Autonomous integrity monitoring method and device for receiver

Abstract

The invention provides an autonomous integrity monitoring method and device for a receiver. The method comprises the following steps: determining a coefficient observation matrix according to a pseudo-range observation equation of a receiver and a plurality of satellites; determining a pseudo-range residual vector and a weighted pseudo-range residual vector quadratic sum by adopting a preset weighted total least square method based on the coefficient observation matrix and the weighting matrix; and monitoring the autonomous integrity of the receiver according to the pseudo-range residual vector and the weighted pseudo-range residual vector quadratic sum. Because the preset algorithm comprises the weighted total least square method, the pseudo-range residual vector and the weighted pseudo-range residual vector quadratic sum are determined by adopting the preset algorithm based on the coefficient observation matrix and the weighting matrix, so that the ill-conditioned problem of the coefficient observation matrix can be solved, large fluctuation of the final calculation result caused by small fluctuation of the observed quantity is prevented, and the accuracy of autonomous integrity monitoring of the receiver is improved.

Description

technical field [0001] The present application relates to the field of satellite navigation, in particular to a method and device for autonomous integrity monitoring of a receiver. Background technique [0002] In the field of satellite navigation, Receiver Autonomous Integrity Monitoring (RAIM) is to use the receiver's own redundant observations to monitor and identify satellite faults, the purpose of which is to monitor the faulty satellites during navigation. , to eliminate faulty satellites, thereby improving navigation accuracy. [0003] Existing RAIM algorithms usually use the least squares residual method for fault monitoring and identification. However, the receiver autonomous integrity monitoring method based on the least squares residual method has an ill-conditioned coefficient matrix problem in satellite fault monitoring. The ill-conditioned coefficient matrix will cause large fluctuations in the final settlement results due to small fluctuations in the observed...

AI Technical Summary

Problems solved by technology

[0006] In the embodiment of the present application, by using the preset weighted total least squares method to determine the pseudorange residual vector and the sum of squares of the weighted pseudorange residual vector based on the coefficient observation matrix and weighting matrix, the ill-conditioned problem of the coefficient observation matrix can be solved , to prevent large fluctuations in the final solution results due to small fluctuations in the observed quantities, so that the calculated pseudorange residual vector and the weighted pseudorange residual vector sum of squares are more accurate, and then the pseudorange with higher precision can be used The residual vector and the weighted pseudorange residual vector square sum are used for receiver autonomous integrity monitoring, which effectively improves the accuracy of receiver autonomous integrity monitoring

Images