非均匀稀疏采样环境自适应α-β滤波算法

Adaptive α-β Tracking Filter Algorithm in Aperiodic Sparseness Sampling Environment

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。

A new adaptive α-β tracking filter algorithm for maneuvering target tracking was proposed in Aperiodic Sparseness Sampling Environment.Firstly,according to the principle of the Minimum Mean Square Error（MS）,the optimal parameter design method was derived.Secondly,the characteristic of the measurement information of the passive sensors was analyzed,a new design method of the tracking index based on the time interval and the target velocity was proposed.Finally,the parameters of the adaptive α-β tracking filter were def＇med. The experiment results show that the proposed algorithm results in more accurate tracking than the existing one, and can be applied for maneuvering target tracking.