论文标题
有限的视野和负面信息在有限集统计（FISST）中的作用
The Role of Bounded Fields-of-View and Negative Information in Finite Set Statistics (FISST)
论文作者
论文摘要
负面信息的作用对于搜索检测 - 轨道问题的作用尤其重要，在搜索检测轨道问题中，对象数量尚不清楚，并且传感器视野的大小远小于感兴趣区域的大小。本文介绍了一种系统地结合视野几何形状以及位置和对象包含/排除证据的方法，并将其随机有限设置为多目标基数分布。该方法是针对一组代表性的多对象分布的，并通过传感器计划问题进行了证明，该问题涉及多个bernoulli过程，最多有100个潜在的目标。
The role of negative information is particularly important to search-detect-track problems in which the number of objects is unknown a priori, and the size of the sensor field-of-view is far smaller than that of the region of interest. This paper presents an approach for systematically incorporating knowledge of the field-of-view geometry and position and object inclusion/exclusion evidence into object state densities and random finite set multi-object cardinality distributions. The approach is derived for a representative set of multi-object distributions and demonstrated through a sensor planning problem involving a multi-Bernoulli process with up to one-hundred potential targets.
