GNSS random model building method considering troposphere residual delay

Abstract

The invention discloses a GNSS random model establishing method considering tropospheric residual delay, and belongs to the field of satellite navigation and positioning. The propagation distance of asatellite signal in the troposphere is calculated through a satellite elevation angle and zenith troposphere thickness; a zenith mapping function is given to calculate tropospheric residual delay, then tropospheric residual delay is brought into a random model to give a method for calculating satellite observation value variance, the characteristics of unmodeled errors are effectively reflected,and precision and reliability of precision single-point positioning can be improved. The method specifically comprises the following steps: (1) determining the troposphere thickness H in the zenith direction according to the position of an observation station, and obtaining a satellite elevation angle E; (2) calculating a propagation distance S of the satellite in a troposphere; (3) calculating aspecific value k of the zenith mapping function; (4) determining the tropospheric residual delay amount; and (5) determining the variance of the satellite according to the tropospheric residual delay.

Description

technical field [0001] The invention belongs to the field of satellite navigation and positioning, relates to the problem of satellite positioning accuracy, and mainly solves the problem of reasonably weakening the influence of tropospheric residual delay in satellite observation values ​​on the positioning accuracy. Background technique [0002] Precise point positioning (PPP) integrates the technical advantages of standard single point positioning and relative positioning, and achieves centimeter-level or even millimeter-level positioning accuracy, and has been widely used in many fields. Since the calculation accuracy of the satellite has a strict mathematical relationship with the stochastic model, determining a reasonable stochastic model for the observations can effectively reduce the influence of various system residual errors and improve the positioning accuracy. [0003] Commonly used stochastic models mainly include equal weight model, height angle fixed weight mod...

AI Technical Summary

Problems solved by technology

In view of the deficiencies in the prior art, the present invention provides a GNSS stochastic model establishment method that takes into account the residual delay of the troposphere to solve the problem that the existing random model cannot reflect the residual delay of the troposphere and the accuracy of the observation value in precise point positioning.

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