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

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.