目标数未知时基于粒子滤波的多目标TBD方法

发布时间：2018-06-26 03:52

  本文选题：粒子滤波 + 多目标　； 参考：《信号处理》2017年09期

【摘要】：针对现有粒子滤波微弱多目标检测前跟踪(TBD)算法要求目标数目或者目标最大数目已知,且无法对邻近微弱目标有效检测的不足,提出了一种基于粒子滤波和目标相继消除(PF-STC)的多目标TBD算法。该算法通过将多目标状态的联合搜索过程简化为多个独立的单目标检测过程,实现数目未知的多目标跟踪和检测。与现有粒子滤波多目标TBD算法相比,新算法克服了现有方法在较弱目标接近较强目标时出现的检测困难,并降低了算法复杂度,能对数目未知的微弱多目标进行有效检测。
[Abstract]:The existing particle filter pre-tracking (TBD) algorithm for weak multi-target detection requires that the number of targets or the maximum number of targets are known and can not be effectively detected for adjacent weak targets. A multi-target TBD algorithm based on particle filter and target successive cancellation (PF-STC) is proposed. The algorithm simplifies the joint search process of multi-target states into several independent single-target detection processes to achieve the unknown number of multi-target tracking and detection. Compared with the existing particle filter multi-target TBD algorithm, the new algorithm overcomes the difficulty of detection when the weak target is close to the stronger target, reduces the complexity of the algorithm, and can effectively detect the unknown number of weak multi-targets.
【作者单位】： 中国人民解放军92493部队98分队;海军航空工程学院信息融合研究所;
【基金】：国家自然科学基金(61179018,61671462)
【分类号】：TN713;TP212
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本文编号：2068958