The Ground Process Segment of SAR Altimeter

The key innovation technology of SAR Altimeter (Synthetic Aperture Radar Altimeter)are Doppler\|beam sharpen and delay/Doppler range compensation.The cooperation of these two technologies makes it has high along track resolution and high precision in height measurement.The ground processor is the key hinge to make sure that SAR altimeter could obtain these superiorities.Many key technologies for SAR altimeter processor,such as Doppler beam\|sharpen,delay/Doppler compensation and the second range correction,multilook,echo model and gradient function for retracker,are introduced in the paper.Based on the processor and related work,some simulation work and airborne experiment were tested by the processor,and both of the quantity results show that the SAR altimeter has more potential superiorities.     

SAR影像海洋表面溢油检测方法与实现

海洋是地球的重要组成部分,它为人类提供了丰富的物质和宝贵的资源,每年海洋都承受着不同程度的侵害,其中油类污染是给海洋造成巨大危害的污染之一。而油类污染又主要来源于轮船破裂漏油以及油井平台或海底输油管道爆炸等。每次事故造成的直接经济损失达几百万至上千万不等,所以对海上溢油进行监测具有重要的意义。选用Envisat的ASAR数据进行海上溢油检测,介绍并分析了SAR图像溢油检测的一般步骤及其实现方法,通过采用单一阈值分割法、最大熵分割法和非监督分类法对影像进行目标检测,从而粗略地将影像区分为前景区域与背景区域,并结合影像的纹理特征进行分类。在纹理特征选取过程中,通过人工选取部分溢油区与非溢油区作为感兴趣区,在感兴趣区上分别统计SAR影像常用的纹理特征,并结合不同目标检测的结果以及原始影像进行基于BP神经网络的分类,得到了良好的效果。最后展望了SAR图像海洋溢油检测的发展方向。     

基于交叉极化比的SAR图像矿物油膜与生物油膜的区分方法

海洋表面矿物油膜、生物油膜等在SAR图像上都呈现为暗色特征,使得单极化SAR图像对矿物油膜和生物油膜的区分存在困难。分析了矿物油膜和生物油膜后向散射系数的极化比,提出一种基于交叉极化比的多极化SAR图像矿物油膜和生物油膜的区分方法,并用SIR\|C多极化数据验证了该方法的有效性。     

建筑物目标高分辨率SAR图像模拟方法

随着TerraSAR-X,Cosmo-SkyMed和Radarsat-2等高分辨率合成孔径雷达(SAR)卫星系统的升空,星载SAR图像空间分辨率达到了米级。在这些高空间分辨率SAR图像中,单个建筑物结构的散射特征能够得到明显的展现,推动了SAR在城市监测中的应用。而城市环境的复杂性给SAR图像的解译和应用带来了巨大的挑战,由于SAR图像模拟有助于图像的解译和应用,因此城市目标高分辨率SAR图像模拟成为一个研究热点。提出了一种基于射线追踪法的图像模拟方法,它能够模拟城市目标SAR图像上叠掩、阴影和多次散射等主要特征,非常有利于SAR图像的解译。该模拟方法首先构建虚拟SAR传感器,发射电磁波射线与场景中三维模型相互作用,并接收回波信号成像,电磁波的传播以及与场景的多次散射在整个过程中都能够被追踪。为了评价该模拟方法的有效性,首先通过模拟平顶屋、尖顶屋模型的SAR图像,然后选择国家体育馆和大场景小区三维模型作为输入,将生成的模拟图像与真实TerraSAR-X聚束模式图像进行比较。结果表明:该模拟器能够模拟城市目标的散射特征并应用于图像的理解和变化检测。     

基于SAR数据的干旱区冲积扇地表粗糙度反演

干旱区冲积扇的表面特征是研究古气候、古环境变化的重要途径,冲积扇扇面粗糙度是反映冲积扇演化的重要指示。合成孔径雷达(SAR)已成为冲积扇扇面特征参数提取的有力工具。然而,现有的地表粗糙度反演模型在干旱区难以得到较好的反演结果。利用Radarsat-2极化数据,开展了疏勒河冲积扇地表粗糙度反演研究,在OH模型的基础上,提出了更加适合干旱区地表粗糙度反演的新方法。经过实测数据的验证,新方法能够解决原有模型在干旱区粗糙度反演结果偏大的问题,并取得了较好的反演结果。该模型的提出为干旱区冲积扇表面参数提取提供了可靠的工具。     

Sensitivity of SAR data to post-fire forest regrowth in Mediterranean and boreal forests

Disturbed forests may need decades to reach a mature stage and optically-based vegetation indices are usually poorly suited for monitoring purposes due to the rapid saturation of the signal with increasing canopy cover. Spaceborne synthetic aperture radar (SAR) data provide an alternate monitoring approach since the backscattered microwave energy is sensitive to the vegetation structure. Images from two regions in Spain and Alaska were used to analyze SAR metrics (cross-polarized backscatter and co-polarized interferometric coherence) from regrowing forests previously affected by fire. TerraSAR-X X-band backscatter showed the lowest sensitivity to forest regrowth, with the average backscatter increasing by 1-2 dB between the most recent fire scar and the unburned forest. Increased sensitivity (around 3-4 dB) was observed for C-band Envisat Advanced Synthetic Aperture (ASAR) backscatter. The Advanced Land Observing Satellite (ALOS) Phased Array-type L-band Synthetic Aperture Radar (PALSAR) L-band backscatter presented the highest dynamic range from unburned to recently burned forests (approximately 8 dB). The interferometric coherence showed low sensitivity to forest regrowth at all SAR frequencies. For Mediterranean forests, five phases of forest regrowth were discerned whereas for boreal forest, up to four different regrowth phases could be discerned with L-band SAR data. In comparison, the Normalized Difference Vegetation Index (NDVI) provided reliable differentiation only for the most recent development stages. The results obtained were consistent in both environments.     

Mapping arctic landfast ice extent using L-band synthetic aperture radar interferometry

In recent years methods have been developed to extract the seaward landfast ice edge from series of remote sensing images, with most of them relying on incoherent change detection in optical, infrared, or radar amplitude imagery. While such approaches provide valuable results, some still lack the required level of robustness and all lack the ability to fully automate the detection and mapping of landfast ice over large areas and long time spans. This paper introduces an alternative approach to mapping landfast ice extent that is based on coherent processing of interferometric L-band Synthetic Aperture Radar (SAR) data. The approach is based on a combined interpretation of interferometric phase pattern and interferometric coherence images to extract the extent and stability of landfast ice. Due to the low complexity of the base imagery used for landfast ice extraction, significant improvements in automation and reduction of required manual interactions by operators can be achieved. A performance analysis shows that L-band interferometric SAR (InSAR) data enable the mapping of landfast ice with high robustness and accuracy for a wide range of environmental conditions.     

高性能SAR成像程序的并行粒度选择技术

高性能并行仿真程序必须采用针对性的并行优化技术以获得高效的性能加速。而根据程序特性,确定适合的并行粒度是设计并行优化技术的基础。因此,以典型合成孔径雷达(SAR)成像程序--距离-多普勒(RD)程序为代表,研究了高性能SAR成像程序的并行粒度选择技术,重点针对并行粒度的基本准则和RD算法的并行粒度选择方法进行了研究。实验结果证明,经过并行粒度优化选择的SAR成像程序能够获得显著的性能提升,并且具有良好的可扩展性。     

SAR图像数据稀疏性分析及在特征增强中的应用

利用合成孔径雷达(SAR)图像中目标的后向散射特性和目标散射中心的理论,分析了SAR图像数据稀疏性的成因。指出SAR图像的稀疏性与典型散射体的后向散射特性、成像区域目标强散射中心的稀疏性和成像区域的粗糙度等因素有关。根据视觉稀疏表示机制,比较了SAR图像与光学图像稀疏特征在视觉上的差异。然后,分析了稀疏约束在SAR图像分辨率增强中的应用方法。最后,用仿真和实测SAR图像数据验证了稀疏性在特征增强中的作用。     

空载SAR发展状况

空载SAR具有提供高分辨率成像的能力,这种能力不受气象条件和太阳照射的限制,其成像范围不受国界、地域和地理自然条件的限制,受到广泛重视,空载SAR经过20多年的发展,尽管数量有限,所提供的信息量却是巨大的,并被广泛应用,为人类提供了大量鲜为人知的信息,概述了空载SAR的用途及发展过程,说明空载SAR的现状和其主要性能,介绍正在发展中的空载SAR项目,分析空载SAR的发展趋势。