点目标和扩展目标共存的Poisson多Bernoulli混合滤波器
A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
摘要：
针对点目标和扩展目标共存的情况，提出了一种泊松多伯努利混合（Poisson multi-Bernoulli mixture，PMBM）滤波器，用于可能同时存在点目标和扩展目标的情况。PMBM滤波器提供了一个递归来计算多目标滤波后验的基础上的数据关联的概率信息，和单目标的预测和更新。在本文中，我们首先推导出PMBM滤波器更新的广义测量模型，其中可以包括测量起源于点和扩展的目标。其次，我们提出了一个同时容纳点目标和扩展目标的单目标空间，并推导出传播点目标高斯密度和扩展目标伽马高斯逆Wishart密度的滤波递归。作为一个计算效率的近似PMBM过滤器，我们还开发了一个泊松多伯努利（PMB）过滤器共存的点和扩展的目标。由此产生的过滤器进行了分析，通过数值模拟。
英文摘要：
This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter for coexisting point and extended targets, i.e., for scenarios where there may be simultaneous point and extended targets. The PMBM filter provides a recursion to compute the multi-target filtering posterior based on probabilistic information on data associations, and single-target predictions and updates. In this paper, we first derive the PMBM filter update for a generalised measurement model, which can include measurements originated from point and extended targets. Second, we propose a single-target space that accommodates both point and extended targets and derive the filtering recursion that propagates Gaussian densities for point targets and gamma Gaussian inverse Wishart densities for extended targets. As a computationally efficient approximation of the PMBM filter, we also develop a Poisson multi-Bernoulli (PMB) filter for coexisting point and extended targets. The resulting filters are analysed via numerical simulations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
