Two-stage robust extended Kalman filter in autonomous navigation for the powered descent phase of Mars EDL
Two-stage robust extended Kalman filter in autonomous navigation for the powered descent phase of Mars EDL
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DOI：
10.1049/iet-spr.2014.0027
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发表时间：
2015-05
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影响因子：
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通讯作者：
Qiang Xiao;Yun-zhang Wu;H. Fu;Yongbo Zhang
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文献类型：
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作者：
Qiang Xiao;Yun-zhang Wu;H. Fu;Yongbo Zhang
针对输入未知的非线性不确定系统，提出了一种两级鲁棒扩展卡尔曼滤波器（TREKF）。在工程实践中，对于非线性不确定系统的未知输入，扩展卡尔曼滤波器（EKF）可能会出现退化甚至发散的情况。针对未知输入，设计了最优两级EKF （TEKF）。鲁棒EKF （REKF）一直被认为是求解非线性不确定系统的有效方法。然而，具有未知输入的非线性不确定系统的信息总是不正确的。为了解决这一问题，利用TEKF和REKF的优点设计了TREKF，并对其稳定性进行了验证。最后，通过火星EDL动力下降阶段（进入、下降和着陆）的数值算例，将TREKF的性能与REKF、TEKF和EKF的结果进行比较，验证了TREKF的性能。这也验证了在火星EDL动力下降阶段，将TREKF用于微型相干高度计、测速仪和惯性测量单元组合导航，有效地减少了模型不确定性和未知输入的不利影响。
This paper proposed a two-stage robust extended Kalman filter (TREKF) for state estimation of non-linear uncertain system with unknown inputs. In engineering practice, the extended Kalman filter (EKF) with unknown inputs of the non-linear uncertain system may be degraded or even diverged. The optimal two-stage EKF (TEKF) is designed to solve the unknown inputs. The robust EKF (REKF) is considered to solve the non-linear uncertain system for a long time. However, the information about the non-linear uncertain system with unknown inputs is always incorrect. To solve this problem, the TREKF is designed by using the advantages of the TEKF and REKF, furthermore, its stability is proved. Finally, the performances of the TREKF, which are compared with the results of the REKF, TEKF and EKF, are verified by illustrating a numerical example of the powered descent phase of Mars EDL (entry, descent and landing). These also verify that the unfavourable effects of the model uncertainties and the unknown inputs are reduced efficiently by using the TREKF for the miniature coherent altimeter and velocimeter and inertial measurement unit integrated navigation during the powered descent phase of Mars EDL.