针对静止目标的自主拦截任务的比例导航制导

Aman Choudhary, V. A, Satadal Ghosh
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引用次数: 0

摘要

由于无人驾驶飞行器(UAV)的使用迅速增加,对保护保护区的高效自主拦截技术的需求变得越来越重要。提出了一种基于比例导航(PN)的新型制导策略,用于单架和多架无人机拦截静止目标。虽然以前的文献主要是针对单跟踪器和多跟踪器设置分别解决控制终端角度和实现期望的最终时间,但设计同时实现这两个目标的制导策略是一个重大挑战。虽然现有文献很少努力满足这两个约束,但它们缺乏保证全面的方法。为此,本文的主要贡献是通过在单跟踪器和多跟踪器设置中采用基于pn的多相制导策略,使跟踪器能够从任意初始方向开始实现任意终端配置,同时满足最终时间约束。开始的“准备阶段”和结束的“最终PPN阶段”有助于确保期望的终端方向,而中间的漫游阶段有助于实现期望的最终时间。分析了各制导方案的相变和性能保证以及制导方案成功的最终可实现时间条件。最后,通过数值仿真,在考虑现实约束条件的单跟踪器和多跟踪器环境下对所开发的制导算法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proportional Navigation-Based Guidance for an Autonomous Interdiction Mission Against a Stationary Target
Due to the rapid increase of unmanned aerial vehicle (UAV) usage, the demand for efficient autonomous interdiction techniques to safeguard protected areas has become increasingly essential. This paper presents novel guidance strategies based on Proportional Navigation (PN) to interdict a stationary target using single and multiple unmanned aerial vehicles (UAVs). While the previous literature has primarily addressed controlling the terminal angle and achieving a desired final time separately for single-pursuer and multi-pursuer setups, designing guidance strategies to achieve both simultaneously poses a significant challenge. Although few existing literature endeavor to satisfy both constraints, they lack in guaranteeing an all-aspect approach. To this end, this paper’s main contribution is enabling pursuers to achieve any terminal configuration starting from any initial orientation while satisfying the final time constraint by employing PN-based multi-phase guidance strategies in single and multiple pursuer setups. While the ‘Preparation phase’ at the beginning and the ‘Final PPN phase’ at the end help ensure the desired terminal orientation, the intermediate Roaming phase helps achieve the desired final time. Also, the guarantee on phase transitions and performance of the overall guidance schemes and conditions on achievable final time for the success of the developed guidance schemes are analyzed. Finally, using numerical simulations, the developed guidance algorithms are validated for single and multiple pursuer(s) environments considering realistic constraints.
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