Research on an unmanned underwater vehicle autonomous active target detection method

被引：0
|
作者：
Ren Y.-F. [1 ,2 ]
Wu Y.-Q. [1 ]
Li Y. [1 ]
Huang H.-N. [1 ]
机构：
[1] Institute of Acoustics, Chinese Academy of Sciences, Beijing
[2] University of Chinese Academy of Sciences, Beijing
来源：
Chuan Bo Li Xue/Journal of Ship Mechanics | 2019年 / 23卷 / 02期
关键词：
Autonomous active target detection; Image segmentation; Unmanned underwater vehicle; Watershed algorithm;
D O I：
10.3969/j.issn.1007-7294.2019.02.012
中图分类号：
学科分类号：
摘要：
The ability of autonomously detecting active target is one of the key capabilities of unmanned underwater vehicle. One of their difficulties is active target detection in reverberation background. In this paper, active target detection is converted into an image segmentation problem. Firstly, morphological reconstruction or low-pass filter is applied in acoustic image preprocessing. Secondly, watershed algorithm is applied to divide targets from a gradient map. An adaptive threshold selection technique is provided based on this target detection method. Tests with sea trial data show that this method is more stable and has lower false alarm rate than CFAR (constant false alarm rate) algorithm. © 2019, Editorial Board of Journal of Ship Mechanics. All right reserved.
引用
收藏
页码：227 / 233
页数：6
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