多传感器融合状态估计方法综述

With the development of sensor network technology, multisensor state estimation has received extensive attention from scholars around the world due to its advantages of robustness, flexibility, scalability, fault detection ability. The method of data fusion lays a theoretical foundation for distributed state estimation and is also the main direction of early research. From 1970s to the end of the 20th century, centralized and decentralized filtering architectures and corresponding algorithms were successively developed. The maturity of wireless communication technology and the emergence of consensus algorithms have brought the research of distributed state estimation into the fast lane. Since 2005, a large number of distributed filtering algorithms based on consensus have been proposed, among which there are many practical classical methods and excellent pioneering methods. This paper aims to review the development of multisensor data fusion state estimation, explore the internal connection from data fusion to distributed filtering, and provide insights into the development of distributed state estimation. Some classical methods are summarized.