摘要
提出一种有效的实时纵向飞行轨迹重构的新方法。为了得到状态估计的快速算法,本文把非线性飞行轨迹重构转化为线性、离散、时变状态和参数估计问题。将数值稳定性好、计算量也小的序列U-D分解滤波算法用于状态方程为线性、观测方程为线性或非线性的滤波问题中。由于测量值中常常含有系统偏差,本文把这些偏差作为增广状态加入增广状态模型中,并利用模型的一些特点,提出偏差分离的U-D分解算法,使计算量大大减少。仿真和实际试飞数据计算表明、本文的方法可得到比平方根协方差滤波更有效的实时飞行轨迹重构结果。
A new efficient real- time flight path reconstruction method of the longitudinal aircraft motion is presented in this paper. The reconstruction of flight path is formulated as a discrete, linear, time-variant state reconstruction problem which can be solved by Kalman filtering techniques. The U-D covariance factorization filter, which has excellent numerical characteristics and needs less computation, is used. Furthermore, by exploiting some special features of the system model, the new partitioned U-D factorization filter and the algorithm to make the bias terms controllable are proposed. This method makes the algorithm implementation more efficient and improves the convergence of filter scheme. The simulating and real flight test data computations show that the proposed method in this paper is robust and efficient.
出处
《航空学报》
EI
CAS
CSCD
北大核心
1992年第7期A394-A397,共4页
Acta Aeronautica et Astronautica Sinica
基金
航空科学基金 编号89153058
关键词
卡尔曼滤波
分解滤波
飞行轨迹重构
Kalman filter, U-D covariance factorization filter, flight path reconstruction
