水利信息化Issue(2)：73-77,5.DOI:10.19364/j.1674-9405.2026.02.011
基于动态方差卡尔曼滤波的高洪期河流流量监测研究
Research on river flow monitoring during high flood period based on dynamic variance Kalman filtering
赵亮1
作者信息
- 1. 颍上县应急管理局,安徽阜阳 236200
- 折叠
摘要
Abstract
To address the problems of low accuracy and weak anti-interference ability of traditional river flow monitoring methods during the high flood period,high-definition cameras were used to non-contact collect river surface images.The Sobel algorithm was applied to extract water level lines,and the optical flow method was employed to analyze the spatiotemporal motion characteristics of water surface pixels.Optical flow vectors were converted into actual flow velocities to achieve local velocity estimation.A state-space model was constructed with flow rate and water level as state variables,and regional flow velocity and water level as observations,incorporating a dynamic noise covariance online update mechanism.River flow was estimated by integrating multi-source observation data with iterative Kalman filtering operations.Experimental results showed that when the proposed method was applied to river flow monitoring during high flood period,the drift accumulation rate remained stable below 1.5％,enabling full-process optimization from water level extraction and local velocity estimation to global flow inversion.The application of the dynamic variance Kalman filtering algorithm effectively enhances the accuracy and stability of flow monitoring,providing a new and effective approach for river flow monitoring during high flood period.关键词
动态方差卡尔曼滤波/高洪期/流量监测/光流法Key words
dynamic variance Kalman filtering/high flood period/flow monitoring/optical flow method分类
信息技术与安全科学引用本文复制引用
赵亮..基于动态方差卡尔曼滤波的高洪期河流流量监测研究[J].水利信息化,2026,(2):73-77,5.
