Input Estimation Algorithms for Reentry Vehicle Trajectory Estimation

Defence Science Journal

Cheng-Yu Liu¹  Pan-Chio Tuan²  Huai-Min Wang² 

[1] Lee-Ming Institute of Technology, Taipei;Chug Cheng Institute of Technology, Taoyuan

关键词: Reentry vehicle;    trajectory estimation;    input estimation;    extended Kalman filter;    reentry vehicle tracking;    reentry vehicle interception;    reentry vehicle trajectory;    validation models;    trajectory estimation algorithms;    simulation and modelling;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: Defence Scientific Information & Documentation Centre

【 摘 要 】

Fast and accurate estimation of trajectory is important in tracking and intercepting reentry vehicles. Validating model is a real challenge associated with the qverall trajectory estimation problem. Input estimation technique provides a’solution to this challenge. Two input estimation algorithms were introduced based on different assumptions about the input applied to the model. This investigation presents approaches consisting of an extended Kahnan filter and two input estimation algorithms to identify the reentry vehicle trajectory in its terminal phase using data from a single radar source. Numerical simulations with data generated from two models demonstrate superior capabilities as measured by accuracy compared to the extended Kalman filter. Evaluation using real flight data provides the consistent results. The comparison between two input estimation algorithms is also presented. The trajectory estimation approaches based on two algorithms are effective in solving the reentry vehicle tracking problem.

【 授权许可】

Unknown