火力与指挥控制2024，Vol.49Issue(7)：36-43,8.DOI:10.3969/j.issn.1002-0640.2024.07.006
基于多级MEKF的微型无人机状态估计
Multi-level MEKF-based State Estimation of Micro-UAVs
摘要
Abstract
Aiming at the problem that it is difficult for conventional algorithms to ensure the accu-racy and real-time of UAV state information resolution as the low cost inertial measurement units are in poor accuracy and weak in stability when micro-UAVs operate in when GPS-denied environment.A multi-level multiplicative extended Kalman filter(MEKF)state estimation algorithm based on the fu-sion of IMU and optical flow sensors is proposed.Firstly,the magnetometer,gyroscope and accelerome-ter data are fused to achieve attitude estimation;secondly,the attitude estimation,acceleration and opti-cal flow data are used to achieve the velocity estimation;finally,the integral of the velocity estimation is fused with the altitude data to achieve position estimation.The experiment results show that the algo-rithm achieves faster and more reliable state estimation than that of the traditional algorithms.关键词
微型无人机/光流传感器/乘性扩展卡尔曼滤波/状态估计Key words
micro-UAVs/optical flow sensor/multiplicative extended Kalman filter/state estimation分类
航空航天引用本文复制引用
刘砚菊,李景泉,冯迎宾..基于多级MEKF的微型无人机状态估计[J].火力与指挥控制,2024,49(7):36-43,8.基金项目
辽宁省基本科研基金资助项目(LJKMZ20220614) （LJKMZ20220614）
