A decentralized Poisson multi-Bernoulli filter is proposed to track multiple vehicles using multiple high-resolution sensors. Independent filters estimate the vehicles' presence, state, and shape using a Gaussian process extent model; a decentralized filter is realized through fusion of the filters posterior densities. An efficient implementation is achieved by parametric state representation, utilization of single hypothesis tracks, and fusion of vehicle information based on a fusion mapping. Numerical results demonstrate the performance.

中文翻译：

---

车辆跟踪的分散泊松多伯努利滤波

提出了一种分散式泊松多伯努利滤波器，用于使用多个高分辨率传感器跟踪多辆车辆。独立滤波器使用高斯过程范围模型估计车辆的存在、状态和形状；通过融合滤波器后验密度来实现分散滤波器。通过参数化状态表示、单个假设轨迹的利用以及基于融合映射的车辆信息融合来实现有效的实现。数值结果证明了性能。