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首页> 外文期刊>Journal of Aerospace Sciences and Technologies >IMPROVEMENTS IN CLASSICAL PROPORTIONAL NAVIGATION GUIDANCE USING FUZZY LOGIC
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IMPROVEMENTS IN CLASSICAL PROPORTIONAL NAVIGATION GUIDANCE USING FUZZY LOGIC

机译：使用模糊逻辑改进经典比例导航指导

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摘要

The performance of classical Proportional Navigation guidance is limited against highly maneuvering targets and in presence of measurements noise resulting into large miss distances and lower hit probability. Also, the advanced Augmented PN guidance technique requires target state estimation. In this paper, fuzzy logic has been used to implement PN guidance and Membership Functions of fuzzy logic has been tuned using genetic algorithm. The proposed Fuzzy Based PN (FBPN) guidance gives superior performance than PN and APN in terms of lower miss distance, higher hit ratio and better ability to handle measurement noise at all target attack aspects. Deterministic simulations have proved the superior performance and robustness of proposed scheme for various conditions such as step target maneuver upto 9g, weaving maneuver and presence of measurement noise. Further, Monte Carlo simulations have proved that proposed scheme enhances interception performance in realistic scenarios by improving the hit ratio upto 48% and rms miss distance upto 41%. Limitations of APN scheme in terms of target state estimation is also mitigated in the proposed guidance scheme. Finally, global asymptotic stability of fuzzy homing guidance loop is proved using circle criterion.
机译：经典比例导航指导的性能受到高度操纵目标的限制，并且存在测量噪声，从而导致大错过距离和较低的误差。此外，高级增强的PN引导技术需要目标状态估计。在本文中，模糊逻辑已用于实现模糊逻辑的PN指导和隶属函数使用遗传算法进行了调整。所提出的基于模糊的PN（FBPN）指导在低距离，更高的命中率和更好地处理所有目标攻击方面的测量噪声方面的PN和APN提供优异的性能。确定性模拟证明了所提出的方案的卓越性能和稳健性，例如步骤目标操纵高达9G，编织机动和测量噪声的存在。此外，Monte Carlo模拟证明，提出的计划通过提高目标方案中的拦截性能，通过提高48％，RMS错过距离高达41％。在拟议的指导方案中也减轻了APN方案在目标状态估计方面的限制。最后，使用圆标准证明了模糊归巢引导环路的全局渐近稳定性。

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