Bayesian Multi-sensor Data Fusion for Target Identification - Applications in Naval and Ground based Command and Control Systems

Albert Bodenmüller
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引用次数: 2

Abstract

Military Command and Control Systems have to deal with a wide range of different sensors and sources. Besides traditional information sources like IFF, Tactical Data Links and ESM sensors additional sources like AIS, Blue Force Tracking and GMTI Radar become important sources for target identification and classification. A correct identification is an important prerequisite to prevent fratricide and civilian collateral damages and to complete the Situational Awareness. This paper gives an overview of our solution for the extension of the Bayesian identification process in order to establish a tactical picture for naval but also for air and ground targets. For some sensors and important identification source like Automatic Identification System (AIS), Automatic Target Recognition (ATR) and GMTI Radar our solution approach will be
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目标识别的贝叶斯多传感器数据融合-在海军和地面指挥和控制系统中的应用
军事指挥和控制系统必须处理各种不同的传感器和信号源。除了IFF、战术数据链和ESM传感器等传统信息源外,AIS、蓝军跟踪和GMTI雷达等其他信息源也成为目标识别和分类的重要信息源。正确识别是防止自相残杀和平民附带伤害,完成态势感知的重要前提。本文概述了我们对贝叶斯识别过程扩展的解决方案,以便为海军、空中和地面目标建立战术图像。对于一些传感器和重要的识别源,如自动识别系统(AIS),自动目标识别(ATR)和GMTI雷达,我们的解决方案将是
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