Abstract
With its superior performance, the unmanned combat air vehicle (UCAV) will gradually become an important combat force in the future beyond-visual-range (BVR) air combat. For the problem of UCAV using the BVR air-to-air missile (AAM) to intercept the highly maneuvering aerial target, an autonomous attack guidance method with high aiming precision is proposed. In BVR air combat, the best launching conditions can be formed through the attack guidance and aiming of fighters, which can give full play to the combat effectiveness of BVR AAMs to the greatest extent. The mode of manned fighters aiming by manual control of pilots is inefficient and obviously not suitable for the autonomous UCAV. Existing attack guidance control methods have some defects such as low precision, poor timeliness, and too much reliance on manual experience when intercepting highly maneuvering targets. To address this problem, aiming error angle is calculated based on the motion model of UCAV and the aiming model of BVR attack fire control in this study, then target motion prediction information is introduced based on the designed model predictive control (MPC) framework, and the adaptive fuzzy guidance controller is designed to generate control variable. To reduce the predicted aiming error angle, the algorithm iteratively optimizes and updates the actual guidance control variable online. The simulation results show that the proposed method is very effective for solving the autonomous attack guidance problem, which has the characteristics of adaptivity, high timeliness, and high aiming precision.
Highlights
IntroductionAs an emerging combat force, unmanned combat air vehicle (UCAV) are playing an increasingly important role in warfare
As an emerging combat force, unmanned combat air vehicle (UCAV) are playing an increasingly important role in warfare.With its excellent performance advantages such as higher agility, harder overload durability, and higher stealth capability, UCAVs gradually develop rapidly towards the direction of direct attack and killing ability [1]
In the actual BVR air combat, to effectively connect the above-mentioned two missions of UCAVs occupying a superior situation and BVR air-to-air missile (AAM)’ guidance, it is necessary to have a crucial process of attack guidance and aiming of the UCAV
Summary
As an emerging combat force, UCAVs are playing an increasingly important role in warfare. To eliminate the aiming error angle in the BVR air combat, the aiming mode of manned fighters is to maneuver through the manual control of the pilots, which is inefficient and obviously not suitable for autonomous UCAVs. The traditional automatic attack guidance method based on the integrated flight/fire control system [23,24,25] relies too much on the set of control parameters by artificial expertise, and it is difficult to adapt to all air combat situations, and the aiming precision could not meet the requirements when intercepting the highly maneuvering target. The aiming error angle is calculated based on the motion model of UCAV and the aiming model of BVR attack fire control in this study, target motion prediction information is introduced based on the designed MPC framework, and the adaptive fuzzy guidance controller is designed to generate control variable.
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