Optimal guidance against active defense ballistic missiles via differential game strategies

Liang, Heng; Wang, Yonghai; Wang, Linlin; Liu, Peng

doi:10.1016/j.cja.2019.12.009

Cited by 41 publications

(19 citation statements)

References 23 publications

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“…The infrared seeker takes about 0.3 s to recognize the real target from the numerous decoys [26,27]. The state in which the seeker recognizes the real target is called the anti-infrared decoy state.…”

Section: Fig 2 Seeker Tracking the Energy Centermentioning

confidence: 99%

Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

Li²,

Xia

2021

J. of Syst. Eng. Electron.

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In this paper, the method of extracting guidance information such as the line-of-sight (LOS) rates under the anti-infrared decoy state for the roll-pitch seeker is researched. Coordinate systems which are used to describe the angles transform are defined. The LOS angles reconstruction model of the roll-pitch seeker in inertial space is established. A Kalman filter model for extracting LOS rates of the roll-pitch seeker is proposed. In this model, the target performs constant acceleration (CA) model maneuvers. The error model of LOS rates extraction under infrared decoy state is established. Several existing methods of extracting LOS rates under anti-infrared decoy state are listed in this paper. Different from the existing methods, a novel method that uses extrapolated values of target accelerations as filter measurements is proposed to solve the guidance information extraction problem under the anti-infrared decoy state. Numerical simulations are conducted to verify the effectiveness of the proposed method under different target maneuvering models such as the CA model, the CA extended model and the singer model. The simulation results show that the proposed method of extracting guidance information such as LOS rates for the rollpitch seeker under the anti-infrared decoy state is effective.

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Section: Fig 2 Seeker Tracking the Energy Centermentioning

confidence: 99%

Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

Li²,

Xia

2021

J. of Syst. Eng. Electron.

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“…Based on the linear-quadratic differential game, literature 20 investigated a midcourse maneuvering strategy, which helps the missile save its fuel while increasing the interceptor's consumption. In, References 21,22 the differential game was applied to the active defense problem, and the optimal guidance laws for missiles, defenders, and interceptors were derived, respectively. Liang et al 23 further gave a workable solution for applying the differential game to a two-on-two engagement scenario.…”

Section: Introductionmentioning

confidence: 99%

Maneuvering penetration strategies of ballistic missiles based on deep reinforcement learning

Qiu

Gao

Jing

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this paper, a ballistic missile terminal penetration scenario is studied, which contains three participants: target, missile, and defender. The ballistic missile attempts to hit the target while evading the defender. A maneuvering penetration guidance strategy that balances both the guidance accuracy and penetration capability is proposed through deep reinforcement learning. Reward shaping and random initialization are applied to improve training speed and generalization, respectively. The proposed strategy is developed based on the twin delayed deep deterministic policy gradient algorithm. It directly maps observations to actions and is an end-to-end guidance scheme that does not require an accurate model. The simulation results show that the proposed strategy has higher penetration probabilities than conventional strategies for different initial heading errors and even for defenders with different guidance laws, which indicates its good robustness and generalization. For different initial heading errors, it has learned different maneuvering modes and has certain intelligence. In addition, it is computationally small, does not consume much memory, and can be easily applied on modern flight computers.

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“…The proposed approach focuses on the miss distance as the outcome of the conflict. Liang et al 9 investigated the optimal guidance problem for an interceptor against a ballistic missile with active defence. A class of optimal guidance schemes are proposed based on a linear quadratic differential game method and the numerical solution to the Riccati differential equation.…”

Section: Introductionmentioning

confidence: 99%

“…A class of optimal guidance schemes are proposed based on a linear quadratic differential game method and the numerical solution to the Riccati differential equation. In 9 , the fuel cost, control saturation and chattering phenomenon were considered. Weiss et al 10 used a minimum-effort guidance approach to obtain a combined guidance law for the attacker.…”

Section: Introductionmentioning

confidence: 99%

A hierarchical reinforcement learning method for missile evasion and guidance

Yan

Yang

Zhang

et al. 2022

Sci Rep

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This paper proposes an algorithm for missile manoeuvring based on a hierarchical proximal policy optimization (PPO) reinforcement learning algorithm, which enables a missile to guide to a target and evade an interceptor at the same time. Based on the idea of task hierarchy, the agent has a two-layer structure, in which low-level agents control basic actions and are controlled by a high-level agent. The low level has two agents called a guidance agent and an evasion agent, which are trained in simple scenarios and embedded in the high-level agent. The high level has a policy selector agent, which chooses one of the low-level agents to activate at each decision moment. The reward functions for each agent are different, considering the guidance accuracy, flight time, and energy consumption metrics, as well as a field-of-view constraint. Simulation shows that the PPO algorithm without a hierarchical structure cannot complete the task, while the hierarchical PPO algorithm has a 100% success rate on a test dataset. The agent shows good adaptability and strong robustness to the second-order lag of autopilot and measurement noises. Compared with a traditional guidance law, the reinforcement learning guidance law has satisfactory guidance accuracy and significant advantages in average time and average energy consumption.

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Optimal guidance against active defense ballistic missiles via differential game strategies

Cited by 41 publications

References 23 publications

Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

Maneuvering penetration strategies of ballistic missiles based on deep reinforcement learning

A hierarchical reinforcement learning method for missile evasion and guidance

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