A method for improving the accuracy of tropospheric zenith delay estimation

CN116010767BActive Publication Date: 2026-07-07CHINA PETROLEUM & CHEMICAL CORP +2

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: CHINA PETROLEUM & CHEMICAL CORP
Filing Date: 2021-10-22
Publication Date: 2026-07-07

AI Technical Summary

Technical Problem

In existing technologies, tropospheric zenith delay models based on measured meteorological parameters cannot be widely used when meteorological parameters cannot be obtained in real time, and the accuracy of empirical models has limited room for improvement, which affects the accuracy and efficiency of GNSS positioning.

Method used

Based on the GPT2w model, a residual periodic model considering annual, semi-annual, and seasonal periodic terms was constructed by combining millimeter-level tropospheric zenith delay data obtained from GNSS measured signals with the Saastamoinen and Askne and Nordius models. Model error compensation was performed to establish a high-precision empirical model of tropospheric zenith delay for a single site.

Benefits of technology

It improves the accuracy of tropospheric zenith delay estimation, enhances the reliability of empirical models, improves GNSS positioning accuracy, especially in the elevation direction, and reduces the convergence time of tropospheric delay during positioning.

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Abstract

The application provides a method for improving the estimation accuracy of tropospheric zenith delay, and belongs to the technical field of navigation and positioning. The technical scheme is as follows: a method for improving the estimation accuracy of tropospheric zenith delay, comprising the following steps: calculating the result of a GNSS measured signal as a reference value of the tropospheric zenith delay, denoted as ZTD GNSS ; estimating the tropospheric zenith delay ZTD GPT2w based on a GPT2w model; calculating the residual dZTD of the tropospheric zenith delay according to existing site data; constructing a residual period model dZTD model considering the annual, semiannual and seasonal period terms after analyzing the periodic signal in the residual sequence of the tropospheric zenith delay; and constructing an empirical improvement model ZTD model of the tropospheric zenith delay: ZTD model = ZTD GPT2w + dZTD model The application has the beneficial effects that the calculation accuracy is effectively improved compared with the GPT2w model, the positioning efficiency is improved, and the convergence time caused by the estimation of the tropospheric delay in the positioning process is effectively reduced.

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