基于标签多伯努利滤波器的机动小目标检测前跟踪

标签多伯努利(LMB)滤波器在传统多伯努利滤波器基础上引入标签空间,能够实现真正意义上的多目标轨迹级滤波.文章对红外小目标的运动和量测进行建模,将标签多伯努利应用到红外小目标检测前跟踪领域.在此基础上,为了实现对运动模型时变目标的检测前跟踪,将交互式多模型(IMM)与LMB检测前跟踪算法相结合,提出IMM-LMB检测前跟踪算法.此外,给出了该算法的序贯蒙特卡罗实现.仿真结果表明,所提算法能够从输入的原始图像中直接实现轨迹级多目标检测和跟踪,且能够在线更新多模型概率,更好的适应多机动目标场景.

Track-before-detect for maneuvering small targets based on Labeled Multi-Bernoulli filter

Labeled Multi-Bernoulli (LMB) filter was proposed based on classic Multi-Bernoulli filter by taking label space into account. It is a true trajectory filter in comparison with other methods. The motion model and measurement model of infrared small targets were studied. The LMB Track-Before-Detect algorithm was applied to detect and track infrared small targets. In order to detect and track multiple maneuvering targets with time-varying motion models, an IMM-LMB Track-Before-Detect algorithm was proposed by integrating the interacting multiple models (IMM) with LMB Track-Before-Detect filter. The sequential Monte Carlo (SMC) implementation for IMM-LMB track-before-detect was also given. Simulation results demonstrate that the proposed algorithm can detect and track multi-targets trajectories from raw image. In addition, it can update the model probability in an online way, which detects and tracks maneuvering targets adaptively.