Abstract: Aiming at the shortcomings of the computational complexity of the Jerk model for highly maneuvering target tracking and the process noise standard deviation of the α-β-γ model must be estimated in advance，a constant gain filtering algorithm is proposed based on the Jerk model which is named as an adaptive α-β-γ-δ model.The computing formulae for α、β、γ and δ are derived theoretically.Finally，the Monte Carlo simulation results to a typical maneuvering movement show the validity of the new algorithm and the far less computational load than Jerk model.

Key words: target tracking, Jerk model, tracking index, α-β-γ-δ filter

摘要： 针对目前高机动目标跟踪的Jerk模型存在计算复杂度高和α-β-γ模型须预先估计过程噪声标准偏差的不足，提出了一种基于Jerk模型的常增益滤波算法：自适应的α-β-γ-δ模型，并从理论上推导出了上述新模型中α、β、γ和δ的计算公式。对一种典型的目标机动形式进行了Monte Carlo仿真，结果表明了新算法对于解决机动目标跟踪问题的有效性，且运算量远远小于Jerk模型算法。

关键词: 目标跟踪, 加加速度模型, 跟踪指标, α-β-γ-δ滤波