Evaluation of some features for extended target extraction in polarimetric radar

P. van Genderen, V. Kovalenko
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引用次数: 1

Abstract

Detection in most surveillance radars is based on the condition of point targets against a more or less homogeneous background. Currently, the resolution of many new types of radar is increasing, at least in the range dimension. Therefore many objects no longer can be considered as points. Also as a consequence, the background is getting more diverse, in statistical terms. The scene addressed in this paper concerns a ground clutter environment, and extended objects observed with a polarimetric radar with modestly high resolution (i.e. 6m resolving power in range). A staged approach is proposed to detection and parameter assessment of extended objects and adding classification based on polarimetric features. The evaluation of this approach is based on recordings of real natural scenes and artificially inserted extended objects. It has been observed that in the multi-stage detection the object classification benefits from several features, amongst which polarimetric ones. It is proposed that the quality of the contour circumscribing the object is the prime factor for quality of the features next to the polarimetric features. Clutter is affecting the edges of the contours, and therefore may have a major impact on features that are dependent on these contours.
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极化雷达扩展目标提取的若干特征评价
大多数监视雷达的检测都是基于点目标在或多或少均匀背景下的情况。目前,许多新型雷达的分辨率都在不断提高,至少在距离维度上是如此。因此,许多对象不再可以被视为点。同样,从统计角度来看,背景也变得越来越多样化。本文讨论的场景是一个地杂波环境,用中等高分辨率(即距离分辨率为6m)的极化雷达观测到的扩展目标。提出了一种基于偏振特征的扩展目标检测、参数评估和添加分类的分级方法。该方法的评估是基于真实自然场景的记录和人工插入的扩展对象。在多阶段检测中,目标分类得益于若干特征,其中偏振特征是最重要的。提出了物体外围轮廓质量是影响偏振特征旁边特征质量的主要因素。杂波正在影响轮廓的边缘,因此可能对依赖于这些轮廓的特征产生重大影响。
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