Research Of Multipath Error Mitigation In GNSS Multiple System Dynamic Deformation Monitoring

In order to understand and control the deformation conditions timely in building structures construction and operation management.It is necessary to find effective methods for deformation monitoring.With the modernization of GPS(Global Positioning System).BDS(BeiDou Navigation Satellite System)and GLONASS(Global Navigation Satellite System,GLONASS)also made their own development plans.The combinations of GNSS(Global Navigation Satellite System)multiple systems were widely used in deformation information because of the advantages such as all-weather,high accuracy,neglect of shade.Compared to the poor number of single system,multiple systems have the enough number and geometry of the satellites.As for one of the main error in short distance which called multipath error,there is no improvement in it.Therefore,it is of great significance to improve the accuracy of deformation monitoring results by exploring ways to weaken the multipath error of GNSS.This paper mainly studies from the following aspects.(1)First of all,study the principle of multipath error,then calculate the functional relationship between multipath error and reflection distance Finally this chapter draw a conclusion that multipath error can be ignored when the reflection distance is more than 50 meters.Secondly,prove that multipath has the characteristic of low frequency by means of fourier transform.Then calculate and prove the diurnal repeatability by broadcast and correlation coefficient,and found that the latter is better than the former.Finally make a conclusion that sidereal filtering is not suitable for single system,it is necessary to find a new way to mitigate the multipath error of GNSS.(2)A new method called IEEMD(improved ensemble empirical mode decomposition)was introduced to build the correction of multipath error in this article.Compared to EEMD(ensemble empirical mode decomposition),the new method can effectively solve the problem of model mixing and incomplete decomposition.It can also decompose the original coordinate sequence into different scales of modal components.The product of Gaussian white noise energy density and the average period is constant.Taking this condition into account,a new method was designed of automatic selection for scale and reconstruction to build the model of multipath error.Use it to correct the later coordinate series by the first day's multipath model by the reason of the strong correlation between two successive days.The experiment results show that IEEMD can get more accurate coordinate sequence than EEMD based on the same way of scale selection and sidereal filtering To a certain extent,solidified the theoretical basis of GPS high-precision real-time dynamic deformation monitoring.(3)It is almost impossible to mitigate the multipath error because of the combinations of GNSS multiple system.We put forward an idea creatively which inspired by machine learning.Using neural network to study the law of multipath error and build the model in GNSS dynamic deformation monitoring.So as to verify the correctness of this idea,three different experiments were conducted based on BP neural work in this chapter.The first experiment shows that the best improvement of this method can reach 51.18%in GNSS three-system.In the second experiment we can see this method could achieve the same effect as the sidereal filtering in GPS dynamic deformation monitoring.Thirdly in order to verify the effect of this method in any system combination,we select deformation monitoring data of different system.The final experiment shows that the best improvement of this method can reach 39.58%in any combinations of GNSS.