不完全信息下导弹参数与状态的联合估计

Joint Estimation of Parameters and States for Missile with Incomplete Information

基于UKF推导了非线性系统参数的递推最大似然估计算法,并结合UKF实现了对不完全信息下导弹的参数与状态的实时联合估计。首先通过引入导弹的导引律,建立导弹的状态滤波模型,进而给出参数辨识的一般递推似然法,并在UKF状态滤波算法的基础上推导出非线性递推最大似然参数估计方法,实现了参数估计与状态滤波的并行计算。仿真结果表明,该方法收敛速度快,具有很好的实时性和较高的估计精度。

The nonlinear system recursive maximum likelihood （RML） estimation method was derived based on Unscented Kalman Filter （UKF）, and real-time joint estimation of parameters and states for missiles with incomplete information was realized. First, the guidance law was introduced into the missile state estimation model, and a state filtering model was established. Then, the classical RML method for parameter identification was presented, based on which the nonlinear RML was developed through UKF. Finally, the parallel calculation of parameter identification and state estimation was completed. The numerical simulation result shows that this method has fast convergence speed, good real-time performance and high estimation accuracy.