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Future electro-optical sensors and processing in urban operations

机译:未来的光电传感器及其在城市运营中的处理

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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:在城市运营中的电光传感器和处理(ESUO)研究中,我们为欧洲防卫局(EDA)的电光专家组(IAP03)铺平了道路,以便对不同功能之间的最佳处理功能分配达成共识平台。提出了本地,分布式和集中处理的组合。通过这种方式,可以将处理功能与所需的功率和可用的通信系统数据速率相匹配,以获得所需的反应时间。在研究中,定义了三个优先方案。对于这些情况,研究了当今和未来的传感器和信号处理技术。优先方案是营地保护,巡逻和搜房。已经应用了一种在单传感器和多传感器系统中分析信息质量的方法。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。这些方法已记录在案,可用于修改方案,或应用于其他方案。现今的数据处理主要在本地进行。目前与其他平台的信息交流非常有限;这主要是在较高的信息级别上执行的。当今系统和方法的分析引起的主要问题是由于当今传感器的视野有限以及缺乏可靠的自动处理而导致反应时间缓慢。然而,宽视野传感器和窄视野传感器之间的有效切换方案可以减少延迟时间。该研究的主要工作是预测未来10至20年内EO传感器的信号处理。建议在手持式传感器和基于车辆的传感器之间进行分布式处理。这可以伴随几辆车上的云处理。此外,要对源自不同平台的传感器数据进行传感器融合,并充分利用无人机图像,必须将分布式处理与集中式处理相结合。异类传感器的传感器融合在将来的处理中起着核心作用。由于这些新技术的应用,未来城市运营中发生的变化将是提高信息质量,缩短响应时间,降低操作员负担。

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