一种基于粒子滤波的双极化雷达检测前跟踪算法

针对雷达在低信噪比（signal to noise ratio，SNR）条件下对运动目标的检测和跟踪难题，提出了一种基于粒子滤波（particle filter，PF）的双极化雷达运动目标检测前跟踪（track before detect，TBD）算法，又称联合粒子滤波检测前跟踪（joint particle filter-track before detect，JPF-TBD）方法.该算法借鉴传统的TBD算法处理框架，以经典PF算法为基础，使用双通道幅度相位似然比函数计算粒子权值，并实现了完整的PF过程.与同类研究相比，所提算法能够充分利用双极化雷达各通道幅度和相位信息，进一步扩展了PF算法的应用范围.仿真实验表明:在SNR>10 dB，虚警概率为10-6的情况下所提算法对目标的检测概率大于0.8.

The algorithm of track before detect using particle filter for dual-polarized radar

On the condition of dual-polarized mode, the radar may suffer from the noise and the clutter, and it poses a significant challenge to detecting and tracking weak targets. To address this problem, a novel joint particle filter algorithm, which can handle dual-polarized data of weak target, is proposed. The algorithm is prepared from the framework of particle filter track before detect (PF-TBD) filter, and it is implemented by firstly adopting a dual-polarized likelihood ratio function (LRF), which can greatly improve the performance of PF-TBD. Compared with classic method, the new approach combines the dual-polarized data with PF-TBD, which provides a new way to such problems, avoiding the loss tracking of the weak target with lower signal to noise ratio (SNR).When SNR>10 dB and the false alarm probability is less than 10-6, the target detection probability can be above 0.8.