基于粒子滤波的检测前跟踪算法是当前连续帧图像中弱目标检测与跟踪的研究热点。鉴于已有研究成果中缺少针对粒子滤波检测前跟踪的机理研究，在Bayes推理框架内，分析了检测前跟踪基于累积观测似然比检测弱目标的原理。在理论上推导了Bayes检测前跟踪递归累积观测数据来实现弱目标检测与跟踪的过程，分析验证了采用粒子滤波过程中未归一化粒子权重实现该过程的机理，并基于该机理实现了一种粒子滤波检测前跟踪算法。仿真试验验证了理论分析的正确性和文中粒子滤波检测前跟踪算法的有效性。

Particle filter based track-before-detect (PF-TBD) is an active research topic on detection and tracking for dim targets in sequential frame images currently. Whereas there is absent of study on mechanism of PF-TBD in existing work, the principle of TBD which is based on cumulative measurement likelihood ratio to detect dim targets is analyzed in Bayesian inference framework. The course of detection and tracking of dim targets using Bayesian TBD which is based on recursively cumulate measurements is educed and the mechanism which realizes it by unnormalized particles′ weights in particle filter processing is analyzed and confirmed in theory. A PF-TBD algorithm is presented based on this mechanism. Simulation results show that the analysis is valid and PF-TBD algorithm in this paper is efficient.