多目标干扰环境中威胁目标自动跟踪方法

针对多目标干扰环境中威胁目标发现与跟踪困难的问题,研究一种基于随机有限集(RFS)的高斯混合概率密度假设(GM-PHD)滤波的算法,建立目标的随机有限集形式的运动和观测模型,利用卡尔曼滤波的预测和更新过程,对被动声呐输出的多目标方位和窄带线谱同时进行跟踪,利用所提取窄带线谱能量作为不同方位目标的输出检测量,可实现对包含线谱的窄带威胁目标的自动跟踪。试验数据的处理结果表明,所提方法可以实现在多目标的复杂情况下对感兴趣的威胁目标的自动跟踪。

Threat target automatic tracking method in multi-target jamming environment

Aiming at the difficulty of detecting and tracking threat targets in the multi-target interference environment,an algorithm based on the Gaussian mixture probability density hypothesis filtering algorithm of random finite set is studied,the motion and observation model of the target's random finite set form is established,and Kalman filter is used.The prediction and update process of the passive sonar can simultaneously track the multi-target azimuth and narrow-band line spectrum energy as the output detection quantity of different azimuth targets,which can realize the automatic tracking of the narrow-band threat target containing the line spectrum.The processing results of the experimental data show that the proposed method can realize the azimuth tracking of the threat target of interest in the complex situation of multiple targets.