首页> 外文会议>Oceans Conference >Advances in Group Filter Applications to Sea Mine Detection
【24h】

Advances in Group Filter Applications to Sea Mine Detection

机译:将筛选应用程序的进步进入海矿检测

获取原文

摘要

Automatic detection of sea mines in coastal regions is a difficult task due to the highly variable sea bottom conditions present in the underwater environment. Detection systems must be able to discriminate objects which vary in size, shape, and orientation from naturally occurring and man-made clutter. Additionally, these automated systems must be computationally efficient to be incorporated into unmanned underwater vehicle (UUV) sensor systems characterized by high sensor data rates and limited processing abilities. Using noncommutative group harmonic analysis, a fast, robust sea mine detection system is created. A family of unitary image transforms associated to noncommutative groups is generated and applied to side scan sonar image files supplied by Naval Surface Warfare Center Panama City (NSWC PC). These transforms project key image features, geometrically defined structures with orientations, and localized spectral information into distinct orthogonal components or feature subspaces of the image. The performance of the detection system is compared against the performance of an independent detection system in terms of probability of detection (P{sub}d) and probability of false alarm (P{sub}(fa)).
机译:由于水下环境中存在的高度可变的海底条件,自动检测沿海地区的海洋矿区是一项艰巨的任务。检测系统必须能够区分尺寸,形状和方向不同的物体与自然发生的和人造杂波的尺寸。另外,这些自动化系统必须被计算为结合到具有高传感器数据速率和有限的处理能力的无人驾驶车辆(UUV)传感器系统中。使用非容态组谐波分析,创建了一个快速的强大的海洋矿床检测系统。生成与非容态组相关联的单一图像转换系列,并应用于海军表面战中心巴拿马城(NSWC PC)提供的侧扫描声纳图像文件。这些将项目关键图像特征(几何定义结构与方向转换为所述不同的正交组件或图像的特征子空间。将检测系统的性能与独立检测系统的性能进行比较,而是在检测概率(P {SUB} D)和误报概率(P {SUB}(FA))方面的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号