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Real-time imaging systems' combination of methods to achieve automatic target recognition

机译:实时成像系统的组合方法实现自动目标识别

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Using a combination of strategies real time imaging weapons systems are achieving their goals of detecting their intended targets. The demands of acquiring a target in a cluttered environment in a timely manner with a high degree of confidence demands compromise be made as to having a truly automatic system. A combination of techniques such as dedicated image processing hardware, real time operating systems, mixes of algorithmic methods, and multi-sensor detectors are a forbearance of the unleashed potential of future weapons system and their incorporation in truly autonomous target acquisition. Elements such as position information, sensor gain controls, way marks for mid course correction, and augmentation with different imaging spectrums as well as future capabilities such as neural net expert systems and decision processors over seeing a fusion matrix architecture may be considered tools for a weapon system's achievement of its ultimate goal. Currently, acquiring a target in a cluttered environment in a timely manner with a high degree of confidence demands compromises be made as to having a truly automatic system. It is now necessary to include a human in the track decision loop, a system feature that may be long lived. Automatic Track Recognition will still be the desired goal in future systems due to the variability of military missions and desirability of an expendable asset. Furthermore, with the increasing incorporation of multi-sensor information into the track decision the human element's real time contribution must be carefully engineered.
机译:使用策略的组合实时成像武器系统正在实现检测其预期目标的目标。以高度置信度要求在杂乱环境中获取杂乱环境中的目标的要求妥协是具有真正的自动系统。诸如专用图像处理硬件,实时操作系统,算法方法和多传感器检测器的组合,以及多传感器检测器是未来武器系统的贫困潜力的宽容及其在真正自主目标习得中的融合。诸如位置信息,传感器增益控制的元素,用于中间校正的方式标记,以及使用不同的成像频谱的增强以及未来的能力,如神经网络专家系统和在看融合矩阵架构上看,可以被视为武器的工具系统实现其最终目标。目前,以高度置信度要求在具有高度置信环境中获取杂乱环境中的目标,以便具有真正的自动系统。现在有必要在轨道决策循环中包含一个人类,这是一个可能长期存在的系统功能。由于军事任务的可变性和消耗性资产的可取性,自动轨道识别仍将是未来系统中的预期目标。此外,随着多传感器信息的增加进入轨道决定,人体元素的实时贡献必须仔细设计。

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