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Survey of multisensor data fusion systems

机译:多传感器数据融合系统概述

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Abstract: Multisensor data fusion involves the integration of data from multiple sensors (and types of sensors) to perform inferences which are more accurate and specific than that available by processing single sensor data. Levels of inference range from target detection and identification to higher level situation assessment and threat assessment. In recent years, data fusion systems have been developed for a variety of applications including IFFN, C3I, tactical resource management, and strategic warning as well as nonmilitary applications. This paper provides a survey of more than 50 data fusion systems and summarizes their application, development environment, and system status, and indicates key techniques utilized. The techniques are mapped to a taxonomy previously developed by Hall and Linn (DFS-90) proceedings). These techniques include positional fusion techniques such as association and estimation, and identify fusion methods, including statistical methods, nonparametric methods, and cognitive-based techniques (e.g., templating, knowledge-based systems, and fuzzy reasoning). An assessment of the state of fusion system development is provided.!
机译:摘要:多传感器数据融合涉及集成来自多个传感器(和传感器类型)的数据,以执行比通过处理单个传感器数据可获得的更为准确和特定的推理。推理级别从目标检测和识别到更高级别的状况评估和威胁评估。近年来,已经为多种应用程序开发了数据融合系统,包括IFFN,C3I,战术资源管理,战略预警以及非军事应用程序。本文提供了对50多个数据融合系统的调查,并总结了它们的应用,开发环境和系统状态,并指出了所采用的关键技术。将该技术映射到Hall和Linn(DFS-90)程序先前开发的分类法中。这些技术包括位置融合技术(例如关联和估计),并标识融合方法,包括统计方法,非参数方法和基于认知的技术(例如,模板,基于知识的系统和模糊推理)。提供了对融合系统开发状态的评估。

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