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.
作者
刘玉柱
屈蔷
曹东
LIU Yuzhu;QU Qiang;CAO Dong(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《传感器与微系统》
CSCD
北大核心
2024年第7期161-164,共4页
Transducer and Microsystem Technologies
关键词
卡尔曼滤波
信息融合
多传感器
噪声估计
Kalman filtering
information fusion
multi-sensor
noise estimation
作者简介
刘玉柱(1994-),男,硕士研究生,研究方向为无人机导航制导;屈蔷(1977-),女,副教授,研究领域为无人飞行器飞行控制及导航、检测技术与自动化装置;曹东(1972-),男,副研究员,研究领域为无人飞行器飞行控制、嵌入式控制系统、检测技术与自动化装。
