六旋翼无人机航磁补偿方法研究  

On Aeromagnetic Compensation of Hexacopter UAVs

作　　者：于龙兴 魏媛媛 付世沫 常青[1] 王耀力[1] YU Longxing;WEI Yuanyuan;FU Shimo;CHANG Qing;WANG Yaoli(College of Electronic Information and Optical Engineering Taiyuan University of Technology,Jinzhong 030000 China;Taiyuan Water Supply Design&Research Institute Co.Ltd.,Taiyuan 030000 China)

机构地区：[1]太原理工大学电子信息与光学工程学院,山西晋中030000 [2]太原供水设计研究院有限公司,太原030000

出　　处：《电光与控制》2025年第2期38-44,共7页Electronics Optics & Control

基　　金：山西省项目(201903D321003);山西省自然科学基金(201801D121141);太原供水设计研究院有限公司项目(RH2000005391)。

摘　　要：地磁导航作为一种无源自主导航方法,与全球定位系统(GPS)相比具有更强的稳定性。为了提高无人机(UAV)平台地磁导航的精确性,需要补偿无人机平台产生的固定干扰、涡流干扰、感应干扰。根据实测六旋翼无人机磁场数据,分析出无人机作业时干扰信号的频率特性;结合传统的Tolles-Lawson模型与卡尔曼滤波算法预测地磁场的变化,去除了传统Tolles-Lawson模型中恒定地磁场的假设;引入遗忘因子α,根据残差理论减小观测协方差误差与状态协方差误差来实现噪声预测,改进卡尔曼滤波。经过实验分析可得,改进自适应卡尔曼滤波有效地降低了补偿误差,较普通卡尔曼滤波补偿效果改善比(IR)提高了5.64,且补偿后磁场数据的噪声毛刺明显减少。As a passive autonomous navigation method,geomagnetic navigation has stronger stability than the Global Positioning System(GPS).To improve the accuracy of geomagnetic navigation of the UAV platform it is needed to compensate for the fixed field interference eddy current interference and induction interference generated by the UAV platform.Based on the measured UAV magnetic field data the frequency characteristics of the interference signal during UAV operation are analyzed.Combining the traditional Tolles-Lawson model and Kalman filter algorithm to predict the change of geomagnetic field and the assumption of constant geomagnetic field in the traditional Tolles-Lawson model is removed.The forgetting factorαis introduced to reduce the noise of observation covariance error and state covariance error according to the residual theory realize noise prediction and improve the Kalman filter.The experimental analysis shows that the improved adaptive Kalman filter effectively reduces the compensation error and the compensation effect Improvement Ratio(IR)is 5.64 higher than that of the ordinary Kalman filter and the magnetic field noise glitch in the compensated magnetic field data is significantly reduced.

关 键 词：无人机 Tolles-Lawson模型 遗忘因子 自适应卡尔曼滤波 

分 类 号：V243.5[航空宇航科学与技术—飞行器设计]