巡飞弹空中自适应快速初始姿态估计  

Adaptive fast initial attitude estimation for inflight loitering munition

作　　者：李增彦[1,2] 李小民[1] 刘秋生[3] 周兆英[2] LI Zeng-yan LI Xiao-min LIU Qiu-sheng ZHOU Zhao-ying(Department of UA V Engineering, Ordnance Engineering College, Shijiazhuang 050003, China Department of Ammunition Engineering, Ordnance Engineering College, Shijiazhuang 050003, China Department of Precision Instrument, Tsinghua University, Beijing 100084, China)

机构地区：[1]军械工程学院无人机工程系,河北石家庄050003 [2]清华大学精密仪器系,北京100084 [3]军械工程学院弹药工程系,河北石家庄050003

出　　处：《光学精密工程》2017年第2期493-501,共9页Optics and Precision Engineering

基　　金：武器装备"十二五"预先研究项目(No.51325050101)

摘　　要：为了解决巡飞弹空中上电后在无参考姿态条件下的初始姿态确定问题,采用低成本磁力计、陀螺仪和加速度计(MARG)传感器设计姿态航向参考系统(AHRS),并提出了一种自适应参考矢量权重的快速初始姿态估计(AFCF)算法。首先,提出了三轴传感器使用前的快速误差校准方法;然后,采用快速互补滤波算法进行姿态估计,分析了其权重函数对于初始姿态估计及收敛性等的影响;接着,提出自适应参考矢量权重及自适应姿态估计方法;最后,利用高精度MTI(Milliren Technologies,Inc)传感器数据对算法进行了验证,并在低成本MARG姿态航向参考系统中对算法进行了实现,对比了改进算法及扩展卡尔曼滤波(EKF)算法的性能。实验结果与分析表明:动态条件下采用MTI传感器数据,改进算法能够在初始时刻收敛,比快速互补滤波(FCF)算法提前约4s;解算精度约为±0.6°,初始时刻精度明显优于FCF;硬件测试则表明改进算法的处理时间为0.062ms,仅为EKF算法的1/9,解算精度约为±1.3°,能够满足姿态测量过程快速收敛、高精度、实时性等要求。To solve the problem of initial attitude estimation for inflight loitering munition in the absence of reference attitude,a fast initial attitude estimation algorithm for adaptive reference vector weight（AFCF）was put forward based on the Attitude and Heading Reference System（AHRS）designed by adopting low-cost magnetic,angular rate and gravity MARG sensor.First of all,a fast error calibration method for three-axes sensor was put forward;Then,the attitude estimation was carried out by adopting the fast complementary filtering algorithm,and the impact of weighting function oninitial attitude estimation and convergence was analyzed;subsequently the method for adaptive reference vector weight and adaptive attitude estimation was proposed;finally,high-precision MTI sensor data was used to verify the algorithm,then the algorithm was implemented in the low-cost MRAG AHRS,and performance of the improved algorithm was compared with that of the extended Kalman filter（EKF）algorithm.The experiment results and analysis show that the improved algorithm can achieve a convergence at the initial time when MTI sensor data is used under dynamic conditions,approximately 4searlier than the fast complement filter（FCF）algorithm;the calculation precision is±0.6°,and the initial precision is obviously better than FCF.Furthermore,the hardware test indicates that processing time for the improved algorithm is 0.062 ms,accounting for 1/9of the EKF algorithm,with an approximately calculation precision of±1.3°,which can meet the requirement of fast convergence,high precision and real-time during the attitude measurement.

关 键 词：巡飞弹 初始姿态估计 互补滤波 最优矢量估计 

分 类 号：V249[航空宇航科学与技术—飞行器设计]