基于耦合气动参数的HGV多模型估计

利用气动参数对未知气动力建模是提高高超声速滑翔目标跟踪精度的有效途径。对目标气动加速度及其导数项进行分析，在非耦合气动参数模型的基础上，考虑气动加速度在转弯和俯仰方向存在的先验信息，推导滚转和螺旋2种耦合气动参数模型。利用一种分离估计模型对目标状态与气动参数进行估计，分别给出状态滤波器和气动参数滤波器的表达式。同时，考虑不同飞行模式下参数的机动频率，构建基于耦合气动参数的交互多模型跟踪算法。仿真表明，本文所提算法精度显著高于针对该类目标的其他跟踪算法。同时，滚转模型的性能优于螺旋模型，且计算复杂度更小。 

Multi-model estimation of HGV based on coupled aerodynamic parameters

Using aerodynamic parameters to model the unknown aerodynamics is an effective way to improve the tracking accuracy of hypersonic gliding vehicles. The aerodynamic acceleration and its derivative is analyzed to prove the necessity of unknown aerodynamics modeling in this paper. Based on the non-coupled aerodynamic parameter model, two coupled aerodynamic parameter models, the Bank model and the spiral model, are constructed by using the priori information of the aerodynamic acceleration in the turn and pitch directions. The target's state and aerodynamic parameters are estimated by a decomposed estimator, and the state filter and the aerodynamic parameter filter are deduced respectively. Meanwhile, considering the maneuver frequencies of parameters in different flight modes, the interacting multiple model tracking algorithm is built based on the coupled aerodynamic parameters. The simulation results show that the accuracy of the proposed algorithms is significantly higher than other tracking algorithms for such targets. In the meantime, the performance of the bank model is better than that of the spiral model, and its computational complexity is smaller.