Abstract: An adaptive adjustment method of maneuvering frequency is researched in this paper to match the actual maneuvering situation based on the “current” statistical model. An adaptive algorithm of dual maneuvering frequency is proposed based on the different effects to gains of maneuvering frequency in the noise variance and the state transition matrix. Simulation results show the adaptive algorithm can quickly track the target whose acceleration is jumping, and improve the estimated accuracy of position greatly.

Key words: maneuvering target tracking, “current” statistical model, adaptive Kalman filtering, Monte Carlo simulation

摘要： 基于当前统计模型，研究机动目标跟踪过程中机动频率的自适应调整方法，使其值更加符合目标的实际机动状况。根据机动频率在噪声方差及状态转移矩阵中对增益的影响不同，设计一种双机动频率自适应算法。仿真表明，该自适应算法能快速跟踪加速度跳跃的机动目标，跟踪机动目标位置精度上有较大的改进。

关键词: 机动目标跟踪, “当前”统计模型, 自适应卡尔曼滤波, 蒙特卡罗仿真