Ship target recognition with the Mellin transform aided by neural networks

H. Serretta, M. Inggs
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引用次数: 7

Abstract

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.
神经网络辅助下的Mellin变换舰船目标识别
本文综述了Mellin变换在雷达舰船目标识别中的应用。正如之前的论文所报道的那样,预处理是通过Mellin变换进行的,识别利用神经网络。然而,在本文中,实质性的重点放在讨论在傅里叶修正直接梅林变换(FMDMT)的实现中应用的预处理技术。FDMDMT从目标的距离轮廓中提取特征,而不考虑向角。特别地,研究了该技术在存在噪声和幅度闪烁时的鲁棒性,以及FMDMT成功的角度范围。使用了真实和模拟数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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