一种新的基于似然比的弱目标TBD方法

在当前基于粒子滤波的检测前跟踪(PF-TBD)算法中,通常是利用累积似然比去检测目标,由于能量累积的效果,无法快速检测到目标的消失。针对这个问题,提出了一种新的基于似然比的检测前跟踪方法。该方法运用单个时刻的似然比进行目标有无判别,并结合多个连续时刻的判别结果给出最终的目标检测结果。仿真结果表明,与传统的基于似然比的弱目标检测前跟踪方法相比,该方法能够减小目标出现时的检测延时,并且能够有效地检测到目标消失。

A Novel Track-Before-Detect Method for Weak Target Based on Likelihood Ratio

In the current particle filter tracking before detection algorithm（PF-TBD）, the target is usually detected by cumulative likelihood ratio. It is unable to detect the disappearance of the target rapidly because of the cumulative effect. A novel track-before-detect method based on likelihood ratio is proposed to solve this problem. The proposed method utilizes single-moment likelihood ratio to mark target with presence or absence, and the final test result is obtained using several continuous marks. Simulation results demonstrate that the proposed method is able to lessen detecting delay when target appears and can detect the disappearance of the target effectively.