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Operator Use of Multi-Sensor Data Fusion for Airborne Picture Compilation

机译:操作员使用多传感器数据融合进行机载图像编译

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A study was conducted to examine the operational use of multi-sensor data fusion for military airborne intelligence, surveillance and reconnaissance. Participants performed a simulated picture compilation task wherein they had to identify all ships and planes in their area of operation using various sensors. One group performed the task using only native sensor data. The second group had imperfect data fusion to help them resolve the kinematic information, but they still had to identify each contact. The results indicated that data fusion automation improved the identification of ships and planes over the native sensor group. However, over time, map clutter continually increased for the group with fusion automation, surpassing the clutter for the native sensor group. The results suggest that while multi-sensor data fusion has benefits for picture compilation, dealing with plot clutter from false and spurious tracks is a key concern. Interface suggestions are provided to mitigate the effects.
机译:进行了一项研究,以检查用于军用空中智能,监测和侦察的多传感器数据融合的操作使用。参与者执行了模拟的图像编译任务,其中它们必须使用各种传感器识别其操作领域的所有船舶和平面。一组仅使用本机传感器数据执行任务。第二组具有不完美的数据融合,以帮助他们解决运动信息,但它们仍然必须识别每个联系人。结果表明,数据融合自动化在原生传感器组上改进了船舶和平面的识别。然而,随着时间的推移,对于具有融合自动化的组,地图杂乱不断增加,超过原生传感器组的杂波。结果表明,虽然多传感器数据融合对图像编译有益,但是从虚假和虚假轨道处理绘图杂乱是关键问题。提供了接口建议以减轻效果。

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