An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering
An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering
复制标题
用于多目标滤波的高效测量驱动顺序蒙特卡罗多伯努利滤波器
DOI：
10.1631/jzus.c1400025
复制
发表时间：
2014
影响因子：
--
通讯作者：
Zhang Sen-lin
中科院分区：
文献类型：
--
作者：
Jiang Tong-yang;Liu Mei-qin;Wang Xie;Zhang Sen-lin
提出了一种有效的测量驱动的序贯蒙特卡罗多伯努利（SMC-MB）滤波器的多目标滤波中存在的杂波和丢失检测。使用门控技术将存活和出生测量与原始测量区分开。然后，生存测量用于更新生存和出生目标，出生测量用于仅更新出生目标。由于大多数杂波测量不参与更新步骤，计算时间显着减少。仿真结果表明，该方法在不降低滤波性能的前提下，提高了系统的实时性。
We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli (SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are distinguished from the original measurements using the gating technique. Then the survival measurements are used to update both survival and birth targets, and the birth measurements are used to update only the birth targets. Since most clutter measurements do not participate in the update step, the computing time is reduced significantly. Simulation results demonstrate that the proposed approach improves the real-time performance without degradation of filtering performance.