Estimation of Aerodynamic Parameter for Maneuvering Reentry Vehicle Tracking

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• 英文论文题名：Estimation of Aerodynamic Parameter for Maneuvering Reentry Vehicle Tracking
• 论文作者：Kai Zhang ; Tingting Fu ; Jiajun Xiong
• 英文论文作者：Kai Zhang ; Tingting Fu ; Jiajun Xiong ; Department of Graduation Management ; Air Force Early Warning Academy ; No.4 Department ; Air Force Early Warning Academy
• 年：2017
• 作者机构：Department of Graduation Management,Air Force Early Warning Academy;No.4 Department,Air Force Early Warning Academy;
• 英文论文关键词：Parameter Estimation ; Aerodynamic Parameter ; Maneuvering Reentry Vehicle ; Reentry Tracking ; Aerodynamic Model ; Cubature Kalman Filter ; Fixed Interval
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：V211
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：5
• 文件大小：225k
• 原文格式：D
• 会议级别：全国

摘要

Aim at handling complicated maneuvers or other unpredicted emergencies, an estimation method of aerodynamic parameter via the Cubature Kalman Filter/Smoother(CKF/S) is proposed for maneuvering reentry vehicle(MaRV) tracking. The aerodynamic model is deduced in order to define the aerodynamic parameter at first. Secondly, the statistical properties of aerodynamic parameters are described by first-order Markov processes, the random processes are carefully chosen and tuned for filtering. Meanwhile,the state model is achieved by augmented these parameters into state vector. Then, the CKF/S is introduced to deal with estimation of aerodynamic parameters. Particularly, a fixed interval(FI) CKS, which carries on forward filtering firstly and then backward smoothing in an interval of fixed time series, is applied to this problem. A comparative performance assessment of three estimation algorithms is presented. The results show that the FI-CKS performs better than the CKF. Moreover, it can achieve a better real-time character compared with the CKS.
Aim at handling complicated maneuvers or other unpredicted emergencies, an estimation method of aerodynamic parameter via the Cubature Kalman Filter/Smoother(CKF/S) is proposed for maneuvering reentry vehicle(MaRV) tracking. The aerodynamic model is deduced in order to define the aerodynamic parameter at first. Secondly, the statistical properties of aerodynamic parameters are described by first-order Markov processes, the random processes are carefully chosen and tuned for filtering. Meanwhile,the state model is achieved by augmented these parameters into state vector. Then, the CKF/S is introduced to deal with estimation of aerodynamic parameters. Particularly, a fixed interval(FI) CKS, which carries on forward filtering firstly and then backward smoothing in an interval of fixed time series, is applied to this problem. A comparative performance assessment of three estimation algorithms is presented. The results show that the FI-CKS performs better than the CKF. Moreover, it can achieve a better real-time character compared with the CKS.

引文

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