Optimal Proportional Navigation Guidance Using Pseudo Sensor Enhancement Method (PSEM) for Flexible Interceptor Applications

Madany, Yasser M.; El-Badawy, El-Sayed A.; Soliman, Adel M.

doi:10.1109/uksim.2016.35

Cited by 5 publications

(7 citation statements)

References 9 publications

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“…Proportional navigation guidance (PNG) is the most widely used guidance law on homing missiles with an active seeker [2,11,12]. PNG generates an acceleration command by multiplying the The reason the missile needs its phase switched is because INS-aided guidance is not that accurate nor precise.…”

Section: Proportional Navigation Guidance Lawmentioning

confidence: 99%

Study on Reinforcement Learning-Based Missile Guidance Law

2020

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Reinforcement learning is generating considerable interest in terms of building guidance law and solving optimization problems that were previously difficult to solve. Since reinforcement learning-based guidance laws often show better robustness than a previously optimized algorithm, several studies have been carried out on the subject. This paper presents a new approach to training missile guidance law by reinforcement learning and introducing some notable characteristics. The novel missile guidance law shows better robustness to the controller-model compared to the proportional navigation guidance. The neural network in this paper has identical inputs with proportional navigation guidance, which makes the comparison fair, distinguishing it from other research. The proposed guidance law will be compared to the proportional navigation guidance, which is widely known as quasi-optimal of missile guidance law. Our work aims to find effective missile training methods through reinforcement learning, and how better the new method is. Additionally, with the derived policy, we contemplated which is better, and in which circumstances it is better. A novel methodology for the training will be proposed first, and the performance comparison results will be continued therefrom.

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Section: Proportional Navigation Guidance Lawmentioning

confidence: 99%

Study on Reinforcement Learning-Based Missile Guidance Law

2020

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“…Two‐dimensional missile‐target geometry has been shown in Fig. 7 [17, 30]. In this section, the optimal inertial navigation multi‐sensor configurations using OPSEM have been applied to the PNG laws to investigate the optimal performance.…”

Section: Optimal Pngmentioning

confidence: 99%

“… Missile‐target geometry [17, 30] A M : missile acceleration, V M : missile velocity, A T : target acceleration, V T : target velocity, R TM : the sight‐line between missile and the target (LOS), y : height,

\dot{θ}

LOS : LOS rotation rate.…”

Section: Optimal Pngmentioning

confidence: 99%

“…The calibration of the navigational system and the compensation of the amount of error during navigation is one of the most urgent procedures that help stabilise the operation of the system using multiple sensors [11–14]. In [15–18], the proposed pseudo sensor enhancement method (PSEM) was introduced to achieve the optimal structural configuration of the sensors and study the prediction of the most critical sensor. Then, a specific pseudo sensor will be integrated with the critical sensor at the same arrangement position and both are working together as a unity sensor to overcome the errors that cause malfunction of the navigational system.…”

Section: Introductionmentioning

confidence: 99%

“…Then, a specific pseudo sensor will be integrated with the critical sensor at the same arrangement position and both are working together as a unity sensor to overcome the errors that cause malfunction of the navigational system. The proposed PSEM was also applied to the proportional navigation guidance (PNG) guidance law to verify performance improvement [17]. In this paper, a novel proposed optimal PSEM (OPSEM) is introduced, investigated and implemented.…”

Section: Introductionmentioning

confidence: 99%

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