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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Automatic Detection of Ship Targets Based on Wavelet Transform for HF Surface Wavelet Radar
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Automatic Detection of Ship Targets Based on Wavelet Transform for HF Surface Wavelet Radar

机译：基于小波变换的高频水面小波雷达舰船目标自动检测

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摘要

High-frequency surface wave radar (HFSWR) has a vital civilian and military significance for continuous maritime surveillance of activities within exclusive economic zone. However, HFSWR has lower spatial and temporal resolutions and the received signals are strongly polluted by different clutter and background noise. Therefore, ship target detection by HFSWR has become a challenging task. This letter presents an automatic ship target detection algorithm based on discrete wavelet transform (DWT). First, a peak signal-to-noise ratio-based algorithm is proposed to automatically determine the optimal scale of DWT for extraction of ship targets. Second, the high-frequency coefficients of DWT at the optimal scale are processed by a fuzzy set-based method to enhance the useful target information and depress the unwanted background noises. Third, a target-highlighted image is reconstructed by ignoring all the low-frequency coefficients and performing inverse DWT only to the enhanced high-frequency coefficients. Finally, the targets are extracted by adaptive threshold segmentation of the final target-highlighted image. Experimental results show that the proposed approach can automatically extract ship targets effectively for range Doppler images with complex background, and has a better target detection performance than the previous wavelet-based algorithm, thereby providing a new reliable image processing-based method of ship target detection for HFSWR.
机译：高频表面波雷达（HFSWR）对于持续海上监视专属经济区内的活动具有至关重要的民用和军事意义。但是，HFSWR具有较低的空间和时间分辨率，并且接收到的信号会被不同的杂波和背景噪声严重污染。因此，通过HFSWR检测船舶目标已成为一项具有挑战性的任务。这封信提出了一种基于离散小波变换（DWT）的自动舰船目标检测算法。首先，提出了一种基于峰值信噪比的算法来自动确定DWT的最优尺度，以提取舰船目标。其次，通过基于模糊集的方法处理DWT的最佳比例的高频系数，以增强有用的目标信息并抑制不需要的背景噪声。第三，通过忽略所有低频系数并且仅对增强的高频系数执行逆DWT来重建目标突出图像。最后，通过对最终目标高亮图像进行自适应阈值分割来提取目标。实验结果表明，该方法能够有效地自动提取背景复杂的距离多普勒图像的舰船目标，并且比以前基于小波的算法具有更好的目标检测性能，从而提供了一种基于图像处理的可靠的舰船目标检测新方法用于HFSWR。

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  • 来源
    《Geoscience and Remote Sensing Letters, IEEE》 |2017年第5期|714-718|共5页
  • 作者

    Qingzhong Li; Wandong Zhang; Ming Li; Jiong Niu; Q. M. Jonathan Wu;

  • 作者单位

    College of Engineering, Shandong Provincial Key Laboratory of Ocean Engineering, Ocean University of China, Qingdao, Shandong, China;

    College of Engineering, Shandong Provincial Key Laboratory of Ocean Engineering, Ocean University of China, Qingdao, Shandong, China;

    College of Engineering, Shandong Provincial Key Laboratory of Ocean Engineering, Ocean University of China, Qingdao, Shandong, China;

    College of Engineering, Shandong Provincial Key Laboratory of Ocean Engineering, Ocean University of China, Qingdao, Shandong, China;

    Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Clutter; Discrete wavelet transforms; Object detection; Marine vehicles; Noise measurement;

    机译：杂波;离散小波变换;目标检测;舰船;噪声测量;

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