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.