Simulation Analysis of Multi-source Measurement Data Fusion Based on EMBET

Abstract

Error model best trajectory estimation method (EMBET) is often used in the fusion processing of multi-source measurement data to improve the accuracy of multi-source heterogeneous measurement data fusion processing. Because the classic multi-source measurement data fusion method based on the principle of EMBET requires high non-relevance and stability of the measurement data, the application range of this method is largely limited. Based on the principle of the classic EMBET method, this paper proposes a multivariate measurement data fusion method based on principal component estimation, which greatly improves the accuracy of data fusion in the case of strong correlation of measurement data and poor data stability. The effectiveness of this method is verified by measured data.