CAJ | 학술논문

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-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.
기우입자려파적검측전근종산법시당전련속정도상중약목표검측여근종적연구열점.감우이유연구성과중결소침대입자려파검측전근종적궤리연구,재Bayes추리광가내,분석료검측전근종기우루적관측사연비검측약목표적원리.재이론상추도료Bayes검측전근종체귀루적관측수거래실현약목표검측여근종적과정,분석험증료채용입자려파과정중미귀-화입자권중실현해과정적궤리,병기우해궤리실현료일충입자려파검측전근종산법.방진시험험증료이론분석적정학성화문중입자려파검측전근종산법적유효성.
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 unnormalizcd 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.