针对非均匀稀疏采样环境下的被动机动目标跟踪问题,提出了一种新的自适应α-β滤波算法。算法首先在最小均方误差准则下,推导了α-β滤波器的最优参数选择方法;然后详细分析了非均匀稀疏采样被动传感器上报数据的特点,提出利用上报时间间隔和目标速度来设计跟踪指数,且根据被动传感器系统的实际观测情况,推导了观测误差标准差的表达式;最后,在保证算法稳定性的前提下,给出了自适应滤波器参数设计方法。实验结果表明,提出算法能够准确对机动目标进行跟踪,性能要好于工程中常用的α-β滤波器,且算法设计简单,能够工程实现。 Aiming at the problem of passive maneuvering target tracking under non-uniform sparse sampling, a new adaptive α-β filtering algorithm is proposed. The algorithm first derives the optimal parameter selection method of α-β filter under the minimum mean square error criterion. Then, the characteristics of non-uniform sparse sampling passive sensor are analyzed in detail. It is proposed to use the reporting time interval and target speed to design tracking According to the actual observation of the passive sensor system, the expression of the standard error of observation error is deduced. Finally, the design method of adaptive filter parameters is given on the premise of ensuring the stability of the algorithm. The experimental results show that the proposed algorithm can accurately track the maneuvering target, the performance is better than the α-β filter commonly used in engineering, and the algorithm is simple in design and can be implemented in engineering.