1. 中国人民解放军92213部队
2. 哈尔滨工程大学智能科学与工程学院
纸质出版:2024
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唐会林, 宋甘琳, 周佳加, 等. 基于GAN-SVC的水下障碍物轮廓构建研究[J]. 传感器与微系统, 2024,(12):12-15. DOI: 10.13873/J.1000-9787(2024)12-0012-04.
针对由于复杂噪声使得水下无人航行器(UUV)声呐探测数据可靠性下降进而导致障碍物轮廓构建失准的问题,本文提出了一种基于生成对抗网络(GAN)和支持向量聚类(SVC)的水下障碍物轮廓构建算法。为区分复杂噪声点与障碍物点,该算法基于SVC对声呐数据异常点进行初步筛选。针对SVC受参数影响可能导致较小簇误判的问题,利用GAN精确筛选异常点;并对精确的障碍物点进行聚类得到各个障碍物的最优轮廓。通过对湖中障碍物探测数据的轮廓构建仿真验证试验,相比SVC算法,使用本文所提GAN-SVC算法在对2个障碍物进行轮廓构建时,准确度分别提高了79.80%和48.13%。
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