Dynamic particle allocation for CB-MeMBer filter
Dynamic particle allocation for CB-MeMBer filter
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DOI：
10.1109/icics.2015.7459929
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
Kuan Han;Zhongya Qin;Xiaoding Gao;Mengjun Jin;Zhiguo Shi
中科院分区：
文献类型：
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作者：
Kuan Han;Zhongya Qin;Xiaoding Gao;Mengjun Jin;Zhiguo Shi
针对多目标跟踪问题，提出了一种基于粒子CB-MeMBer滤波的粒子分配方法。考虑到粒子分布的不确定性和每个目标的存在概率，我们将粒子CB-MeMBer滤波器的重采样步骤与所提出的粒子分配相结合，使系统的多目标滤波失真在理论上最小。此外，我们还设计了该方法的硬件结构，并讨论了如何优化该方法的资源利用。仿真结果表明，采用所提出的粒子分配方法的粒子CB-MeMBer滤波器比均匀分配方法具有更好的滤波性能，特别是在粒子总数有限的情况下。
In this paper, we propose a particle allocation approach in the particle CB-MeMBer Filter for multi-target tracking (MTT). Considering the particle distribution uncertainty and existence probability of each target, we combine the re-sampling step of particle CB-MeMBer filter with the proposed particle allocation, resulting in the theoretically minimum multi-target filtering distortion for the system. Furthermore, we design a hardware structure of the proposed particle allocation approach and discuss how to optimize the resource usage in it. Simulation results show that particle CB-MeMBer filter with the proposed particle allocation approach has better filtering performance than that of the equally allocating approach, especially when the total number of particles is limited.