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 conjunction with specific embodiments.
[0034] The invention discloses a BP neural network tropospheric delay correction method based on the Saastamoinen model, which includes 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] among them, 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 express the non-linear relationship between station wet delay and meteorological parameters and Saastamoinen model wet delay, as follows:
[0040] The input parameters of the BP neural network are ground meteorological parameters and the wet delay calculated value ZWD of the Saastamoinen model SAAS , Where the ground meteorological parameters include atmospheric pressure P ...
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