An Estimation Algorithm of Maneuvering Target Movement Elements
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摘要: 对于机动目标的运动要素估计, 当前运用较多的是基于匀加速模型的卡尔曼滤波方法, 但由于卡尔曼滤波器本身的缺陷, 该方法只适用于目标做匀加速直线运动的情况, 而无法对目标做转弯运动时的运动要素进行有效估计。为了克服这个问题, 文中提出了一种机动目标运动要素的估计算法, 通过对卡尔曼滤波协方差阵的定期重置, 使得增益矩阵的绝对值始终保持在较大的状态, 对估计值的修正效果始终处于一个较好的水平, 最终解决包含转弯运动在内的机动目标运动要素的估计问题。数学仿真结果表明, 所设计的估计算法对机动目标具有较强的跟踪能力, 满足了估计误差要求, 该方法简单可行, 易于工程实现。Abstract: For estimation of maneuvering target movement elements, the Kalman filter method based on the uniform acceleration model has more applications, however, due to the defect of Kalman filter itself, this method is only applicable to the target with uniform acceleration in the straight line movement situation, but is impossible to estimate the motion elements of the target in turning. In order to overcome this problem, an estimation algorithm of maneuvering target movement elements is proposed in this paper. Through periodic reset of the covariance matrix of Kalman filtering, the algorithm can make the absolute value of the gain matrix always keep larger, make the correction effect of estimation at a satisfactory level, and ultimately solve the estimation problem of maneuvering target movement elements including turning movement. Mathematical simulation results show that the proposed estimation algorithm has strong tracking ability for maneuvering target, and meets the requirement of estimation error. It is simple and easy to be realized in engineering.
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