Deformation monitoring positioning method and device based on carrier wave phase difference static and dynamic state fusion

Abstract

The invention provides a deformation monitoring positioning method based on carrier wave phase difference static and dynamic state fusion; the method comprises the following steps: receiving GNSS observation data of a monitoring station and a reference station, making station-star double-difference for carrier wave phase in the observation data so as to form a non-rank defect equation set, using an extended Kalman algorithm to carry out iterative solution according to the least square idea, thus obtaining a floating point position solution of the monitoring station; if a fuzziness integer value is searched by an LAMBDA/MLAMBDA algorithm, a fixed position solution of the monitoring station can be finally obtained. The method periodically adjusts a time update process in the extended Kalmanfiltering algorithm, fuses advantages of a dynamic mode and a static mode of the carrier wave phase difference algorithm, thus ensuring precision deformation monitoring sensitivity and high precisionrequirements. The method can improve the horizontal positioning precision up to 3mm, and can improve the elevation positioning precision up to 5mm; compared with a conventional carrier wave phase difference static state mode method, the method can effectively ensure the monitoring sensitivity, thus keeping the deformation reaction time within a required scope.

Description

technical field [0001] The invention belongs to the technical field of satellite navigation and positioning, and in particular relates to a deformation monitoring and positioning method and device based on dynamic and static fusion of carrier phase difference. Background technique [0002] Global Navigation Satellite System (GNSS, Global Navigation Satellite System) high-precision differential positioning technology has been widely used in high-precision monitoring fields such as dam deformation monitoring, landslides and land subsidence. With the development of China's Beidou satellite system, satellite positioning technologies based on Beidou and GPS have been widely used in various production fields, and have the characteristics of high precision, good continuity, all-weather, and real-time performance, and have become the main monitoring means today. The high-precision positioning technology currently used in the field of high-precision deformation monitoring is carrier ...

AI Technical Summary

Problems solved by technology

In the field of precision deformation monitoring, especially in slope deformation monitoring, settlement monitoring, etc., the traditional carrier phase difference positioning method still has shortcomings: the dynamic mode method is due to the location part of the state matrix and its covariance matrix in the extended Kalman filter Each epoch must be initialized, and the filtering and iterative smoothing cannot be performed continuously, which leads to the reduction of the positioning accuracy of the solution while ensuring the sensitivity, so that the positioning accuracy is only at the centimeter level, which cannot meet the needs of precise monitoring; the static mode only The position part of the solution state matrix and its covariance matrix is ​​initialized in the first epoch. After continuous iterations in non-first epochs, the positioning accuracy is high but the sensitivity is poor, which cannot be used in precision deformation monitoring and other fields.

In order to solve the problem of poor applicability of high-precision positioning methods in the field of precision deformation monitoring, two solutions are currently used: 1. Using carrier phase difference dynamic mode plus smoothing algorithm, this processing method can improve positioning accuracy, but the accuracy is difficult to achieve Millimeter level, it is difficult to meet the requirements of settlement monitoring, and the sensitivity of the algorithm will also be reduced due to the smoothing algorithm; 2. The periodic static solution method is adopted. This method uses periodic post-event static processing, which can effectively guarantee the accuracy and sensitivity, but requires manual work. Periodic operation, resulting in greatly reduced automation level of the monitoring system

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