欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
风场信息是机载大气数据系统故障情况下重构大气数据的基础,飞机对所处的风场的感知对飞行器的安全飞行具有重要意义.目前机载风速测量通常是基于惯性导航系统或GPS提供的地速与大气数据系统提供的真空速计算法,由于真空速的测量滞后以及测量误差,直接计算的风速不能满足飞机使用要求.利用高空风场以水平风为主的大气特点,建立风场估计模型,以水平风速的东向及北向分量作为状态向量,以机载大气数据系统压力传感器提供的动压为量测量,通过构建扩展卡尔曼滤波器的方法实现外部风场的精确估算.在此基础上对虚拟大气数据系统提供的风场信息进行分析,验证此估计算法的可行性和有效性.仿真结果表明,该方法可获得较高的风速估算精度,并具有良好的稳定性,为飞机高空飞行提供精确的外部风场信息备份.
英文摘要：
Atmospheric data is reconstructed based on airborne wind field information under air data system fault conditions, in which the perception of wind farms is important for the safety of an aircraft in flight. Currently airborne wind speed measurement is usually calculated with ground speed provide by GPS or inertial system （INS）and true airspeed provide by air data system. The wind speed of direct calculation cannot meet the aircraft requirements because of true airspeed measurement lag and measurement error. In this paper,wind field estimation model is built considering that high altitude wind field is mainly constituted by horizontal wind. An extended Kalman filter （EKF） is constructed to achieve an accurate estimate of the external wind field information by taking the east and the north wind as the state vectors,the dynamic pressure provided by pressure sensors of airborne air data system as measurement. Wind field based on the virtual air data is used to validate the feasibility and effectiveness of the estimation method. Simulation results show that this method can obtain higher wind speed estimation accuracy and good stability, provide accurate external wind information to back up aircraft flight at high altitude.
同期刊论文项目
同项目期刊论文
Optical flow-aided navigation for UAV: A novel information fusion of integrated MEMS navigation syst
期刊信息
位置：