摘要
针对传统导航系统易受攻击和诱导的问题,设计了一种太阳偏振光辅助的无人机航姿优化解算方法。该方法基于微惯性器件、偏振光传感器,构建状态阈值改进的共轭梯度优化的姿态解算模型,模型以无约束梯度优化理论为依据,使用四元数更新姿态,创建动态步长因子,获取姿态的变化趋势。实验证明,该方法静态性能稳定,动态环境中,该方法姿态估计值与各种滤波融合方法相比精度相似甚至较高,同时对于非重力加速度与其他方法比具有良好抑制作用。
To solve the problem that the traditional navigation system is vulnerable to be attacked and guided,a solar polarized light assisted attitude optimization method for UAV is designed.Based on the mi-cro inertial device and polarized light sensor,the attitude solution model of conjugate gradient optimization with improved state threshold is constructed.Based on the unconstrained gradient optimization theory,the model updates the attitude with quaternion,creates a dynamic step factor,and obtains the change trend of attitude.Experiments show that the static performance of this method is stable.In the dynamic environ-ment,the attitude estimation accuracy of this method is similar or even higher than that of various filter fu-sion methods.At the same time,it has a good inhibitory effect on no gravity acceleration compared with other methods.
作者
金仁成
孙庆飞
刘忱
黄启鹏
JIN Ren-cheng;SUN Qing-fei;LIU Chen;HUANG Qi-peng(School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,Liaoning Province,China)
出处
《信息技术》
2023年第6期1-7,12,共8页
Information Technology
基金
国家自然科学基金青年科学基金(51505062)
中央高校基本科研业务费专项基金(DUT19LAB11)。
关键词
太阳偏振光
MIMU
航姿解算
共轭梯度
状态因子
solar polarized light
MIMU
navigation position calculating
conjugate gradient
form factor
