A spectral approach to image-enhanced moving target radar detection

R. Bonneau
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引用次数: 3

Abstract

A difficult problem with ground moving target radar (GMTI) detection is how to consistently track targets moving through non-homogeneous regions of clutter such as forest and urban boundaries. Although attempts have been made to mitigate this detection problem using terrain mapping data, such data does not give current clutter information due to change in vegetation, roads, buildings, and seasonal variation. We propose to use synthetic aperture radar (SAR) imagery to enhance the detection performance of GMTI radar. We use a multiresolution Markov model to represent both target and background clutter. This multiresolution structure allows us to accurately match GMTI clutter with the geographically registered SAR imagery for consistent moving target detection through clutter boundary areas.
图像增强运动目标雷达探测的光谱方法
地面运动目标雷达(GMTI)检测的一个难题是如何在非均匀杂波区域(如森林和城市边界)中持续跟踪运动目标。尽管已经尝试使用地形测绘数据来缓解这种检测问题,但由于植被、道路、建筑物和季节变化的变化,这些数据不能提供当前的杂波信息。我们提出利用合成孔径雷达(SAR)图像来提高GMTI雷达的探测性能。我们使用多分辨率马尔可夫模型来表示目标和背景杂波。这种多分辨率结构使我们能够准确地将GMTI杂波与地理注册的SAR图像进行匹配,从而通过杂波边界区域进行一致的运动目标检测。
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