基于Kalman 滤波算法对运动目标射击研究

针对传统炮兵对运动目标射击时间长、精度低的问题，提出采用卡尔曼滤波对目标运动状态进行准确估计。分析卡尔曼滤波算法的特点，采用预测—更新的递推算法，以某装甲目标为例求取系统状态估计值，并对运动目标射击中的应用进行研究。仿真结果表明：该算法能对目标运动状态进行快速准确的估计，大大提高炮兵火力反应速度和射击精度，有效地提高炮兵作战效能。

Research of Firing at Moving Target Based on Kalman Filtering Algorithm

Aiming at the shortage of long time and low accuracy of traditional artillery firing at moving target, put forward to make use of Kalman filtering algorithm to estimate the moving target state accurately. Analyze the characteristics of the Kalman filtering algorithm, calculate the estimation of an armored target state by using the predicting-updating recursion algorithm, and study the application of moving target shooting. The result proves that the Kalman filtering algorithm can estimate the moving target state quickly and accurately, makes the speed and accuracy of artillery’s firepower greatly improve, raises the weapon system’s battle efficiency of artillery effectively.