气动模型及导航信息辅助的大气参数估计方法

Air data estimation method aided by aerodynamic model and navigation information

针对无初始风速信息情况下的虚拟大气数据计算问题,提出一种气动模型及导航信息辅助的大气参数粗精两级估计方法.利用飞行器气动模型下的动力学方程,建立与风速直接相关的导航传感器测量模型;采用非线性最小二乘优化方法对风速进行一级估计,并作为滤波初始值;利用扩展卡尔曼滤波,对风速进行二级估计,进而实现大气参数的实时精确估计.实验结果表明,所提方法具有较高的收敛速度和估计精度,可提高大气数据系统的测量范围和可靠性,适用于全飞行包线下攻角、侧滑角、真空速的测量.

Aiming at virtual air data estimation without initial wind velocity, a two-step air data estimation method aided by the aerodynamic model and navigation information is proposed. On the foundation of dynamic equations with the aerodynamic model, the measuring model of navigation sensors directly relate to wind speed is established. The nonlinear least squares optimization algorithm is used to estimate the wind speed roughly, and take the estimation as initial value.The precise estimate of wind speed is achieved with the extended Kalman filter（EKF）. Based on the wind estimation, the real-time and high accuracy estimation of air data is realized. The simulation results show that, this algorithm has higher convergence speed and estimation accuracy, and improves the air data system＇s measurement range and reliability, which can apply to the measuring of true air speed, angle of attack and sideslip within full flight envelope.