Saastamoinen model-based BP nerve network troposphere delay correction method
A BP neural network and tropospheric delay technology, which is applied in the field of global navigation systems, can solve problems such as low model accuracy, poor model accuracy, and systematic deviation of the Saastamoinen model, and achieve the effect of high model accuracy and elimination of systematic deviation
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[0033] The technical solution of the present invention will be further introduced below in combination with specific embodiments.
[0034] The invention discloses a BP neural network tropospheric delay correction method based on the Saastamoinen model, comprising the following steps:
[0035] S1: According to the Saastamoinen model, calculate the tropospheric wet delay value ZWD at the station SAAS , as shown in formula (1);
[0036]
[0037] in, for:
[0038]
[0039] S2: Establish a BP neural network representing the wet delay at the station, such as figure 1 As shown, the BP neural network is used to represent the nonlinear relationship between the wet delay of the station and the meteorological parameters and the wet delay of the Saastamoinen model, as follows:
[0040] The input parameters of the BP neural network are surface meteorological parameters and the wet delay calculation value ZWD of the Saastamoinen model SAAS , where the surface meteorological para...
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