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Multisensor data fusion for IED threat detection

机译：用于IED威胁检测的多传感器数据融合

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摘要

In this paper we present the multi-sensor registration and fusion algorithms that were developed for a force protection research project in order to detect threats against military patrol vehicles. The fusion is performed at object level, using a hierarchical evidence aggregation approach. It first uses expert domain knowledge about the features used to characterize the detected threats, that is implemented in the form of a fuzzy expert system. The next level consists in fusing intra-sensor and inter-sensor information. Here an ordered weighted averaging operator is used. The object level fusion between candidate threats that are detected asynchronously on a moving vehicle by sensors with different imaging geometries, requires an accurate sensor to world coordinate transformation. This image registration will also be discussed in this paper.
机译：在本文中，我们提出了一种多传感器配准和融合算法，该算法是为部队保护研究项目开发的，目的是检测对军事巡逻车的威胁。使用层次证据聚合方法在对象级别执行融合。它首先使用有关用于表征检测到的威胁的特征的专家领域知识，该知识以模糊专家系统的形式实现。下一级别是融合传感器内和传感器间信息。这里使用了有序加权平均算子。具有不同成像几何结构的传感器在移动的车辆上异步检测到的候选威胁之间的对象级融合需要精确的传感器到世界坐标的转换。此图像配准还将在本文中讨论。

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