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Ship target recognition with the Mellin transform aided by neural networks

机译:利用神经网络的Mellin变换进行舰船目标识别

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This paper summarises further research into the application of the Mellin transform for radar ship target recognition. As reported in previous papers, preprocessing is via the Mellin transform, with recognition utilising neural networks. However, in this paper, substantial emphasis is placed on discussing the pre-processing techniques applied in the implementation of the Fourier modified direct Mellin transform (FMDMT). The FDMDMT extracts features from the range profiles of targets, regardless of aspect angle. In particular, the robustness of the technique in the presence of noise and amplitude scintillation is investigated, together with the range of angles over which the FMDMT is successful. Real and simulated data is utilised.
机译:本文总结了Mellin变换在雷达舰船目标识别中的应用的进一步研究。如前几篇论文所述,预处理是通过Mellin变换进行的,并利用神经网络进行识别。但是,在本文中,重点放在讨论在傅立叶改进的直接梅林变换(FMDMT)的实现中应用的预处理技术。 FDMDMT会从目标的范围配置文件中提取特征,而与宽高比无关。特别是,研究了该技术在存在噪声和幅度闪烁的情况下的鲁棒性,以及成功实现FMDMT的角度范围。利用真实和模拟的数据。

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