EH-4电磁成像系统在热储构造勘查中的应用研究

地热区的地球物理勘查工作主要是探测地热系统周边的热储构造情况,EH-4电磁成像系统具有不受高阻层屏蔽、轻便、探测深度大等优点。根据地热区热储构造的特点,研究了该套系统在热储构造勘查中的几个关键技术,重点分析了平行试验的重要性、过渡带数据特征及其校正方法。通过在江西某温泉已知热储构造上的实验研究,分析总结了EH-4电磁成像系统在热储构造勘查中应用的可行性及有效性。     

石油勘探电磁层析成像在复杂岩层的应用仿真

对石油岩层进行勘探时,是通过电磁波形成稳定图像,对石油岩层进行勘探.由于石油区域的岩层结构密集和稀松部分分布不均匀,电磁层析成像在分布不均匀的岩石结构中,电磁波回波过程发生不定衰减,导致电磁析图像发生局部变异.传统的石油勘探电磁层析成像技术在图像局部变异下,会严重影响后期的成像效果,成像信息失真明显.提出采用加权小波分析的石油勘探中电磁层析成像复杂结构声波过滤方法.用非线性方程描述所有的石油勘探中电磁层析成像结构声波,选取一组成像信号作为样本数据,计算成像信号的权重,获取所有成像信号在声波过滤过程中的重要程度.针对上述结果进行小波变换处理,完成成像信号的分解,将所有的因子进行重构,实现声波过滤.实验结果表明,利用改进算法进行石油勘探中电磁层析成像复杂结构声波过滤,能够极大的提高过滤准确性,得到清晰的成像信号.     

Jitter Tests and Studies for the Azimuth Axis of the TMT Tertiary Mirror System

太阳辐照度绝对辐射计的灵敏度研究与优化

衣小龙^1,2,方伟¹,骆杨¹,夏志伟¹,王玉鹏¹

（1. 中国科学院 长春光学精密机械与物理研究所,长春 130033;

2. 中国科学院大学,北京100049）

创新点说明：

1）通过理论分析以及实验测量的手段,研究灵敏度非线性误差对太阳辐照度绝对辐射计测量精度的影响;

2）提出了太阳辐照度绝对辐射计的测量新方法,通过实时修正灵敏度补偿了灵敏度的非线性误差,从而提高测量精度。

研究目的：

目前太阳辐照度绝对辐射计的定标精度随光功率的降低而下降,本文主要研究目的是提高太阳辐照度绝对辐射计的测量精度,从而提高定标精度。

研究方法：

通过理论分析以及实验测量的路线研究灵敏度非线性,通过修正灵敏度误差提高太阳辐照度绝对辐射计的测量精度。基于两点插值原理提出优化的测量方法。在各个辐射功率下测量实时修正灵敏度,得到灵敏度非线性的相对系统误差为2.2%,分析灵敏度非线性的影响。同时使用新方法以及传统方法测量辐射功率。

结果：

比对实验结果说明新方法将测量精度提高到0.1%,通过实时修正补偿了灵敏度非线性。

结论：

1）新方法可以显著提高地面比对实验的定标精度;

2）灵敏度非线性研究为优化太阳总辐照度监测仪的在轨定标精度提供了理论和实验依据。

关键词：测量精度;绝对辐射计;辐射定标;太阳辐照度

     

Characterization and optimization of magnetic garnet films for magneto-optical visualization of magnetic field distributions

Rare-earth iron garnet films with in-plane anisotropy grown on (111)-oriented substrates can be used as magneto-optical indicator films for visualization of magnetic leakage fields in nondestructive evaluation. The influence of Faraday rotation, Faraday ellipticity, absorption and film thickness on the performance of a magneto-optical indicator film is investigated. A new optimization method is introduced and compared with the method of contrast optimization. The theory is experimentally verified and an application example is presented.     

FPIR实时快视成像方法

一维全极化综合孔径辐射计(Full Polarization Interferometric Radiometer,FPIR)是一种轻量化的高空间分辨率的综合孔径微波辐射计系统。基于综合孔径辐射计成像原理及X波段FPIR原理样机,提出一种快视成像方法:(1)对原始数据进行抽取和平均,降低实时处理运算量;(2)简化误差处理过程,进而利用傅立叶变换法和G矩阵法反演亮温。通过对FPIR原理样机的地面实验,验证了该实时快视成像方法的有效性。     

乳腺MRI图像肿块分割的分段比较与方法研究

计算机辅助诊断通过对乳腺磁共振成像( MRI)中肿块区域的自动分割和测量为医生提供定量的诊断依据。对分割过程中不同阶段的多种算法进行实验对比,以此探索更具稳定性和准确性的分割方案：空间模糊C均值( sFCM)聚类算法在肿块的初始定位中具有抗噪声能力和稳定性强的优点,而GVF snake模型在精细分割中对局部轮廓具有较好的收敛性;结合两种算法,并运用MRI序列帧间灰度分布相似、肿块位置/形状相近的原理,最终提高整个序列的分割精度与稳定性。     

一种新的LOG算子对SAR图像的边缘检测能力

在对SAR图像的分析和识别中,边缘的检测信息十分重要。针对传统的LOG算子的缺陷,本文提出了一种基于自适应中值滤波的改进LOG算子对SAR图像的边缘检测方法,在平滑图像内部区域的同时保留了更多的细节,提高了LOG算子对SAR图像的弱边缘检测能力,是一种有效的方法。     

基于神经网络控制的星载微波辐射计

本文提出一种采用神经网络控制技术的消除星载全功率微波辐射计系统增益和等效本机噪声波动的方法。此方法通过基于神经网络的控制系统,控制微波辐射计的系统增益与参考电压,使微波辐射计在轨运行期间系统参数保持不变。系统参数通过地面实验获得,因此在轨运行期间不再需要星上两点定标中的低温基准源,减少了低温定标天线等物理设备。     

A new approach for mapping of Biological Soil Crusts in semidesert areas with hyperspectral imagery

Biological Soil Crusts (BSCs), consisting of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, live within or immediately on top of the uppermost millimeters of soil, where they form a more or less firm aggregation of soil particles and organisms. They mainly occur in soils of arid and semi-arid regions, which cover more than 35% of the earth's land surface and are assumed to play a major role as primary producers, C- and N-sinks and soil stabilizers.

In order to establish a methodology for mapping of BSCs, their spectral characteristics with respect to different crust types were analyzed. The resulting reflectance spectra of different crust types had a shallow absorption feature centered around 680 nm in common, in which they differed from the spectra of bare soil.

In October 2004, hyperspectral CASI data with a spatial resolution of 1 m were recorded in conjunction with field spectroscopic measurements in the Succulent Karoo, South Africa. Available spectral indices for Biological Soil Crusts were tested on the image but did not produce satisfying classifications. Therefore, an alternative approach was established based on spectral field data, field observations and the hyperspectral dataset. The newly developed Continuum Removal Crust Identification Algorithm (CRCIA) is based on small and narrow spectral characteristics, that were extracted by continuum removal and subsequently expressed as a set of logical conditions. Using this method, 16.2% of the area which covers 12 km² of gently sloping hills with some granite outcrops were classified as BSCs. Validation of the classification resulted in a Kappa index of 0.831.

In a next step, the methodology will be tested with regard to scale-dependent effects and applied to images covering areas with additional types of BSCs and soil to develop a robust and generally applicable method.     

Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR

Remote sensing of invasive species is a critical component of conservation and management efforts, but reliable methods for the detection of invaders have not been widely established. In Hawaiian forests, we recently found that invasive trees often have hyperspectral signatures unique from that of native trees, but mapping based on spectral reflectance properties alone is confounded by issues of canopy senescence and mortality, intra- and inter-canopy gaps and shadowing, and terrain variability. We deployed a new hybrid airborne system combining the Carnegie Airborne Observatory (CAO) small-footprint light detection and ranging (LiDAR) system with the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) to map the three-dimensional spectral and structural properties of Hawaiian forests. The CAO-AVIRIS systems and data were fully integrated using in-flight and post-flight fusion techniques, facilitating an analysis of forest canopy properties to determine the presence and abundance of three highly invasive tree species in Hawaiian rainforests.

The LiDAR sub-system was used to model forest canopy height and top-of-canopy surfaces; these structural data allowed for automated masking of forest gaps, intra- and inter-canopy shadows, and minimum vegetation height in the AVIRIS images. The remaining sunlit canopy spectra were analyzed using spatially-constrained spectral mixture analysis. The results of the combined LiDAR-spectroscopic analysis highlighted the location and fractional abundance of each invasive tree species throughout the rainforest sites. Field validation studies demonstrated < 6.8% and < 18.6% error rates in the detection of invasive tree species at  7 m² and  2 m² minimum canopy cover thresholds. Our results show that full integration of imaging spectroscopy and LiDAR measurements provides enormous flexibility and analytical potential for studies of terrestrial ecosystems and the species contained within them.