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Modeling of Dual-Spinning Projectile with Canard and Trajectory Filtering

机译:基于Canard和轨迹滤波的双旋弹丸建模

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摘要

The article establishes a seven-degree-of-freedom projectile trajectory model for a new type of spinning projectile. Based on this model, a numerical analysis is performed on the ballistic characteristics of the projectile, and the trajectory of the dual-spinning projectile is filtered with the unscented Kalman filter algorithm, so that the measurement information of projectile onboard equipment is more accurate and more reliable measurement data are provided for the guidance system. The numerical simulation indicates that the dual-spinning projectile is mainly different from the traditional spinning projectile in that a degree of freedom is added in the direction of the axis of the projectile, the forebody of the projectile spins at a low speed or even holds still to improve the control precision of the projectile control system, while the afterbody spins at a high speed maintaining the gyroscopic stability of the projectile. The trajectory filtering performed according to the unscented Kalman filter algorithm can improve the accuracy of measurement data and eliminate the measurement error effectively, so as to obtain more accurate and reliable measurement data.
机译:本文建立了一种新型的自旋弹丸的七自由度弹丸轨迹模型。在此模型的基础上,对弹丸的弹道特性进行了数值分析,并采用无味卡尔曼滤波算法对双旋弹丸的弹道进行了滤波,使弹丸车载设备的测量信息更加准确,更加准确。为制导系统提供了可靠的测量数据。数值模拟表明,双旋转弹丸与传统的旋转弹丸的主要区别在于,在弹丸轴线方向上增加了自由度,弹丸的前体低速旋转甚至保持静止。从而提高了弹丸控制系统的控制精度,同时使残体高速旋转,从而保持了弹丸的陀螺稳定性。采用无味卡尔曼滤波算法进行轨迹滤波,可以提高测量数据的准确性,有效地消除测量误差,从而获得更加准确可靠的测量数据。

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