A Chirp Transform Algorithm for Processing Squint Mode FMCW SAR Data

Frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) is a lightweight cost-effective high-resolution airborne imaging radar. In squint case, the frequency scaling algorithm, which is suitable for processing nonchirped raw data, cannot be used directly in FMCW SAR data processing because of low system sampling frequency. On the other hand, the continuous antenna motion of FMCW SAR can cause serious distortions in the reconstructed images. In this letter, an improved algorithm called the chirp transform algorithm is proposed. When the effects of the residual video phase are negligible, the algorithm uses a chirp transform to perform the time scaling operation to alleviate the sampling frequency problem. It requires only fast Fourier transforms and multiplications. The range cell migration introduced by the continuous motion is also compensated completely in range-Doppler domain. The algorithm performances are analyzed and are supported by point target simulation experiments.     

三峡水库消落区植物群落演变趋势及优势植物适应策略

三峡水库周期性蓄水显著改变了消落区植物群落组成及多样性,植物群落的演变过程能反映和影响整个消落区生态系统的变化,但目前还缺乏长期连续的观测数据记录,因而本研究基于2009—2021年6月的固定样方长时间序列监测数据和优势植物叶片功能性状数据,分析了消落区3个高程(145～155、155～165和165～175m)区域植物群落多样性和优势植物重要值的变化趋势,通过冗余分析和蒙特卡罗检验揭示了水库运行特征参数和气象因子对消落区植物特征的影响。研究发现:1)消落区3个高程区域,优势植物差异明显,145～155和155～165 m区域以狗牙根、香附子和苍耳等为主,165～175 m区域以狗牙根、野胡萝卜和鬼针草等为主。145～155 m区域植物群落Shannon-Wiener多样性指数(1.47±0.47)和Pielou均匀度指数(0.67±0.07)显著低于165～175 m区域。2)2009—2021年期间,高程145～155和155～165 m区域Shannon-Wiener多样性指数和Pielou均匀度指数呈波动下降趋势,优势植物狗牙根和香附子的重要值呈增加趋势。3) RDA分析表明,...     

BP模型双样本训练方法

根据气象预报应用情况，分析ＢＰ模型训练人工神经元网络中存在的问题，并提出双样本训练方案。试验表明，采用双样本训练的网络，实际预报能力较高。     

GPS授时服务系统在气象业务中的应用

介绍了利用GPS的时间信息组建内部局域网的授时服务系统的方法:首先通过微控制器(MCU)将GPS接收器送出的二进制信息转换成各种不同的格式输出供服务器调用,然后通过基于网络时间协议的服务器/客户端时间校对软件,实现内部局域网计算机的自动对时.此外,针对GPS失锁或出现异常不可用的情况,提出了系统应对处理方法.     

地理学科价值观在教材中的渗透——以人教版高中必修地理1新教材为例

地理学科价值观蕴含在丰富的地理教材中,人教版高中必修地理1新教材是新课改背景下编写的教材,也是学生进入高中后接触到的首本地理教材。因此,如何在教材中渗透学科价值观成为关键问题。本文将从地理学科六个层面的价值观出发,对教材进行梳理与研究。以"何时‘蓝天’常在"为例进行具体分析,为教师对新教材的理解与教学过程的实施提供参考依据,为凸显新教材在课程改革中的重要地位提供更多可思考的路径。     

Statistical analysis of stress transmission in wet granular materials

The micromechanics of wet granular materials encompasses complex microstructural and capillary interconnects that can be readily described through a formal derivation of stress transmission in such a 3‐phase medium. In the quest for defining an appropriate stress measure, the stress tensor expression that results from homogenization [Duriez et al. J Mech Phys Solids 99 (2017): 495‐511] of such a medium provides theoretical insights necessary to extract useful information on the relationship between capillary effects and microforce interactions via several small‐scale parameters whose evaluation can be challenging. Using instead a statistical approach where microvariable distributions are described by probability density functions, the current study provides simple estimates of stress components in terms of only a few tractable microvariables such as coordination number and fabric anisotropy. In particular, the latter recognizes details of contacts such as force interactions being either mechanical or capillary, including interactions with and without mechanical contact. The developed expressions are in a good agreement with discrete element method simulation results of the triaxial loading of a wet granular assembly, notably for hydrostatic (mean) pressure. A new set of dimensionless groups is also identified to characterize the significance of mechanical and capillary physics, which facilitates a better understanding of the contribution of dominating elements to stress, while also providing the opportunity to incorporate important capillary effects in micromechanically based constitutive formulations.     

视超光速源的统计分析

本文收集了视超光速源样本的有关观测数据，在同步加速自康普顿散射机制下导出了各源的多普勒因子，再利用视超光速源的相对论射束模型计算样本源的有关物理量，如射电光度和亮温度，并与它们的观测值作直接的比较，得到较好的相关结果。这些结果支持了活动星系核中具有相对论射束运动的假设。同时我们比较了样本源的射电、光学、Ｘ射线的发现它们之间有一定的相关性，说明在不同波段上的辐射机制可能存在某种联系。     

Work on astrometric binaries in China

The investigations of astrometric binary systems, currently carried out in the People's Republic of China, are described and discussed.Communication presented at the International Conference on Astrometric Binaries, held on 13–15 June, 1984, at the Remeis-Sternwarte Bamberg, Germany, to commemorate the 200th anniversary of the birth of Friedrich Wilhelm Bessel (1784–1846)     

确定“隐蔽层”厚度的pc—1500程序

“隐蔽层”用浅层初至波记录不到,而有“隐蔽层”存在时,在折射解释中常常产生两种误差。确定“隐蔽层”的厚度,是工程物探、工程地质和工程地震学中的一个重要问题。本文给出了确定两种“隐蔽层”厚度的pc—1500程序,简便实用。     

The comparison of PCA and discrete rough set for feature extraction of remote sensing image classification – A case study on rice classification, Taiwan

Texture information offers an extensive solution for image classification by providing better accuracy of image information. However, huge amounts of improper additional texture information may result in a chaotic state, and this leads to uncertainty in the classification process. Considerable portion of earlier works have been carried out through the generally acknowledged procedure of Principal Components Analysis (PCA). However, the PCA method has flaws in the area of influenced and non- influenced attributes. On the whole, whether PCA provides an effective solution to determine the value of knowledge rule in image information still remains a question. This study proposes an innovative method, called Discrete Rough Set method, as a tool for image classification. This study focuses on two crucial issues: (1) The core attributes of the target categories in image classification are systematically analyzed while eliminating surplus attributes rationally; (2) The unique point of each attribute, which influenced the target categories, is successfully found. This is a crucial aspect that is very helpful for the construction of decision rule. Finally, in this study we utilized the expert knowledge classifier and the overall accuracy of Discrete Rough Set (96.67%) exceeds that of the conventional PCA (86.00%) of paddy rice area evaluation from Quickbird image. This result shows that the appropriate classification knowledge can be presented by Discrete Rough Set, and this information can effectively improve the accuracy of image classification. An erratum to this article can be found at