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  • 标题:Predictive Missile Guidance with Online Trajectory Learning
  • 本地全文:下载
  • 作者:M. Ugur Akcal ; N. Kemal Ure
  • 期刊名称:Defence Science Journal
  • 印刷版ISSN:0976-464X
  • 出版年度:2017
  • 卷号:67
  • 期号:3
  • 页码:332-339
  • 语种:English
  • 出版社:Defence Scientific Information & Documentation Centre
  • 摘要:This study presents a predictive guidance scheme for tactical missiles. The modern day targets, with improved manoeuverability, have revealed insufficient performance of the conventional guidance laws. The underlying cause of this poor performance is the reactive nature of the conventional guidance laws such as proportional navigation (PN) and pure pursuit (PP). Predictive guidance offers an alternative approach to the classical methods by taking proactive actions by estimating target’s future trajectory. However, most of the existing predictive guidance approaches assume that the interceptor have a model of the target dynamics. A guidance strategy is developed in this study, that can learn the target dynamics iteratively and adapt the interceptor actions accordingly. A recursive least squares (RLS) estimation algorithm is employed for learning and estimating the possible future target positions, and a fixed horizon nonlinear program is employed for selecting the optimal interception action. Monte-Carlo simulations show that the guidance algorithm introduced in this work demonstrates a significantly improved performance compared to the alternatives in terms of interception time and miss distance.
  • 关键词:Predictive guidance;Trajectory learning;Tactical missile;Recursive least squares;Parameter estimation;Optimal interception
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