激光气象雷达多次后向散射信号特性分析

利用小角近似方法，分别给出了单次和多次后向散射激光雷达方程.通过引入的多次散射评价参量，分析了接收视场角和光学厚度等因素对多次后向散射信号的影响.理论研究表明:多次后向散射主要与接收视场角和光学厚度密切相关，当接收视场角比发射视场角大10倍，光学厚度超过3时, 多次后向散射信号逐渐增大并占主要优势，当接收视场角比发射视场角大100倍时，光学厚度超过1时，多次后向散射信号开始明显增强.     

随机粗糙面上后向散射的增强

用基尔霍夫近似,研究了随机粗糙面后向散射方向上角度性的散射增强的理论。所得到的极化二次散射强度的解析公式解释了随机粗糙面上多次散射的相干性,并用来定量地计算随机粗糙面后向散射的增强。 关键词：     

用后向散射压缩器产生超高强度激光

报道自制的一台小型的激光系统,用后向布里渊散射与光栅压缩系统组合,把5ns激光脉冲压缩到40ps,压缩率大于100倍.     

大气后向散射比对风速测量的影响

采用同时测量Rayleigh散射和Mie散射混合信号的多普勒频移的单边缘技术,探测低空中（b值的变化,导致测量结果有很大的误差。详细分析了Rb值的变化对风速测量灵敏度及测量结果的影响,并做出了在不同Rb值情况下的风速测量校正曲线。结果表明：随着Rb值的增大,风速测量灵敏度有升高的趋势;随着Rb值偏差的增大,测量的风速误差有增大的趋势;同时,在相同的Rb值偏差情况下,随着径向风速的增大,测量的风速误差也有相应的增大。     

大气后向散射比对风速测量的影响

 采用同时测量Rayleigh散射和Mie散射混合信号的多普勒频移的单边缘技术,探测低空中（<12 km）的大气风速。由于大气后向散射比R_b值的变化,导致测量结果有很大的误差。详细分析了Rb值的变化对风速测量灵敏度及测量结果的影响,并做出了在不同Rb值情况下的风速测量校正曲线。结果表明：随着R_b值的增大,风速测量灵敏度有升高的趋势;随着Rb值偏差的增大,测量的风速误差有增大的趋势;同时,在相同的R_b值偏差情况下,随着径向风速的增大,测量的风速误差也有相应的增大。     

激光在水中气泡微粒的后向散射特性

从激光能量、目标位置、视场大小及气泡厚度等方面对气泡后向散射特性进行研究.采用实验方法研究脉冲激光气泡后向散射特性.实验结果表明,增大激光能量在一定程度上可以有效地改善气泡探测的效果,而气泡发生器位置和视场的合理选择使得气泡探测更容易些,气泡区域厚度的变化对气泡后向散射并没有明显的影响.该实验结论与蒙特卡洛数值模拟的结果一致.     

强壮前沟藻的后向散射特性研究

基于2012年7月藻类培养实验期间的实测生物-光学数据,分析了强壮前沟藻的后向散射特性及其影响因素。结果表明,强壮前沟藻的后向散射系数值具有光谱变化性,并随叶绿素浓度的升高而增大,两者之间呈很好的幂函数关系,相关系数R2最小值可达0.96;此外,由于色素的吸收作用,使得其光谱形状会随叶绿素的变化而变化;同时获得的后向散射比率620 nm处的变化范围在0.006 4～0.011 6之间;总体上,各波段颗粒物后向散射比率也呈现随叶绿素浓度增加而增大的趋势,但在高叶绿素浓度下,这种变化规律并不明显,并且就其光谱形状而言,无论叶绿素浓度高低,其光谱形状始终保持一致;颗粒密度是影响后向散射比率的主要因素之一,两者之间呈幂函数关系,相关系数r在620 nm处高达0.98。     

激光后向散射式大气能见度测量仪样机的研制

大气能见度的高精度、实时性探测对军事装备及军事活动起着重要作用.针对军事装备对能见度测量的实时、精确、仪器便携、功耗低、无合作目标的特殊要求,根据激光后向散射理论,研究了舰用探测大气能见度激光雷达样机的原理、系统组成及其软件实现,并进行了外场试验,试验结果表明样机误差在±20%以内.     

光后向散射法测烟尘浓度的实验研究

设计了一套具有高灵敏度的利用光后向散射法测烟尘浓度的装置,不仅具有实时、在线、连续测量等优点,而且价格低廉、便于安装.通过理论分析获得散射光强与烟尘浓度的关系,并通过自行设计的测量装置测量了不同烟尘浓度下的散射光强,验证了理论的正确性并获得了描述后向散射光强的电信号强度与烟尘质量浓度关系的曲线.实验结果证明在烟尘浓度较低时,后向散射光强与烟尘浓度有很好的线性关系.     

1．06μm激光大气后向散射强度仿真计算研究

针对激光大气后向散射信号对激光导引头制导性能的影响,分析了激光大气后向散射的形成,利用MATLAB语言对1．06μm激光大气后向散射信号强度进行了仿真计算,同时设计开发了一套模拟计算软件,并通过试验验证了软件计算激光大气后向散射信号强度的准确性。     

A Bayesian approach to seafloor classification using multi-beam echo-sounder backscatter data

Seafloor classification using acoustic remote sensing techniques is an attractive approach due to its high-coverage capabilities and limited costs. The multi-beam echo-sounder (MBES) system provides high-resolution bathymetry and backscatter information with 100% coverage. In this paper, we present a seafloor classification method that employs the MBES backscatter data. The method uses the averaged backscatter data per beam. It, therefore, is independent on the quality of the MBES calibration. Also, its performance is insensitive to seafloor type variation along the MBES swathe and corrections for the angular dependence of the backscatter are not needed. The method accounts for the ping-to-ping variability of the backscatter intensity. It estimates both the number of seafloor types present in the survey area and the probability density function for the backscatter strength at a certain angle for each of the seafloor types. Application of the method to MBES backscatter data acquired in a well-known test area in the North Sea shows very good agreement with available ground truth. The method’s discriminatory performance for this area is demonstrated to be comparable to that of taking samples of the sediment. All seafloor types known to be present in the area are resolved for. Application of the method to the Stanton bank data set shows clearly separable areas that differ in seafloor composition.     

作物残茬覆盖度遥感监测研究进展

作物残茬作为农田生态系统的重要组成部分,影响着农田生态系统中的营养物质、碳、水和能量的流动与循环。作物残茬覆盖度作为描述作物残茬数量和分布的重要指标,对于农田生态系统C循环和全球气候变化均有实际意义,具备重要的定量监测价值。遥感技术具有准确、经济、快速大面积监测的能力,因此利用遥感监测区域尺度的作物残茬覆盖度,受到国内外学者的关注。工作回顾总结了目前利用遥感监测作物残茬覆盖度的主要方法和最新研究进展,并根据基本方法的差异以及数据源的不同,从五个类别分别介绍了遥感监测原理与技术革新,对每一类方法的优点和缺陷进行分析,并提出了相应的改进措施。最后对作物残茬覆盖度遥感监测方法的发展趋势进行了展望。     

Acquisition and processing of backscatter data for habitat mapping - Comparison of multibeam and sidescan systems

Often marine habitat surveys use multibeam bathymetry systems to model the seafloor. This describes the morphology but not the terrain lithology or substrate. Backscatter imagery helps the interpreter to better classify the physical environment that may support a particular biological community. In this contribution, the acquisition performance of both multibeam and sidescan sonar backscatter imagery are contrasted and examples shown. The logistical factors affecting the two systems during surveying are discussed and data from both systems compared.Choice of systems for habitat mapping is discussed. A relative cost analysis of the various survey systems is presented with varying resolution and coverage. The size and shape of the footprint, and thus resolution, is variable dependant on many factors, including ship speed, data processing and sampling. The resolution and formation of imagery is important, but high sampling rates are shown not to be a complete solution as over-sampling can present a false impression of high resolution. However, it is suggested that backscatter imagery should have least 7 bit sensitivity to aid visual and digital inspection. Habitat mapping examples are shown using multibeam backscatter and sidescan sonar, where the processing has been optimised for backscatter imagery. A key question is how much of high resolution bathymetry data is essential for habitat mapping, and whether backscatter imagery can provide more of the information required at a higher resolution than a bathymetric morphology map.     

Acoustic measurement of suspensions of clay and silt particles using single frequency attenuation and backscatter

The use of ultrasonic acoustic technology to measure the concentration of fine suspended sediments has the potential to greatly increase the temporal and spatial resolution of sediment measurements while reducing the need for personnel to be present at gauging stations during storm events. The conversion of high-frequency attenuation and backscatter amplitudes to suspended silt and clay concentration has received relatively little attention in the literature. In order to improve the state of knowledge, a laboratory investigation was undertaken by the National Center for Physical Acoustics in cooperation with the USDA-ARS National Sedimentation Laboratory. In these experiments, two immersion transducers were used to measure attenuation and backscatter from 20 MHz acoustic signals propagated through suspended clay (smectite and kaolinite) and silt particles. The resulting data includes attenuation values for a wide range of concentrations (0.3–14 g/L) and particle sizes (0.03–14 μm diameter). Attenuation curves for each particle were compared to the theoretical attenuation curves developed by Urick (1948) and Sheng and Hay (1988) for scattering as presented by Landers (2010) [5,11,12]. In addition, it was found that the backscatter signal could be used to discriminate between suspensions dominated by clay or silt.     

基于FISS成像光谱数据牛奶品种识别研究

利用自主研制的地面成像光谱辐射测量系统(field imaging spectrometer system,FISS)获取了14种典型牛奶样品的高光谱图像数据,并基于此做了牛奶品种识别研究.首先剔除2个异常样品,对剩余12种牛奶样品随机取样,共取1 200个像元样本;为消除高频随机噪声和基线偏移,改善多重共线性,对所有...     

Snow cover monitoring method by using HJ-1 satellite data

Environment and Disasters Monitoring Microsatellite Constellation with high spatial resolution,high temporal resolution and high spectral resolution characteristics was put forward by China.HJ-1B satellite,one of the first two small optical satellites,had a CCD camera and an infrared camera,which would provide an important new data source for snow monitoring.In the present paper,through analyzing the sensor and data characteristics of HJ-1B,we proposed a new infrared normalized difference snow index (INDSI) referring to the traditional normalized difference snow index (NDSI).The accuracy of these two automatic snow recognition methods was estimated based on a supervised classification method.The accuracy of the traditional NDSI method was 97.761 9％ while that of the new INDSI method was 98.617 1％.     

遥感影像分类方法研究进展

遥感影像分类是遥感信息提取的重要手段,是目前遥感技术中的热点研究内容.分类方法是遥感影像分类的重要内容,有效地选择合适的分类方法是提高分类精度的关键.随着遥感技术的发展,传统的非参数分类方法已经难以满足分类精度需求,基于智能算法的非参数分类方法得到了迅速发展,并在遥感影像分类中发挥着重要作用.近年来,组合分类器由于能够...     

基于野外实测数据的珊瑚礁不同底质光谱可分性及珊瑚色素影响分析

珊瑚礁遥感监测的任务之一是获取底栖物质的组成及分布,但由于珊瑚礁存在较强的空间异质性及复杂的光谱,使得目前利用遥感技术进行底栖物质信息提取还存在较大难度。珊瑚礁不同底栖物质的光谱特性是开展珊瑚礁遥感监测的基本先验知识,但目前关于不同珊瑚种类的光谱特性分析研究较为匮乏。本研究基于野外实测光谱数据和模拟卫星遥感数据,开展珊瑚礁不同底质类型的光谱特性研究,特别是针对不同造礁石珊瑚种间及种内的光谱差异进行比较分析,并探讨不同珊瑚体内色素组成对珊瑚光谱特性的影响研究,最后甄选了四种常用卫星数据,通过数值模拟探讨了不同底质类型的光谱可分性。结果显示,利用反射光谱曲线值的大小能较好的识别沙和白化珊瑚,而利用蓝绿红波段反射率的一阶微分值能有效识别出海藻、海草和健康珊瑚。对于不同种类的珊瑚而言,科、属、种、珊瑚形状、珊瑚颜色的不同均会对珊瑚的反射光谱造成影响。叶绿素含量（包含叶绿素a、叶绿素b、叶绿素c）与珊瑚反射光谱值相关性较好,是影响珊瑚光谱反射率的主要因素之一,虫黄藻密度在一定程度上也能影响珊瑚光谱反射率,但不如叶绿素影响明显,其密度的高低会影响珊瑚光谱在局部波段的峰值特征。在目前常用的多光谱卫星数据中,Landsat8数据具有可观测近岸的蓝波段,具备识别沙、白化珊瑚、海藻、健康珊瑚、海草的能力,而IKONOS和Quickbird可识别沙、白化珊瑚和海草。相对而言,SPOT5表现较差,仅能识别沙和白化珊瑚。在不同种类珊瑚的识别方面,多光谱遥感数据由于无法捕捉特征波段,需要采用具有高空间分辨率的高光谱遥感数据进行有效识别。在今后的工作中,将进一步扩大珊瑚礁底质样本数据集,并建立珊瑚礁光谱库,为今后我国珊瑚礁遥感监测体系建立提供数据支撑。     

一种高精度偏振遥感探测方式的精度分析

检偏器的角度误差是影响偏振遥感探测精度的重要因素之一,是许多高精度定量化偏振遥感需要考虑的一个问题。在检偏器(0°,60°,120°)放置的测量系统中,当入射光偏振角接近于0°或180°时偏振测量易产生最大误差值,而偏振角接近30°,90°和150°时,偏振度的测量具有很高的精度;在检偏器(0°,45°,90°)放置方式中,偏振角接近45°的光束测量易具有最大误差值,而偏振角接近于0°,90°和135°时,角度误差对偏振度测量精度的影响很小。除了个别偏振角外,对高偏振度入射光束的偏振测量通常具有较大的偏振测量误差。因此,引进线偏振光的平均偏振度测量精度描述偏振测量装置的优劣,结果表明检偏器(0°,60°,120°)放置方式优于检偏器(0°,45°,90°)放置方式。     

Predicting the probability of wheat aphid occurrence using satellite remote sensing and meteorological data

The occurrence and prevalence of wheat aphid has severe impact on wheat quality and bring about wheat yield loss. Infestation models commonly based on in situ meteorological data can be effective, but are usually lacking spatialized information, which could be provided using multispectral remote sensing datasets. The purpose of this study was to develop a prediction model for aphid occurrence probability by combining remote sensing images and meteorological data in a logistic regression based framework. In such framework, the predictor variables are: land surface temperature (LST), normalized difference vegetation index (NDVI) and perpendicular drought index (PDI) derived from satellite remote sensing image and temperature, precipitation and wind speed coming from meteorological stations. Logistic regression estimated predictor coefficients showed that LST was the most important factor inducing aphid occurrence, followed by NDVI, temperature, precipitation, wind speed and PDI. The prediction accuracy of the model was evaluated by calculating receiver operating characteristics (ROC) against reference data, scoring a value of area under the ROC curve of 0.993, and resulting in an overall predicted accuracy of 94.4% for the estimated subset. In addition, the results suggested that the probability of aphid occurrence obtained by the logistic regression model had a positive correlation with aphid damage level from field data. Based on the validation subset, it was observed that there were lower omission error with 23.68 and commission error with 23.81% and higher overall accuracy with 75.61% when the cut-off probability (p) value was 0.45. The model developed can be a useful tool to predict aphid occurrence and incidence over winter wheat with some advance, and it could be effective in protecting winter wheat from aphid infestation.