条带图模式相干声呐的建模与增强

R. Sathishkumar, P. J. A. Vignesh, H. R. Babu
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引用次数: 0

摘要

传统声纳提供目标区域的低分辨率成像。合成孔径声呐(SAS)建模比传统系统具有挑战性,因为拖鱼路径几何形状更复杂,数据通常是非平稳的。研究了合成孔径技术在声纳图像中的应用,提出了一种新的二维SAS目标特征提取模型。该技术被证明在分辨方面是准确的。时域算法可以处理一般的声纳情况,但效率很低;因此,频域方法是首选的。在本文中,我们讨论了啁啾缩放算法(CSA)来处理SAS数据。然后尝试克服当前二维SAS中固有的一些运动误差。进行了仿真,并对该技术的精度进行了评估。
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Modelling and Enhancement of Stripmap Mode Coherent Sonar
Conventional sonar offers low-resolution imaging of a target region. Synthetic aperture sonar (SAS) modeling ischallenging than the conventional systems because the towfish path geometry is more complicated and the data are usually non stationary. This paper investigates the application of synthetic aperture technique to sonar image and develops a new model for two-dimensional (2-D) SAS target feature extraction. The technique is shown to be accurate at resolving. Time-domain algorithms can handle general sonar cases, but they are very inefficient; therefore, frequency-domain methods are preferred. In this paper, we discuss the chirp scaling algorithm (CSA) to handle SAS data. An attempt is then made to overcome some of the motion errors inherent in the current 2-D SAS. Simulations are implemented and the accuracy of the technique is assessed.
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