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“当前”统计模型是较好的机动目标跟踪模型。为了更好地实现对机动目标的跟踪,针对该模型存在机动频率离线确定和加速度上限固定2个问题,利用卡尔曼滤波过程中的新息向量和其协方差的变化,对机动频率参数进行自适应调整;依据加速度增量与位置增量之间函数关系,构造调整因子对加速度上限进行自适应调整。进一步,通过交互式多模型算法,将“改进”的当前统计模型和匀速模型相结合,弥补单一模型的缺点,以其对更加复杂多变的目标运动实现有效地跟踪。
The “current” statistical model is a good maneuvering target tracking model. In order to realize the tracking of the maneuvering target better, two problems are solved: the maneuvering frequency is off-line and the upper limit of acceleration is fixed. Based on the change of the interest vector and its covariance in the Kalman filter, Adapt and adjust; According to the function relation between the increment of acceleration and increment of position, adjust the adjustment factor to adjust the upper limit of acceleration adaptively. Further, through the interactive multi-model algorithm, the current statistical model of “improvement ” is combined with the uniform velocity model to make up for the shortcoming of the single model and to effectively track the more complex and changeable target movement.