模型参数扰动下的火星大气进入鲁棒状态估计方法

针对火星大气进入段模型参数扰动及动力学系统的强非线性影响导航系统状态精确估计问题，提出了一种模型参数扰动下的鲁棒插值滤波（DDF）方法。该方法在传统插值滤波方法代价函数的基础上，通过把扰动参数对状态估计精度影响的度量矩阵乘积的迹增广到代价函数，推导了具有解析滤波增益形式的鲁棒插值滤波方法。同时，通过实时计算进入过程中导航系统的非线性，基于系统非线性度给出了鲁棒插值滤波方法阶次自适应选取准则。只在系统强非线性阶段采用高阶鲁棒插值滤波方法，既保证状态估计精度，同时满足导航系统实时性需求。仿真结果表明，提出的鲁棒插值滤波方法比传统的一阶插值滤波方法估计精度更高，能达到二阶鲁棒插值滤波方法的估计精度，比整个进入过程采用二阶鲁棒插值滤波方法具有更高的解算效率。

Robust State Estimation Method for Martian Atmosphere under Model Parameter Disturbance

A robust divided difference filter (DDF) method is proposed to solve the problem of accurate state estimation influenced by the disturbance of the model uncertainty and strong nonlinearity of the dynamical system. Based on the cost function of the traditional DDF, the robust DDF with the analytic filter gain is deduced by augmenting the traces of the product of the metric matrix of the state estimation error to the model parameter of the cost function. In addition, the nonlinearity of the navigation system is calculated in real-time during Mars entry phase, which is used as the criteria for deciding the order of DDF. High-order robust DDF is used only when the nonlinearity of the system exceeds a given threshold, which can not only guarantee the accuracy of the state estimation, but also meet the real-time demand of the navigation system. The method is used to estimate the state of the probe for Mars entry, and the simulation results show that the estimation performance of the robust DDF proposed in this paper is better than that obtained by the traditional first order DDF. At the same time, it has almost of the same estimation accuracy with the second DDF and much higher computational efficiency.