多传感器目标识别系统

A. Forman, D.B. Brown, J. Hughen, R.R. Pressley, A. R. Sanders, D. Sullivan
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引用次数: 4

摘要

介绍了美国高级研究计划局(ARPA)的多传感器目标识别系统(MUSTRS)。智能传感器管理器控制前视红外(FLIR)和毫米波(MMW)雷达传感器,以获得对地面目标的多重观察。红外图像中的目标识别使用最小平均相关能(MACE)滤波的变化和/或基于模型的算法称为关键特征。雷达数据采用二次距离复合滤波技术进行处理。证据是用贝叶斯方法组合的。该系统能够以极低的虚警率对时间关键型移动目标进行正确的分类。
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MUltiSensor Target Recognition System (MUSTRS)
The paper describes the Advanced Research Projects Agency (ARPA) MUltiSensor Target Recognition System (MUSTRS). A smart sensor manager controls forward-looking infrared (FLIR) and millimeter wave (MMW) radar sensors to obtain multiple looks at targets on the ground. Targets in IR images are recognized using a variation on minimum average correlation energy (MACE) filtering and/or a model-based algorithm called key features. Radar data are processed using quadratic distance composite filtering techniques. Evidence is combined using a Bayesian method. The system has been designed to correctly classify time critical mobile targets with very low false alarm rates.<>
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