凹障碍超宽带SAR图像特征分析
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然科学基金资助项目(61372163)


Study on ultra-wideband SAR image feature of negative obstacle
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    野外环境下的凹障碍感知一直是地面无人作战平台环境感知面临的难题,长期以来常规传感器,例如立体视觉、红外相机和激光雷达,都没有取得好的效果。超宽带合成孔径雷达作为一种全天时、全天候的高分辨率雷达,在目标感知方面得到了广泛的运用。基于超宽带合成孔径雷达感知凹障碍是一种有效的感知手段,阐述了凹障碍的雷达成像几何,利用MATLAB模拟仿真合成孔径雷达数据获得了凹障碍图像,分析得出了凹障碍在雷达图像表现出由阴影区和光亮区紧密相连的特征,并通过实测数据成像获得的凹障碍图像结果,对凹障碍雷达图像特征进行了进一步的验证。

    Abstract:

    Negative obstacle sensing is one of the most difficult problems for unmanned ground vehicle in unstructured environments. The regular obstacle sensors, such as stereo vision, infrared detector and ladar, have their limited performances in unconstructed environments. Ultrawideband SAR (synthetic aperture radar) sensors have the ability to operate in all weather, all lighting and foliage covered conditions, which have been received widely. Sensing negative obstacle by ultrawideband SAR for unmanned ground vehicle was an effective way. Image geometry of negative obstacle was expounded. The simulation image of negative obstacle was obtained by simulation based on MATLAB, and the conclusion that the image feature of negative obstacle is the shadow area next to shine area is obtained. Moreover, a real data experiment is presented and the experimental result proves the same conclusion again.

    参考文献
    相似文献
    引证文献
引用本文

蒋志彪,王建,宋千,等.凹障碍超宽带SAR图像特征分析[J].国防科技大学学报,2017,39(6):160-164.
JIANG Zhibiao, WANG Jian, SONG Qian, et al. Study on ultra-wideband SAR image feature of negative obstacle[J]. Journal of National University of Defense Technology,2017,39(6):160-164.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2016-07-08
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2018-01-16
  • 出版日期:
文章二维码