Nonlinear Unequal Precision Data Fusion Method Based on Clustering Algorithm

Multisource information fusion is a multilevel and multifaceted processing process, including the detection, correlation, combination and estimation of multisource data, so as to improve the accuracy of status and identity estimation. Because of its high detection accuracy, it has the advantages of good expansibility, high reliability, low cost of obtaining information, and is widely used in modern military and various civilian fields. In many applications, it has played a good role in promoting the development of modern science and technology and the improvement of people’s lives. In many fields, the multi-source information fusion theory plays an obvious role in the estimation of maneuvering target state in the military background. Based on the theory of multisource information fusion and navigation information data, this paper develops a nonlinear data fusion method with unequal accuracy based on clustering algorithm to improve navigation and positioning accuracy. The method of clustering fusion after weighted multi-source data is used to improve the data accuracy, and then the navigation and timing accuracy is improved.