Micro-deformation prediction method, device, equipment and readable storage medium based on Beidou

Abstract

The present invention provides a Beidou-based micro-deformation prediction method, device, equipment and readable storage medium, which relate to the field of satellite monitoring technology, including obtaining a displacement data set, the displacement data set includes at least two sets of displacement data, and the displacement The data is the three-dimensional displacement of the target obtained by satellite measurement, and each of the displacement data in the displacement data set is calculated separately to obtain the displacement and deformation data of each of the displacement data; according to the displacement and deformation data, Establish a prediction model, and calculate the displacement prediction result of the target at the third moment relative to the second moment through the prediction model; predict the future deformation trend of the monitoring object, which can be applied to the monitoring of geological disasters, buildings, bridges and other fields and early warning; the prediction accuracy is improved, and the limitation that the traditional single displacement and deformation prediction model cannot accurately describe the deformation and evolution law is solved.

Description

technical field [0001] The present invention relates to the technical field of satellite monitoring, in particular to a Beidou-based micro-deformation prediction method, device, equipment and readable storage medium. Background technique [0002] At present, the prediction model based on displacement deformation usually adopts nonlinear prediction method, and the commonly used classic models mainly include time series analysis, gray GM (1,1) prediction model, Kalman filter, regression analysis model, support vector machine, artificial neural Network, etc. In addition, prediction research on mixed models is also a popular method at present. [0003] However, the current displacement and deformation monitoring and early warning systems are often only aimed at a certain object or a certain type of scene. The system’s versatility is not strong, and the ability to deal with sudden changes is weak. high. [0004] Due to the complexity of displacement and deformation in various a...

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Problems solved by technology

[0003] However, the current displacement and deformation monitoring and early warning systems are often only aimed at a certain object or a certain type of scene. The system’s versatility is not strong, and the ability to deal with sudden changes is weak. high

[0004] Due to the complexity of displacement and deformation in various application environments, it is difficult to accurately predict the displacement and evolution process of the monitoring body only through a single model, and in the actual data collection process, the collected data is often affected by noise and interference in the system , the data may also be affected by special circumstances and cause missing situations

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