Research on Measurement Error Model of GNSS/INS Integration Based on Consistency Analysis

Abstract

Kalman filter is widely taken as an optimal fusion algorithm in GNSS/INS integration, and GNSS positioning error is often simply modeled as white noise in a loosely-coupled system. But many research results have shown that GNSS positioning error has the characteristic of temporal correlation. Correct error model of Kalman filter can ensure that the level of estimated accuracy is equal to that of actual accuracy. Inaccurate model will influence the consistency between estimated accuracy and actual integrated accuracy. Moreover, quality control method based on variance-covariance with inconsistency is not reliable and not utilized to detect gross errors. So, this paper mainly researches on GNSS positioning and velocity error model and its impact on quality control in GNSS/INS integration. In this paper, state-augmentation method is applied to solve the problems of GNSS colored noise to ensure the navigation accuracy consistency, and the rationality of the improved model is verified by the effect of quality control. Simulation and field test results show that state-augmentation method can improve the consistency between actual error and estimation standard deviation, and satisfy the requirement of quality control based on variance-covariance to improve the integration reliability.