Cooperative Missile Guidance for Active Defense of Air Vehicles

García, Eloy; Casbeer, David W.; Fuchs, Zachariah E.; Pachter, Meir

doi:10.1109/taes.2017.2764269

Cited by 79 publications

(31 citation statements)

References 27 publications

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“…Research on missile guidance and control fields is being actively conducted nowadays, as it has always been [1][2][3][4][5][6][7][8][9][10]. Traditionally, the guidance system and control system of an interceptor missile are separately designed.…”

Section: Introductionmentioning

confidence: 99%

Integrated Guidance and Control Using Model Predictive Control with Flight Path Angle Prediction against Pull-Up Maneuvering Target

Park

Kim

2020

Sensors

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Integrated guidance and control using model predictive control against a maneuvering target is proposed. Equations of motion for terminal homing are developed with the consideration of short-period dynamics as well as actuator dynamics of a missile. The convex optimization problem is solved considering inequality constraints that consist of acceleration and look angle limits. A discrete-time extended Kalman filter is used to estimate the position of the target with a look angle as a measurement. This is utilized to form a flight-path angle of the target, and polynomial fitting is applied for prediction. Numerical simulation including a Monte Carlo simulation is performed to verify the performance of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Integrated Guidance and Control Using Model Predictive Control with Flight Path Angle Prediction against Pull-Up Maneuvering Target

Park

Kim

2020

Sensors

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“…The air defense, which has the most potential in counteracting airstrikes is missiles with a high level of maneuvering accuracy accompanied by an autopilot system that can guide missiles to hit targets in the air. Eloy Garcia et al describe the effectiveness of air defense, with the theme of the cooperative missile guide to active defense of air vehicles [2]. About active countermeasures against missile attacks that lead to the aircraft as a target, with the aim of airstrikes can be anticipated to the maximum and can avoid casualties and material damage.…”

Section: Introductionmentioning

confidence: 99%

Smart guided missile using accelerometer and gyroscope based on backpropagation neural network method for optimal control output feedback

Faqih

Sujito

Sendari

et al. 2020

J. Mechatron. Electr. Power Veh. Technol.

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As a maritime country with a large area, besides the need to defend itself with the military, it also needs to protect itself with aerospace technology that can be controlled automatically. This research aims to develop an air defense system that can control guided missiles automatically with high accuracy. The right method can provide a high level of accuracy in controlling missiles to the targeted object. With the backpropagation neural network method for optimal control output feedback, it can process information data from the radar to control missile’s movement with a high degree of accuracy. The controller uses optimal control output feedback, which is equipped with a lock system and utilizes an accelerometer that can detect the slope of the missile and a gyroscope that can detect the slope between the target direction of the missile to follow the target, control the position, and direction of the missile. The target speed of movement can be easily identified and followed by the missile through the lock system. Sampling data comes from signals generated by radars located in defense areas and from missiles. Each part’s data processing speed is calculated using a fast algorithm that is reliable and has a level of accuracy and fast processing. Data processing impacts on the accuracy of missile movements on any change in the position and motion of targets and target speed. Improved maneuvering accuracy in the first training system can detect 1000 files with a load of 273, while in the last training, the system can detect 1000 files without a load period. So the missile can be guided to hit the target without obstacles when maneuvering.

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“…In order to protect the target, a widely discussed topic in recent years is the active defense countermeasure, whereby a defending missile (or a defender) is launched from the target or a target-friendly platform to intercept the attacking missile. There are several approaches to investigating the active defense problem, including optimal control [ 1 , 2 , 3 , 4 , 5 ], differential game [ 6 , 7 , 8 , 9 , 10 ], sliding mode control [ 11 ], and line-of-sight guidance [ 12 , 13 ]. In [ 1 , 2 , 3 , 4 , 5 ], the authors used optimal control theory to derive cooperative guidance laws for target and defender with the assumption that the pursuit guidance law of an attacking missile is fixed and known.…”

Section: Introductionmentioning

confidence: 99%

“…In [ 1 , 2 , 3 , 4 , 5 ], the authors used optimal control theory to derive cooperative guidance laws for target and defender with the assumption that the pursuit guidance law of an attacking missile is fixed and known. In [ 6 , 7 , 8 , 9 , 10 ], the authors adopted differential game theory to analyze the dynamic conflicts and design the associated guidance laws. In [ 11 ], a cooperative guidance law based on sliding model control was proposed, and its objective was to make the zero-effort miss distance and zero-effort relative velocity of missile–defender engagement both zero.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Estimation and Cooperative Guidance for Active Aircraft Defense in Stochastic Scenario

Fang

Cai

2019

Sensors

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The active aircraft defense problem is investigated for the stochastic scenario wherein a defending missile (or a defender) is employed to protect a target aircraft from an attacking missile whose pursuit guidance strategy is unknown. For the purpose of identifying the guidance strategy, the static multiple model estimator (sMME) based on the square-root cubature Kalman filter is proposed, and each model represents a potential attacking missile guidance strategy. Furthermore, an estimation enhancement approach is provided by using pseudo-measurement. For each model in the sMME, the model-matched cooperative guidance laws for the target and defender are derived by formulating the active defense problem as a constrained linear quadratic problem, where an accurate defensive interception and the minimum evasion miss distance are both considered. The proposed adaptive cooperative guidance laws are the result of mixing the model-matched optimal cooperative guidance laws in the criterion of maximum a posteriori probability in the framework of the sMME. By adopting the adaptive cooperative guidance laws, the target can facilitate the defender’s interception with the attacking missile with less control effort. Also, simulation results show that the proposed guidance laws increase the probability of successful target protection in the stochastic scenario compared with other defensive guidance laws.

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Cooperative Missile Guidance for Active Defense of Air Vehicles

Cited by 79 publications

References 27 publications

Integrated Guidance and Control Using Model Predictive Control with Flight Path Angle Prediction against Pull-Up Maneuvering Target

Integrated Guidance and Control Using Model Predictive Control with Flight Path Angle Prediction against Pull-Up Maneuvering Target

Smart guided missile using accelerometer and gyroscope based on backpropagation neural network method for optimal control output feedback

Adaptive Estimation and Cooperative Guidance for Active Aircraft Defense in Stochastic Scenario

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