Research on Multi-source Data Fusion Method Based on Bayesian Estimation

As a framework for data fusion, it is a source of information through a combination of appropriate methods to get a more satisfactory result, mainly detection, estimation of multiple sources of data, and the combination treatment. Because the measurement data from multiple sources always have some degree of uncertainty and inconsistency, using multi source data fusion algorithm for the measurement data of multiple nodes for data fusion, using data redundancy to reduce this uncertainty, high reliability data. In this paper, the Bayesian estimation method is used to deal with multi-source data. It is proved by experiments that the algorithm is effective for the fusion of multi-source data and the inconsistency of the data.