使用PMMW和LADAR图像的自动目标检测

M. R. Stevens, M. Snorrason, Sengvieng Amphay
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引用次数: 2

摘要

对带有自动目标捕获(ATA)导引头的空对地导弹的需求在很大程度上是由飞行员制导炸弹在多云条件下(如在科索沃的情况)的失败所驱动的。无源毫米波(PMMW)传感器具有穿透云层的能力;事实上,无论天气状况如何,它们都倾向于以高对比度显示金属物体(如移动地面目标)。然而,与激光雷达(LADAR)等其他流行的ATA传感器相比,它们的分辨率非常低。我们提出了一种结合PMMW优越的目标检测潜力和LADAR高质量分割和识别能力的A - TA算法套件。采用89GHz 18”孔径PMMW传感器和1.06 /spl μ /超高分辨率雷达,对本项目采集的一组军用车辆图像对进行了初步检测和分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic target detection using PMMW and LADAR imagery
The need for air-to-ground missiles with autonomous target acquisition (ATA) seekers is in large part driven by the failure of pilot-guided bombs in cloudy conditions (such as demonstrated in Kosovo). Passive-millimeter wave (PMMW) sensors have the ability to see through clouds; in fact, they tend to show metallic objects (such as mobile ground targets) in high contrast regardless of weather conditions. However, their resolution is very low when compared with other popular ATA sensors such as laser-radar (LADAR). We present an A TA algorithm suite that combines the superior target detection potential of PMMW with the high-quality segmentation and recognition abilities of LADAR. Preliminary detection and segmentation results are presented for a set of image-pairs of military vehicles that were collected for this project using an 89GHz, 18" aperture PMMW sensor and a 1.06 /spl mu/ very-high-resolution LADAR.
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