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本文提出了一种新的机动目标自适应跟踪卡尔曼滤波器。其基本思想是:通过统计方法录取加速度数据,实时建立其AR模型,通过前、后项预测作机动指令估计。由于选择了新的机动加速度量,从而得出线性的状态方程,由机动指令的实时估计得到机动目标自适应跟踪卡尔曼滤波器。 在PC—8000开发系统上的数字仿真结果表明其在各种机动情况下都具有较高的距离、速度和加速度估计精度。
This paper presents a new maneuvering target adaptive tracking Kalman filter. The basic idea is: through the statistical methods to take acceleration data, real-time to establish its AR model, through the front and back of the forecast for maneuver instruction estimation. Due to the selection of a new maneuvering acceleration, a linear state equation is obtained, and a maneuvering target adaptive tracking Kalman filter is obtained from the real-time estimation of maneuvering commands. The numerical simulation results on PC-8000 development system show that it has higher accuracy of distance, velocity and acceleration estimation under various maneuvering conditions.