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Real-time identification of fixed targets

机译:实时识别固定目标

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Abstract: Fixed targets such as bridges, airfields, and buildings are of military significance and their value is constantly being appraised as the battle scenario evolves. For examples, a building thought to be of no significance may be reappraised, through intelligence reports, as a military command center. The ability to quickly strike these targets with a minimal amount of a priori information is necessary. The requirements placed on such a system are: (1) Rapid turnaround time from the moment the decision is made to attack. Depending on the user organization, this time ranges from fifteen minutes to twelve hours. (2) Minimal a priori target information. There is likely to be no imagery data base of the target, and the system may be required to operate with as little information as an overhead photograph. (3) Real time recognition of the target. Terminal guidance of the weapons delivery system to a specified destructive aimpoint of will be impacted by the recognition system. (4) Flexibility to attack a variety of targets. A data base of known high value fixed targets (HVFT) may be stored, but the sudden inclusion of new targets must be accommodated. This paper will discuss a real time implementation of a model based approach to automatically recognize high value fixed targets in forward looking infrared (FLIR) imagery. This approach generates a predictive model of the expected target features to be found in the image, extracts those feature types from the image, and matches the predictive model with the image features. A generic approach to the description of the target features has been taken to allow for rapid preparation of the models from minimal a priori target information. The real time aspect has been achieved by implementing the system on a massively parallel single instruction, multiple data architecture. An overview of an entire system approach to attack high value fixed targets will be discussed. The automatic target recognizer (ATR), which is a part of this system, will be discussed in detail and results of the ATR operating against HVFT in FLIR imagery will be shown.!4
机译:摘要:诸如桥梁,飞机场和建筑物之类的固定目标具有军事意义,并且随着战斗情况的发展,其价值也不断得到评估。例如,可以通过情报报告重新评估被认为无关紧要的建筑物作为军事指挥中心。必须具有以最少数量的先验信息快速达到这些目标的能力。对这样的系统的要求是:(1)从做出攻击决定之时起就需要快速的周转时间。根据用户组织的不同,该时间范围从15分钟到12小时。 (2)最少的先验目标信息。可能没有目标的图像数据库,并且可能要求系统以与开销照片一样少的信息进行操作。 (3)目标的实时识别。武器发射系统对特定破坏目标的最终指导将受到识别系统的影响。 (4)灵活地攻击各种目标。可以存储已知的高价值固定目标(HVFT)的数据库,但是必须容纳突然包含的新目标。本文将讨论基于模型的方法的实时实现,该方法可自动识别前视红外(FLIR)图像中的高价值固定目标。此方法生成在图像中找到的预期目标特征的预测模型,从图像中提取那些特征类型,然后将预测模型与图像特征进行匹配。已经采用了一种对目标特征进行描述的通用方法,以允许从最少的先验目标信息中快速准备模型。通过在大规模并行单指令多数据架构上实现系统,可以实现实时性。将讨论攻击高价值固定目标的整个系统方法的概述。将详细讨论作为系统一部分的自动目标识别器(ATR),并显示FLR图像中针对HVFT的ATR操作结果。!4

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