一种飞行器高精度高动态自主拦截 / 碰撞的方法

By employing a method based on rotation matrix and delayed Kalman filtering, the control error problem caused by camera delay and low frame rate under high-speed multi-rotor motion was solved, achieving stability and success rate of high-precision, high-dynamic autonomous interception/collision missions.

CN118242933BActive Publication Date: 2026-07-17BEIHANG UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIHANG UNIV
Filing Date
2024-02-29
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies for high-precision, high-dynamic autonomous interception/collision missions suffer from camera imaging and image processing delays caused by the high-speed movement of multi-rotors, resulting in large control errors and low image feedback frequency leading to system instability, making it difficult to achieve high-precision interception/collision.

Method used

By employing a rotation matrix-based controller and a delayed Kalman filter method, combined with an aircraft model, target model, camera imaging model, and IMU measurement model, the stability and accuracy of the controller are optimized through delayed state estimation, achieving high-precision and high-dynamic interception/collision.

Benefits of technology

It improves the success rate and accuracy of interception/collision missions, and can achieve stable autonomous interception/collision control under high-speed conditions, effectively responding to the threat of high-speed target intrusion.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明提出一种飞行器高精度高动态自主拦截 / 碰撞的方法,包括如下步骤:步骤一:基于旋转矩阵的控制器;在步骤一中,基于旋转矩阵的控制器根据收集到的图像信息和飞行器自身状态,计算拦截控制量;飞行器模型、目标模型、相机成像模型共同构成了步骤一的数学模型;步骤二:基于延迟卡尔曼滤波的观测器;飞行器模型、目标模型、相机成像模型、IBVS模型共同构成了系统模型、IMU测量模型和图像延迟测量模型,这些模型用于延迟卡尔曼滤波的状态预测和测量更新。本发明引入了基于旋转矩阵的高精度高动态自主拦截 / 碰撞控制,作为支持拦截 / 碰撞的关键技术。本发明验证了算法在机载感知和控制下的有效性,巩固了其在实际应用中的可行性。这些贡献共同推动了运动目标高精度高动态自主拦截 / 碰撞技术的发展,为有效应对高速目标入侵威胁提供了重要的工具和方法。
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