Game Theoretic Non-cooperative Dynamic Target Tracking for Directional Sensing-Enabled Unmanned Aerial Vehicles

IF 6.8 Q1 AUTOMATION & CONTROL SYSTEMS
Peng Yi, Ge Jin, Wenyuan Wang
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引用次数: 0

Abstract

In this article, a game theoretic non-cooperative dynamic target tracking algorithm that empowers defensive unmanned aerial vehicles (UAVs), with directional sensing capabilities to track and collect information on intrusive UAVs, is proposed. Specifically, defenders aim to maximize the collection of identity information from intruders possessing anti-tracking and evading capabilities, while simultaneously preventing their entry into protected areas. Game theory is employed to determine the optimal confrontation paths for defenders against the intruders. The probability perception model is utilized for evaluating the dynamic target tracking capability and designing a tracking merit function to assess tracking performance, taking into account both the target's position and the perception relative angle. Furthermore, considering the dynamic interactive behaviors between intruders and defenders, the iterative linear quadratic game (ILQG) algorithm is employed to solve the Nash equilibrium of the non-cooperative target tracking game. Through simulation experiments, the effectiveness of the proposed algorithm in accomplishing multi-agent dynamic target tracking tasks is demonstrated and the performance of the algorithm under varying parameters in the intruder's cost function is evaluated, which represent different intrusion intentions.

Abstract Image

支持定向传感的无人飞行器的博弈论非合作动态目标跟踪
本文提出了一种博弈论非合作动态目标跟踪算法,该算法使具有定向感应能力的防御型无人飞行器(UAV)能够跟踪和收集入侵型无人飞行器的信息。具体来说,防御者的目标是最大限度地收集具有反跟踪和规避能力的入侵者的身份信息,同时阻止其进入保护区。博弈论被用来确定防御者与入侵者的最佳对抗路径。利用概率感知模型来评估动态目标跟踪能力,并设计跟踪优点函数来评估跟踪性能,同时考虑目标的位置和感知相对角度。此外,考虑到入侵者和防御者之间的动态交互行为,采用迭代线性二次博弈(ILQG)算法求解非合作目标跟踪博弈的纳什均衡。通过仿真实验,证明了所提算法在完成多代理动态目标跟踪任务中的有效性,并评估了算法在入侵者成本函数参数变化(代表不同入侵意图)下的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
0.00%
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