海洋动力过程光学遥感探测示例--水面舰船航速探测

初步探讨了光学遥感应用于海洋动力过程探测的可能性以及水动力学调制对海洋动力过程光学遥感成像的影响.阐明了Kelvin尾迹的横波在光学遥感影像中成像的原理,并利用深水环境下波速与波长的关系探测了IKONOS影像和航天飞机照片中船只的航速.     

小入射角下海浪后向散射系数不对称性和各向异性分析验证

基于北京遥测技术研究所机载波谱仪实测数据以及ECMWF提供的风场数据,分析了不同风速条件下小入射角海浪平均后向散射系数不对称性与各向异性随入射角的变化特性,并对导致这一现象的原因进行了初步分析。结果表明:小入射角下,海浪平均后向散射系数随入射角增大呈现递减趋势并在18°时达到某一稳定值,之后基本维持不变;海浪后向散射系数不对称性与各向异性均随入射角增大呈现递增趋势,同样在18°增大至某一稳定值,之后基本维持不变;低风速条件下,海浪不对称性和各向异性与风速有关,且风速越大不对称性与各向异性越明显。     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.     

神舟四号高度计波形数据预处理和信息提取

神舟四号(SZ-4)高度计在国内首次提供了星载雷达高度计回波波形数据.本文中作者分析了SZ-4高度计回波波形的特点,完成波形数据的预处理,并在此基础上完成初步的信息提取.在数据预处理方面,通过SZ-4高度计水陆边界处波形的特点,提出了波形最大幅度控制的方法,筛选回波波形.在波形归一化处理过程中,发现SZ-4高度计波形中存在双峰现象,并指出第二个峰为异常波形区.在波形信息提取方面,利用波形重新跟踪得到的半功率点计算出SZ-4高度计高度跟踪补偿误差,并根据高度计天线指向角和回波波形下降沿斜率之间的关系,从波形后沿提取天线指向角信息.分析结果表明,SZ-4高度计天线指向比较平稳,而跟踪补偿由于变化较大,在计算海面高度时,应作为一项误差源被考虑到.     

全极化SAR图像中溢油极化特征研究

相比于单极化SAR图像,全极化SAR图像不仅能体现海面目标的几何特征、后向散射特征,还能体现目标的极化特征。因此,在溢油检测方面,极化SAR更具优势。特征提取作为溢油检测的关键步骤,直接影响到溢油检测的精度。在本文中,我们分析了全极化SAR图像中海面溢油的极化特征,如极化散射熵、平均散射角等。并提出了新的极化特征P,该特征参数能够反映海面目标电磁散射过程中布拉格散射机制和镜面散射机制的比例。为了研究极化特征溢油检测的能力,本文基于SIR-C/X-SAR和Radarsat-2全极化SAR图像开展了相关实验,并对比分析了溢油的多种极化特征。实验结果显示,在中低风速情况下,C波段溢油探测效果优于L波段;本文提出的极化特征P对海面散射机制敏感;基准高度和特征参数P在C波段比其他极化特征更适于溢油检测。     

溢油乳化过程C波段微波散射特性实验研究

本文基于水槽溢油观测实验,研究溢油乳化过程中表面散射特性的变化。利用全极化C波段微波散射计和矢量网络分析仪等测量设备对易发生乳化反应沥青含量小于3%的原油（A型油）、油田中开采出的新鲜原油（B型油）和经过脱水去杂质处理的工业原油（C型油）进行观测。文中详细分析了在C波段微波下乳化油膜与平静水面的后向散射差异,以及油膜乳化过程对后向散射的影响,结果显示在低风速、无浪的条件下（最大波高低于3mm）,原油的乳化反应可通过表面粗糙度和自身介电常数的变化来调制雷达后向散射,并且这两种方式中表面粗糙度的影响占主导地位。对比B型和C型原油在乳化状态和未乳化状态下的表面后向散射,结果显示在各状态下B型油膜表面后向散射均大于C型油,且在VV、HH、HV/VH极化方式下两者后向散射平均差异分别为2.19 dB、2.63 dB、2.21 dB,在20%油膜含水率的乳化状态下差异较未乳化状态时小,平均差异分别为0.98 dB、1.49 dB、1.5 dB,结果表明不同类型油种间由于成分和油膜属性的不同会在一定程度上导致油膜表面粗糙度存在差异,影响油膜表面后向散射。     

基于多源遥感数据的日本海内波特征研究

日本海特殊的地理位置和复杂的地形使得该海域内波表征极为复杂,遥感是大范围观测内波的有效手段,已被广泛应用于内波的探测研究。本文利用MODIS、GF-1和ENVISAT ASAR遥感影像,开展了日本海内波特征研究。通过提取内波波峰线,生成了日本海内波空间分布图;获取了内波的波峰线长度和传播速度,并基于非线性薛定谔方程反演了内波振幅。研究结果表明,日本海内波分布范围宽广,不仅大陆架沿海区内波分布密集,深海盆地也探测到了大量内波;日本海北部45°N附近海域有少量内波出现,利用高分影像探测到朝鲜陆架浅海区有大量小尺度内波,大和海盆、大和隆起的西南部海域没有发现内波。日本海内波波峰线长达100多千米,深海区的传播速度大于1 m/s;浅海区内波振幅约10 m左右,深海区可达60 m以上。     

基于星载红外辐射计的北极海表温度数据对比分析

本文基于2016年MODIS(ModerateResolutionImagingSpectroradiometer)-Aqua、MODIS-Terra和VIIRS(Visible Infrared Imager Radiometer Suite)三种红外辐射计的海表面温度(Sea Surface Temperature,SST)数据,统计了北极地区红外SST1月和7月的覆盖率及有效覆盖天数,并与Argo(Arrayfor Real-timeGeostrophicOceanography)浮标数据进行了匹配验证,直观获取北极SST误差分布情况并研究SST遥感观测能力,为更好地了解北极地区从而应对气候变化提供一定的资料基础。结果表明,北极地区红外辐射计SST数据7月的覆盖率和有效观测天数均高于1月,1月三种数据相差不大,7月VIIRS的覆盖率和有效观测天数均优于MODIS-Aqua和MODIS-Terra,联合三种红外辐射计的覆盖率和有效观测天数相较于单星有所增加, 1月覆盖率最高为8%, 7月最高接近70%,表明多星联合探测是提高北极地区SST数据覆盖率和观测天数的有效方法;北极地区SST数据的误差普遍高于全球总体水平, VIIRS白天、夜间的均方根误差(E_(rms))均低于MODIS-Aqua和MODIS-Terra, MODIS-Aqua白天SST的E_(rms)高于MODIS-Terra,夜间则低于MODIS-Terra。综合来看, VIIRS在北极的覆盖率、有效观测天数及与浮标的匹配结果在三种红外辐射计中为最优。     

基于结构特征的SAR船只类型识别能力分析

1 引言 SAR是船只探测的有效手段,利用SAR影像不仅可以检测船只目标,而且还可以提取船只的长度、宽度以及航速、航向等信息.随着星载SAR空间分辨率的提高,使基于星载SAR影像的船只类型识别成为可能.利用星载SAR可以检测出大面积范围内的船只和初步识别其类型.     

基于小波变换和HIS变换的海冰SAR与光学遥感影像融合方法研究

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral information, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be improved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transformation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar(ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensity-saturation(HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue(RGB) space, and the optical image from the China-Brazil Earth Resources Satellite(CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis(PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification.