密集杂波环境下确定性退火DA-HPMHT跟踪算法

摘要

在对Homothetic概率多假设跟踪（ probabilistic multiple hypothesis tracking， PMHT）和确定性退火（deterministic annealing， DA）技术深入研究的基础上，结合扩展卡尔曼算法，提出了DA⁃HPMHT算法。针对密集杂波环境对多目标跟踪性能的影响，给出了DA⁃HP MHT算法在匀速直线交叉运动目标，机动转弯目标和匀速直线邻近目标的仿真实验，并同HP MHT算法进行了仿真比较。仿真结果表明，在初始值与真实值相差较大的情况下，HPMHT算法跟踪性能下降，而DA⁃HPMHT算法仍能保持较好的跟踪精度，并且满足实时性要求，证明DA⁃HP MHT算法对密集杂波环境下多机动目标跟踪的有效性。%Based on the principle of the homothetic probabilistic multiple hypothesis tracking ( HPMHT) , the de⁃terministic annealing ( DA) approach, and the extended Kalman filter, we propose a new multitarget tracking algo⁃rithm DA⁃HPMHT. We compare and analyze the estimation accuracy of DA⁃HPMHT in simulation experiments for uniform linear crossover movement targets, maneuvering turning crossover targets and uniform linear closely spaced targets under the dense clutter environment. The experimental results demonstrate HPMHT algorithm′s performance degrades when the initial value differs from its real value, but the DA⁃HPMHT algorithm still has good tracking ac⁃curacy and can meet real time requirement at the same time;this confirms the effectiveness of the DA⁃HPMHT in multiple maneuvering target tracking under dense clutter environment.