosphere and troposphere, multipath, receiver measurement noise and instrumental biases. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS measurements. In this paper, two prominent ionospheric delay smoothing algorithms, viz. combined code and carrier smoothing filter (CCCSF) and Hatch smoothing filter (HSF) are compared for reducing the effect of code measurement noise and multipath. The smoothing results are validated with the Bernese GPS data processing software. The estimated TEC results after correction of various errors and biases are presented for various GAGAN stations. The work presented is useful for accurate ionospheric modeling required for communication, navigation and surveillance (CNS) systems in India.