使用CBMeMBer过滤器跟踪杂波中的分裂目标

Yifan Xie, H. Kim, T. Song
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引用次数: 0

摘要

在分割目标跟踪中,目标可能会分裂成多个目标,因此快速准确地估计所有目标的状态就变得至关重要。CBMeMBer过滤器的标准公式假设目标出生强度是已知的先验。考虑到目标分裂事件应该是随机的,可以发生在任意位置,这个假设就变得不现实了。本文采用自适应出生分布来解决分裂目标的跟踪问题。结果表明,自适应出生方法更适合于目标分裂问题。通过最优子模式分配(OSPA)度量和基数估计来评估性能。仿真结果表明,自适应出生CBMeMBer在较小的OSPA距离下对基数的变化有较好的响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking splitting targets in clutter using the CBMeMBer filter
For splitting target tracking, the target may split into several such that estimating the states of all targets respon-sively and accurately becomes crucial. The standard formulation of the CBMeMBer filter assumes that the target birth intensity is known as a priori. In consideration of the fact that the target splitting event should be random and could happen at an arbitrary position, this assumption becomes unrealistic. In this paper we apply the adaptive birth distribution to solve the problem of tracking splitting targets. The adaptive birth method is turned out to be more suitable to the splitting target problem. The performance is evaluated by the Optimal Sub-pattern Assignment(OSPA) metric and cardinality estimate. Simulations show that the adaptive birth CBMeMBer is responsive to the changes in cardinality with small OSPA distance.
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