A novel passive TBD algorithm based on phase correction and observability of moving targets under bistatic observation

A novel Track Before Detect (TBD) algorithm in this work is presented to investigate the target tracking problem under bistatic observation conditions with passive receivers. The proposed algorithm involves deriving Resolution Unit Motion (RUM) model and likelihood of Phase Deviation from Central Mean (PDCM), and utilizing Labeled Multi-Bernoulli (LMB) filter to realize TBD, referred to as the RUM-PDCM-LMB-TBD algorithm. Firstly, a new RUM model for RD (Range Doppler) map is proposed to optimize filtering parameters of LMB-TBD and make more effective use of Doppler information. Additionally, by deriving the phase characteristic distribution of the target, a likelihood function model of PDCM is developed to incorporate the phase information of measurements into the proposed algorithm. Subsequently, to improve the accuracy and stability of target state estimation, these two models, i.e., RUM and PDCM, are combined. Furthermore, via jointly performing TBD and DBT (Detect Before Track) in a single passive radar system, this work elaborates on how to achieve state estimation in Cartesian coordinates; simultaneously, the observability conditions of target states under the bistatic observation model are analyzed in depth. Finally, the effectiveness of the proposed RUM-PDCM-LMB-TBD algorithm is validated through experiments, and the influencing factors of DBT on estimation accuracy are thoroughly analyzed.