基于串行重采样改进的检测前跟踪算法研究

针对基于粒子滤波的弱小目标检测前跟踪算法(Particle Filter Track Before Detect， PF-TBD)存在采样粒子数目随空间维数呈指数增长、计算量急剧增加等问题，提出一种基于串行重采样改进的检测前跟踪算法(Serial Resampling Track Before Detect, SR-TBD)。所提算法通过对粒子状态的位置空间与速度空间进行串行采样，实现搜索帧间能量的有效积累，并降低状态维数造成计算量的增加，提升算法收敛速度。通过算法仿真与传统 PF-TBD 算法对比，表明本文提出的改进算法在算法收敛速度、运算量等方面均得到提升。

Research on Improved Tracking-Before-Detection Algorithm Based on Serial Resampling

Aiming at the problem of particle filter track before detect (PF-TBD) based on small target, the number of sampling particles increases exponentially with the spatial dimension, and the calculation volume increases sharply. This paper proposes an improved tracking algorithm named serial resampling track before detect (SR-TBD). The proposed algorithm serially samples the position space and velocity space of the particle state to realize the effective accumulation of energy between search frames, and reduce the number of states to increases the amount of calculation, and improves the convergence speed of the algorithm. The comparison between algorithm simulation and traditional algorithm shows that the improved algorithm proposed in this paper has been improved in terms of convergence speed and calculation volume.