基于改进卡尔曼滤波的多测温传感器数据融合方法分析  

Analysis of Data Fusion Method for Multiple Temperature Sensors Based on Improved Kalman Filtering

作　　者：李乐 李昂 阎毓杰[1] LI Le;LI Ang;YAN Yujie(Wuhan Second Ship Design and Research Institute,Hubei 430061,China)

机构地区：[1]武汉第二船舶设计研究所,湖北430061

出　　处：《电子技术（上海）》2024年第3期214-215,共2页Electronic Technology

摘　　要：阐述基于改进卡尔曼滤波的多测温传感器数据融合方法。在传统的卡尔曼滤波数据融合基础上,通过更新状态变量的协方差矩阵来改善卡尔曼滤波增益,动态估计出每一时刻各测温点的温度值。This paper expounds a data fusion method for multiple temperature sensors based on improved Kalman filtering.On the basis of traditional Kalman filtering data fusion,it improves the Kalman filtering gain by updating the covariance matrix of state variables,and dynamically estimates the temperature values of each temperature measurement point at each moment.

关 键 词：测温传感器 卡尔曼滤波 数据融合 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]