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Quantifying the Benefit of Airborne and Ground Sensor Fusion for Target Detection

机译:量化机载和地面传感器融合对目标检测的好处

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In this paper, a study involving the detection of buried objects by fusing airborne Multi-Spectral Imagery (MSI) and ground-based Ground Penetrating Radar (GPR) data is investigated. The benefit of using the airborne sensor to cue the GPR, which will then search the area indicated by the MSI, is investigated and compared to results obtained via a purely ground-based system. State-of-the-art existing algorithms, such as hidden Markov models will be applied to the GPR data both in queued and non-queued modes. In addition, the ability to measure disturbed earth with the GPR sensor will be investigated. Furthermore, state-of-the-art algorithms for the MSI system will be described. These algorithms require very high detection rates with acceptable false alarm rates in order to serve as an acceptable system. Results will be presented on data collected at outdoor testing and evaluation sites.
机译:本文研究了一项涉及通过融合机载多光谱图像(MSI)和地基探地雷达(GPR)数据检测掩埋物体的研究。研究了使用机载传感器提示GPR的好处,该GPR然后将搜索MSI指示的区域,并将其与通过纯地面系统获得的结果进行比较。现有的最新算法(例如隐马尔可夫模型)将以排队和非排队模式应用于GPR数据。此外,还将研究使用GPR传感器测量受干扰的地球的能力。此外,将描述MSI系统的最新算法。这些算法需要很高的检测率和可接受的误报率,才能用作可接受的系统。结果将显示在户外测试和评估站点收集的数据上。

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