Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta

Because of the importance of rice for the global food security and because of the role of inundated paddy fields in greenhouse gases emissions, monitoring the rice production world-wide has become a challenging issue for the coming years. Local rice mapping methods have been developed previously in many studies by using the temporal change of the backscatter from C-band synthetic aperture radar (SAR) co-polarized data. The studies indicated in particular the need of a high observation frequency. In the past, the operational use of these methods has been limited by the small coverage and the poor acquisition frequency of the available data (ERS-1/2, Radarsat-1). In this paper, the method is adapted for the first time to map rice at large scale, by using wide-swath images of the Advanced SAR (ASAR) instrument onboard ENVISAT. To increase the observation frequency, data from different satellite tracks are combined. The detection of rice fields is achieved by exploiting the high backscatter increase at the beginning of the growing cycle, which allows the production of rice maps early in the season (in the first 50 days). The method is tested in the Mekong delta in Vietnam. The mapping results are compared to existing rice maps in the An Giang province, with a good agreement (higher than 81%). The rice planted areas are retrieved from the maps and successfully validated with the official statistics available at each province (R² = 0.92). These results show that the method is useful for large scale early mapping of rice areas, using current and future C band wide-swath SAR data.     

宽幅SAR海上大型运动舰船目标数据集构建及识别性能分析

以TopSAR和ScanSAR成像模式为代表的宽幅合成孔径雷达(SAR)可以实现更大范围的海洋场景观测。但实现宽测绘带的同时降低了成像分辨率,因此宽幅SAR图像中的舰船目标缺乏清晰的结构特征,给大范围海上舰船目标识别带来了极大的挑战。同时,由于缺乏海上运动航母、两栖舰等大型关键目标的宽幅SAR样本数据,使得海上运动大型关键舰船目标识别更加困难。针对该问题,该文构建了宽幅SAR海上大型运动舰船目标数据集,共包含2291个大型舰船目标样本,类别划分为大型军事舰船,长度为≥250 m的大型民用舰船和长度为150～250 m的大型民用舰船。其构建过程为:首先,通过先验知识辅助获取港口区域大型军事舰船目标样本;其次,利用属性信息对OpenSARShip数据集进行长度筛选获取大型民用舰船目标样本;最后,在样本的距离-多普勒域添加二次相位误差进行运动仿真来模拟海上运动舰船目标的成像结果。此外,该文使用经典识别算法和深度学习方法对构建的数据集与运动仿真处理后的数据进行了识别性能分析,结果表明在低分辨率情况下采用SAR图像复数信息可以在一定程度上提高算法的识别率;并且运动舰船目标的散焦问题对识别准确率具有较大影响。      

利用相位中心偏移方位多波束来实现宽测绘带SAR成像

该文提出了一种基于相位中心偏移方位多波束的宽测绘带星载SAR实现方案。通过在方位向上配置相位中心偏移的多个波束使雷达在一个脉冲周期内完成多个多普勒历程的信号采样,显著降低系统对脉冲重复频率的要求,实现宽测带SAR成像。针对卫星速度的非恒定性和不同波位所需PRF的多样性造成的方位信号非均匀采样,该方案采用了多通道信号重建技术来恢复均匀采样信号的算法。与采用高轨技术和分布式技术的宽测绘带SAR方案相比,这种方案的技术难度较小、易于实现。     

非正交发射的宽域高分辨MIMO InSAR成像模式研究

MIMO InSAR具有比多基线InSAR更稳健和精确的地形高程重建能力,但其关键技术之一是在各阵元接收端分离出源自不同阵元发射信号的回波。现有正交信号正交性不足,依赖它们实现回波分离会产生严重回波间相互干扰。为此,该文提出了一种非正交发射的MIMO InSAR成像模式,该模式首先通过控制各阵元交替发射信号,使其主瓣回波交替出现在各脉冲重复周期,此时只需压低各阵元天线俯仰维旁瓣即可大幅降低回波间的相互干扰,从而避免回波分离对发射信号正交性的依赖。在此模式基础上,该文又引入基于方位向多通道处理的波束扫描技术以缓解交替发射时方位不模糊与距离不模糊之间矛盾,从而实现宽域、高分辨观测。仿真结果证明了该文MIMO InSAR成像模式的有效性。     

距离向多孔径超宽测绘带成像体制中各项误差分析

理论上已经证实可实现超宽测绘带的距离向多孔径成像方法在增加测绘带宽的同时又可获得较高的分辨率。为了正确地评定距离向多孔径成像方法的实用性,该文给出了体制中各项误差的定量分析,并对一些误差给出了相应的算法上的修正。