Research On Fusion Estimation Algorithm Of Multi-sensor And Its Application In Landslide

The landslide is a kind of natural disasters, which has a very great impact on human life. China’s annual economic losses caused by landslides is up to billions of dollars.At present, for landslide,we can only predict its development trend by arranging a number of monitoring points and using some data processing methods, but because of the existence of false noise in monitoring data, the traditional forecasting methods are generally not well to determine the landslide trends.For the above issue, in order to better remove the false noise, which influences the landslide forecast, and full use the monitoring data, this paper has studied the landslide forecast on two aspects,based on the in-depth study of the fusion estimation theory. On the one hand, the author has proposed the improved sequential dynamic weighted fusion method for the insufficient in the existing weighted fusion algorithm and applied this method to fuse the displacement data of more than one monitoring point for a specific instance; On the other hand, based on the classic Kalman filtering algorithm, the principle of centralized Kalman filtering algorithm,federal Kalman filtering algorithm and adaptive Kalman filtering algorithm has been studied at first,then landslide motion model is established,according to the landslide geological properties and dynamic principles. Finally, as the landslide for maneuvering targets, adaptive Kalman filtering algorithm has been used for the first time using for the displacement data fusion of multiple monitoring points in a specific instance.The results show that the fusion precision of the proposed dynamic sequential weighted fusion algorithm is higher than that of the existing weighted fusion algorithm; Through simulation,it indicates that the fusion precision of adaptive kalman filtering algorithm is higher than the centralized Kalman filtering algorithm and federal Kalman filtering algorithm;The example shows that not only the dynamic sequential weighted fusion algorithm and and adaptive kalman filtering fusion algorithm can both fuse the multi-point displacement data of landslide in some degree, but also can reflect the overall trend of landslide. Therefore, the results of this paper enrich the landslide forecast theoretical system.