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Future electro-optical sensors and processing in urban operations

机译:未来的电光传感器和城市运营的加工

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In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.
机译:在电气光学传感器和城市运营中的处理(ASUO)研究中,我们为欧洲国防局(EDA)电气 - 光学专家(IAP03)铺平了道路,以常识地了解不同的加工功能的最佳分布平台。提出了本地,分布式和集中处理的组合。以这种方式,可以将处理功能匹配到所需的电源和可用的通信系统数据速率,以获得期望的反应时间。在该研究中,定义了三种优先级方案。对于这些场景,研究了当天和未来的传感器和信号处理技术。优先情景是营地保护,巡逻和房屋搜索。已经应用用于分析单个和多传感器系统中信息质量的方法。已经提出并使用了一种估计通过命令链传输数据的反应时间的方法。记录了这些方法,可用于修改方案,或应用于其他方案。现在的数据处理主要是在本地组织的。存在与其他平台的信息交换非常有限;这主要以高信息水平进行。从本日系统和方法的分析产生的主要问题是由于当天传感器的有限视野和缺乏稳健的自动化处理领域而慢的反应时间。然而,在视场传感器的宽和窄场之间的高效切换方案可以减少延迟时间。该研究的主要努力是在未来十到二十年内预测EO传感器的信号处理。在手持式和基于车辆的传感器之间提出了分布式处理。这可以伴随着多个车辆的云处理。另外,为了对源自不同平台的传感器数据进行传感器融合,并充分利用UAV图像,分布式和集中处理的组合至关重要。在未来处理中的异构传感器的传感器融合存在核心作用。由于应用这些新技术的未来城市运营中发生的变化将是提高信息质量,反应时间较短,操作员负荷较低。

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