基于无人平台的水下目标自动检测方法
发布时间：2018-08-19 09:26
【摘要】：在水下复杂的声场环境中,对水声目标的自动检测技术是无人平台自主探测的基础,具有重要的研究价值。针对无人平台自噪声在声场中对目标检测的干扰,提出了一种结合峰值信息与梯度信息的目标峰值判决方法;针对由于干扰信号以及信噪比低造成的目标航迹信息缺失现象,设计了一种基于自适应区域生长的航迹修复方法,改善目标航迹的质量;基于检测前跟踪思想,利用霍夫变换获取方位历程图中目标航迹信息的提取与估计。使用上述方法对实验数据进行处理,较为有效地抑制了载体平台自噪声、环境噪声、杂波等的干扰,完成无人干预条件下目标的自动检测,取得了预期的效果。
[Abstract]:In complex underwater acoustic environment, automatic detection of underwater acoustic targets is the basis of autonomous detection of unmanned platforms, and has important research value. A track repair method based on adaptive region growing is designed to improve the quality of the target track. Based on the idea of tracking before detection, the target track information in the azimuth histogram is extracted and estimated by Hough transform. Therefore, the interference of carrier platform self-noise, ambient noise and clutter is effectively suppressed, and the automatic target detection under the condition of no interference is completed, and the expected effect is achieved.
【作者单位】： 中国科学院声学研究所;
【基金】：国家“863”计划项目(Y212051211)
【分类号】：TB56
[Abstract]:In complex underwater acoustic environment, automatic detection of underwater acoustic targets is the basis of autonomous detection of unmanned platforms, and has important research value. A track repair method based on adaptive region growing is designed to improve the quality of the target track. Based on the idea of tracking before detection, the target track information in the azimuth histogram is extracted and estimated by Hough transform. Therefore, the interference of carrier platform self-noise, ambient noise and clutter is effectively suppressed, and the automatic target detection under the condition of no interference is completed, and the expected effect is achieved.
【作者单位】： 中国科学院声学研究所;
【基金】：国家“863”计划项目(Y212051211)
【分类号】：TB56
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