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Multi-frame data fusion techniques for ATR of ship targets from multiple ISAR images

机译:来自多个ISAR图像的舰载目标ATR的多帧数据融合技术

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This paper deals with the topic of Automatic Target Recognition (ATR) of Non Cooperative Targets. Specifically the focus is on the ATR of ships from multiple ISAR images. An investigation on different techniques for the fusion of the information provided by multiple image frames is presented. The techniques exploit the principles of multi-feature based ATR and apply them to the case of availability of several images. The recognition process makes use of a wire-frame models library which undergoes a step of candidate models selection before feeding the target model declaration step. Both cases of centralized and decentralized data fusion techniques are considered. The performance of the proposed techniques is investigated in depth by means of simulated data. Moreover the paper provides a comparison of the results of the proposed techniques when applied to live ISAR images of ship targets.
机译:本文涉及非合作目标的自动目标识别(ATR)主题。具体而言,重点是来自多个ISAR图像的船舶的ATR。提出了对用于融合由多个图像帧提供的信息的不同技术的研究。该技术利用了基于多功能的ATR的原理,并将其应用于可获取多个图像的情况。识别过程利用线框模型库,该库在输入目标模型声明步骤之前要经过候选模型选择步骤。考虑了集中式和分散式数据融合技术的两种情况。通过仿真数据深入研究了所提出技术的性能。此外,本文还提供了将这些技术应用于舰船目标的实时ISAR图像的结果的比较。

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