改进的多传感器信息融合算法及其应用  

Improved multi-sensor information fusion algorithm and its application

作　　者：刘玉柱 屈蔷[1] 曹东[1] LIU Yuzhu;QU Qiang;CAO Dong(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京211106

出　　处：《传感器与微系统》2024年第7期161-164,共4页Transducer and Microsystem Technologies

摘　　要：针对量测噪声未知的问题,提出一种改进的多传感器信息融合方法,首先对量测噪声进行实时跟踪与估计,接着基于估计的量测噪声进行最优加权融合,解决常规加权法权值不是最优的问题,最后将融合的结果进行卡尔曼滤波,得到系统的状态估计。将改进的多传感器信息融合方法应用某型无人机(UAV)垂向高度信息融合系统中,经仿真验证,表明该方法具有一定的工程实用价值。Aiming at the problem that the measurement noise is unknown,an improved mul-ti-sensor information fusion method is proposed.Firstly,the measurement noise is tracked and estimated in real-time.Then,the measurement noise based on the estimation is optimally weighted and fused to solve the problem that the weight value of the conventional weighting method is not optimum.Finally,the fusion result is Kalman filtered carried out to obtain the state esti-mation of the system.The improved multi-sensor information fusion method is applied to the vertical altitude information fusion system of a UAV.The simulation results show that the me-thod has certain practical value in engineering.

关 键 词：卡尔曼滤波 信息融合 多传感器 噪声估计 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]