| 引用本文: | 李冬,魏超,周萱影.初始误差和制导工具误差估计的非线性方法.[J].国防科技大学学报,2018,40(6):61-67.[点击复制] |
| LI Dong,WEI Chao,ZHOU Xuanying.Estimation of initial error and guidance instrumentation error based on nonlinear model[J].Journal of National University of Defense Technology,2018,40(6):61-67[点击复制] |
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| 初始误差和制导工具误差估计的非线性方法 |
| 李冬1, 魏超1, 周萱影2 |
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(1. 中国人民解放军91550部队， 辽宁 大连 116023;2. 国防科技大学 文理学院， 湖南 长沙 410073)
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| 摘要: |
| 准确估计初始误差和制导工具误差是机动发射飞行器精度鉴定必须解决的重要问题之一，提出了一种基于非线性模型的误差估计新方法。给出了平台初始失准角向定向误差的转换方法，采用不动点迭代法实现真实视加速度的精确计算，将真实发射系的轨道参数表示为初始误差和工具误差的非线性函数，结合外测数据建立了同时估计初始误差、工具误差、外测系统误差、遥外测时间零点偏差的非线性模型，避免了初始误差的线性化近似。给出了Bayes极大后验估计方法，利用非线性模型和先验信息获得误差的最优估计，证明了估计方法的收敛性。仿真结果表明，所提方法提高了初始误差和工具误差的估计精度，并实现了测量数据的自校准。 |
| 关键词: 初始误差 制导工具误差 非线性模型 Bayes极大后验估计 |
| DOI：10.11887/j.cn.201806009 |
| 投稿日期：2017-10-06 |
| 基金项目:国家自然科学基金资助项目（61703408） |
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| Estimation of initial error and guidance instrumentation error based on nonlinear model |
| LI Dong1, WEI Chao1, ZHOU Xuanying2 |
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(1. The PLA Unit 91550, Dalian 116023, China;2. College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China)
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| Abstract: |
| The accurate estimation of the initial error and the guidance instrumentation error plays a key role in the precision assessment of the maneuvering launched vehicle, so a new estimation method based on nonlinear model was proposed. The platform initial angle error was transformed into the orientation error. The true apparent acceleration was accurately calculated by using the fixed point iteration method. Then, the trajectory parameters of the truth launch coordinate were represented by a nonlinear function with the initial error and the guidance instrumentation error. A nonlinear model was constructed by using the exterior trajectory measurements. This model can simultaneously estimate the initial error, the guidance instrumentation error, the measurement systematic error, and the time-zero deviation between telemetry data and exterior data, and it can avoid the linear approximation of the initial error. The Bayes MAP (maximum a posterior) estimation is given to obtain the optimal estimation of these errors by using the nonlinear model and the prior information, and it is proved to be convergent. Experimental results show that the proposed method improves the estimation accuracy of the initial error and the guidance instrumentation error when compared with the linear method and other nonlinear method. Furthermore, the proposed method can also achieve the self calibration between different measurements. |
| Keywords: initial error guidance instrumentation error nonlinear model Bayes maximum posterior estimation |
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