Defence Science Journal | |
Algorithm of Impact Point Prediction for Intercepting Reentry Vehicles | |
Cheng-Yu Liu1  Pan-Chio Tuan2  Chiun-Chien Liu2  | |
[1] Lee-Ming Institute of Technology, Taipei;Chung Cheng Institute of Technology, Tao Yuan | |
关键词: Reentry vehicle; trajectory estimation; input estimation; adaptive Kalman filter; impact point prediction; counterparallel guidance law; | |
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 】
Intercepting reentry vehicles is difficult because these move nearly at hypersonic speeds that traditional interceptors cannot match. Counterparallel guidance law was developed for defending a high speed target that guides the interceptor to intercept the target at a 180° aspect angle. When applying the counterparallel guidance law, it is best to predict the impact point before launch. Estimation and prediction of a reentry vehicle path are the first steps in establishing the impact point prediction algorithm. Model validation is a major challenge within the overall trajectory estimation problem. The adaptive Kalman filter, consising of an extended Kalman filter and a recursive input estimator, accurately estimates reentry vehicle trajectory by means of an input estimator which processes the model validation problem. This investigation presents an algorithm of impact point prediction for a reentry vehicle and an interceptor at an optimal intercept altitude based on the adaptive Kalman filter. Numerical simulation using a set of data, generated from a complicated model, verifies the accuracy of the proposed algorithm. The algorithm also performs exceptionally well using a set of flight test data. The presented algorithm is effective in solving the intercept problems.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912010139703ZK.pdf | 287KB | download |