第45卷第2期2024年2月仪器仪表学报ChineseJournalofScientificInstrumentVol.45No.2Feb.2024DOI:10.19650/j.cnki.cjsi.J2312280收稿日期:2023-12-15ReceivedDate:2023-12-15∗基金项目:中国高校产学研创新基金-无人集群协同智能项目(2021ZYB02002)资助基于改进ESKF的植保无人机时延位姿补偿算法∗刘慧,施志翔,沈亚运,储金城,沈跃(江苏大学电气信息工程学院镇江212013)摘要:为解决全球导航卫星系统和惯性测量单元融合时间不同步问题,提高植保无人机位姿估计精度,本文根据植保无人机大惯性、强振动的特性提出一种基于改进误差状态卡尔曼的时延位姿补偿算法。首先对名义状态变量线性预测,引入渐消因子提高强振动环境下的系统稳定性;接着采用互补滤波对角速度补偿,对姿态误差状态变量修正;最后结合测量的延迟时间,使用互补滤波外推数据,提高大惯性特性下的速度位置精度。实验结果表明,相较于误差状态卡尔曼算法,横滚角和俯仰角均方根误差减少0.2669°和0.2414°,偏航角均方根误差减少0.0764°;正常航迹植保作业下,东北天方向速度均方根误差减少0.2105、0.1849、0.2388m/s;东北天方向位置均方根误差分别减少0.21、0.19、0.23m,有效提高位姿估计精度。关键词:植保无人机;误差状态卡尔曼滤波;延时补偿;信息融合;组合导航中图分类号:TH391.4TH39文献标识码:A国家标准学科分类代码:520.60TimedelayandattitudecompensationalgorithmforplantprotectionUAVbasedontheimprovedESKFLiuHui,ShiZhixiang,ShenYayun,ChuJincheng,ShenYue(SchoolofElectricalandInformationEngineering,JiangsuUniversity,Zhenjiang212013,China)Abstract:TosolvetheproblemofglobalnavigationsatellitesystemsandinertialmeasurementunitfusiontimeasynchronousandimprovetheaccuracyofposeestimationofplantprotectionUAV,thisarticleproposesadelayposecompensationalgorithmbasedontheimprovederrorstateKalmanfilterbyusingthecharacteristicsoflargeinertiaandstrongvibrationofplantprotectionUAV.Firstly,thenominalstatevariablesarelinearlypredicted,andafadingfactorisintroducedtoimprovethesystemstabilityinstrongvibrationenvironments.Then,complementaryfilteringisusedtocompensatefordiagonalvelocityandcorrecttheattitudeerrorstatevariables.Finally,combinedwiththedelaytimemeasured,complementaryfilteringisusedtoextrapolatethedataandimprovetheveloci...
