用CMC-80双板机实现的高空气象雷达数据接口和预处理系统

一、引言为了获得高空气象要素,可用气球或火箭携带无线电探空仪升空,由气象雷达追踪其运动轨迹,可算出不同高度层上的风向、风速。同时,探空仪将高空气象信息(温度、湿度、压力等)不断发回地面被气象雷达接收,根据这些遥测数据即可求出完整的高空气象要素供天气预报用。这显然要求对雷达探空数据进行实时的处理,因此近年来,国内各气象部门纷纷选用了8位字长的微型机系统来处理各类气象雷达探空数据。但由于高空气象雷达是自动跟踪与录取且采用小周期探空仪,数据率远较其它测风气象雷达为高,用8位机实时处理对速度与内存要求苛刻。因此,我们选用CMC-80双板机(除结构上多一块板外,其主要功能类似于其它Z80单板机)与主机(BCM-3)组成双     

L波段电子探空仪系统的探空终止高度受环境温度影响的研究

基于海拉尔区GCOS站2011-2020年L波段电子探空仪系统的探空终止高度的观测数据及该地区这10年的气温观测数据,利用excel统计分析的方法,对每年的探空年平均球炸高度、每年各月的探空月平均球炸高度、每年07时15分与19时15分年球皮质量不达标的数量和10年各月探空仪在高空中出现故障的次数进行统计分析,并与对应时间段内的气温数据进行对比分析。得出结果：电子探空仪系统在每年当中的1、2、3、11和12月份其探空月平均球炸高度基本上均未达到3.5万米以上,其探空仪在高空中出现故障的次数整体偏大,而这几个月份的月平均气温基本上均小于0℃;在每年当中的19时15分年球皮质量不达标的数量均明显高于07时15分的数量,而19时15分球炸时的年平均高空环境温度均明显低于07时15分的温度;低温是影响探空终止高度的关键因素。     

8毫米云雷达与探空观测确定云底和云顶高度的对比分析

利用地基Ka波段云雷达和无线电探空仪数据进行云边界识别和对比分析研究。结果表明,8毫米波云雷达探测的云底高度比无线电探空仪观测偏低约300m,大多数情况下二者识别的云底高度接近;而判定的云顶高度偏差较大。雷达与探空云底高度判别偏差较大时,在云下常存在大气"干层",此时雷达探测更为灵敏;探空仪水平漂移及其湿度传感器的探测误差随高度增加是造成两者偏差的主要原因。通过计算和对比雷达反射率的时空变化率,给出了云雷达确定云底和云顶高度的一个可信度判据。     

L波段气象雷达浅谈

随着经济的发展气和象探测要求越来越高,以及和国际气象观测接轨,从前主要运用于军事的雷达现在逐渐广泛运用于气象观测及各种民用设备,而我国现阶段高空探测主要是以我国自主研制生产的L波段测风雷达为主。L波段雷达区别于其他雷达显著特点就是波长较长,其波长在18cm左右,相对于其它短波雷达它具有穿透力强、损耗小、所需功率小和观测距离远的特点,能够尽可能减少大气中水汽粒子、尘埃等物质对它信号的衰减,适用于观测低速、简单的运动,由于高空仪器移动速度较慢,多普勒频移现象能够忽略,因此L波段雷达可以基本满足现阶段高空观测的需要,是一款简单实用的高空观测利器。本文主要是以L波段为主来做一个阐述,具体将会讲解到笔者从事几年L波段雷达探测和维护工作的一些经验,同时为了增加本文的立体感,将会对L波段雷达和其他雷达做一个对比讲解。     

GFE（L）1型雷达故障分析及处理

GFE(L)1型雷达在整个高空大气探测系统中占据了重要的地位,本文基于L波段雷达在探空过程中较为常见的故障,分析总结出L波段雷达一些检修的方法,为同行维护人员提供参考。     

一种GPS探空仪风失量反演算法

给出了采用矢量滑窗平均来反演GPS探空仪风矢量的算法。采用此算法对探空数据进行处理,可以明显减少大气波动的影响,得到以矢量形式表征的测风数据。通过和业内公认的标准探测设备Vaisala GPS探空仪的测风数据比较,表明此算法在实际应用中的可行性和优越性。     

无人机测风技术研究

随着航空、大气探测以及微电子技术的发展和应用,无人机测风技术日益成为无人机应用的一项重点研究内容。介绍了目前常用的无人机测风方法,如水平空速归零法、解析测风方法、航位推算法以及皮托-静压管测风法等,阐述了各种高空风风速测量原理以及各自优缺点,指出皮托-静压管测风法更适合复杂环境下实时探测,具有良好的应用前景,同时分析了皮托-静压管测风法的关键技术,以达到提高无人机风场测量精度的目的。     

水面船只SAR探测的极化方式研究

利用SIR-C SAR的C和L波段全极化数据,分析水面船只的极化散射特性和船只与背景海面雷达后向散射的信噪比特性,研究水面船只SAR探测的最优极化方式。结果显示,二面角散射是水面船只SAR成像的主要机理。线性极化中,HV极化具有最大的船只与背景海面雷达后向散射信噪比。与线性极化相比,圆极化的雷达后向散射信噪比更优。C波段和L波段的水面船只的极化散射特性存在较大的差异,L波段的信噪比大于C波段的信噪比。水面船只的雷达后向散射特性表明,L波段的圆极化是水面船只探测的最优极化方式。     

基于时分复用技术的组网地基雷达半实物仿真系统[BT)]

针对雷达半实物模型在组网仿真中试验复杂、设备成本高且通用性差的问题,设计了一套基于时分复用技术的组网地基雷达半实物仿真系统;该系统包括L波段雷达半实物系统、P波段雷达半实物系统以及P波段雷达数学模型;仿真试验过程中,先通过软件预先仿真得到雷达工作时序文件,依据该文件控制雷达半实物和数学模型的工作时间,设定L波段雷达半实物系统或P波段雷达半实物分时段重复应用,结合数学模型仿真结果进行分析,得到组网雷达的目标探测结果;通过仿真想定验证了该套系统能够正常运行,并得到正确的仿真结果;该系统的实现提高了仿真逼真度与可信度,缩减了设备成本,简化了试验方法,降低了试验难度。     

基于嵌入式系统的测冰雷达数据远程实时读取系统的研究与实现

介绍了一种结合Internet网络和嵌入式技术的测冰雷达探测数据远程读取系统。系统基于树莓派构建嵌入式系统,采用nginx和sqlite分别构建Web服务器和相应的数据库;树莓派通过USB接口采集测冰雷达的冰层厚度探测数据,并外接USB无线网卡通过无线局域网发射器接入Internet网络;远程移动终端作为数据读取方,通过中国移动3G网络访问树莓派上所搭建的Web服务器,最终以FTP页面形式下载所采集到的冰层厚度数据,并以HTTP页面形式绘制冰层厚度报表呈现给用户,实现冰层的实时观测。实验表明,系统实现了远程实时读取测冰雷达探测数据的目标,解决了传统测冰雷达探测数据先存盘后处理的低实时性问题。     

高空湿度探测用加热式湿度传感器的研制

为实现高空高湿环境下对湿度的准确测量,本文设计和研究了集成加热功能的湿度传感器,在探空仪进行高空湿度探过程中利用两只加热式湿度传感器进行轮流加热除湿和湿度测量。通过对聚酰亚胺湿敏材料进行改性和合成,设计和制作了加热式的电容型湿度传感器,其灵敏度为0.2195 pF/%RH、响应时间小于1 s、湿滞为4.8%RH、半年漂移量在±0.3%RH以内。通过分析不同温度下的加热恢复时间,制定了加热式湿度传感器轮流工作的机制,轮流加热时间和周期分别为2s和120 s。并利用数据采集电路以及GPS探空仪对加热式湿度传感器进行了地面静态性能和高空动态性能测试,其高空湿度探测结果与VA SALA RS92的显示出较好的一致性和较低的湿度误差。本文研制的加热式湿度传感器能具有良好的地面性能,实现了交替加热除湿和湿度测量的功能,具有高空湿度探测的应用潜力。     

基于TDLAS技术的机载水汽密度测量仪

近年来,可调谐激光吸收光谱(TDLAS)技术发展迅速,在气体浓度检测领域被广泛应用。水汽密度的测量在高空气象业务中占有重要地位,但我国目前的高空气象业务基本依靠探空气球的数据开展,用这种方式测量水汽密度具有数据量少、数据不够新、成本高的缺点。在TDLAS技术的基础上,结合机载环境情况,实现了在机载环境下实时、准确、快速地测量水汽密度,为飞机在飞行过程中提供了实时的气象参考;为气象预报提供了更加丰富的气象数据;也为特定区域进行机载气象探测提供了参考。     

The impact of assimilation of AMSU data for the prediction of a tropical cyclone over India using a mesoscale model

Tropical cyclones form over the seas: a typical data‐sparse region for conventional observations. Therefore, satellites, especially with microwave sensors, are ideal for cyclone studies. The advanced microwave sounding unit (AMSU) , in addition to providing very valuable data over non‐precipitating cloudy regions, can provide very high horizontal resolution of the temperature and humidity soundings. Such high‐resolution microwave data can improve the poorly analysed cyclone. The objective of this study is to investigate the impact of ingesting and assimilating the AMSU data together with conventional upper air and surface meteorological observations over India on the prediction of a tropical cyclone which formed over the Arabian Sea during November 2003 using analysis nudging. The impact of assimilating the AMSU‐derived temperature and humidity vertical profiles in a mesoscale model has not been tested yet over the Indian region. Such studies are important as most weather systems over India form over the seas. The present study is unique in the sense that it addresses the impact of ingesting and assimilating microwave sounding data (together with conventional India Meteorological Department data) on the prediction of a tropical cyclone, which formed over the Arabian Sea during November 2003 using analysis nudging. Two sets of numerical experiments are designed in this study. While the first set utilizes the National Center for Environmental Prediction (NCEP) reanalysis (for the initial and lateral boundary conditions) only in the fifth‐generation mesoscale model simulation, the second set utilized the AMSU satellite and conventional meteorological upper air and surface data to provide an improved analysis through analysis nudging. The results of the two sets of model simulations are compared with one another as well as with the NCEP reanalysis and the observations.

The results of the study indicated that the impact of ingesting and assimilating microwave sounding data and the conventional meteorological data through nudging resulted in an improvement in the simulation of wind asymmetries and the warm temperature anomalies. The with‐assimilation run simulated stronger wind speeds and stronger vertical velocity motion as compared with the without‐assimilation run. The time series of the minimum sea level pressure (SLP) and maximum wind speed for the simulations with the microwave sounding data and conventional meteorological data show better agreement with the observations than the simulations without the assimilation. The central minimum pressure of the simulations with the modified analysis are lower by 7 hPa as compared with the simulations without the assimilations. Even though there is not much of a difference in the maximum wind speed between the two simulations at the initial forecast time, the results indicate that the simulations with microwave sounding data and conventional meteorological data reveal a marked (9 m/s) increase in the maximum wind speed over the simulations without the assimilation. While the lowest central pressure estimated from the satellite image is 988 hPa, the simulations with microwave sounding data and conventional meteorological data show a value of 999.5 hPa for the lowest central minimum pressure. One reason for the inability of the simulation with improved analysis to achieve the observed lowest SLP is that the NCEP reanalysis had manifested an extremely weak system in the first place and, despite assimilation with microwave sounding data and conventional meteorological data, only a moderate improvement in the lowest SLP could be achieved. A proper appreciation of the impact of the microwave sounding data can be obtained by comparing with the lowest SLP obtained from the simulation without assimilation which showed a value of 1007 hPa. The initial mis‐representation in the location of the centre of the cyclone in the NCEP reanalysis with respect to the observed location has led to marked errors in the track prediction of both the model simulations. The assimilation of microwave satellite data is yet to be implemented in the current operational regional model over India and hence the results of this study may be relevant to the operational tropical cyclone forecasting community.     

风廓线雷达对塔克拉玛干沙漠沙尘及晴空湍流的探测研究

利用塔克拉玛干沙漠大气环境观测试验站2010年6~8月风廓线雷达探测资料,在前期研究基础上,进一步分析了沙尘天气的雷达回波强度以及沙漠夏季晴空湍流发展演变特征。研究表明:①在具有一定湍流脉动和大气湿度的前提下,风廓线雷达可以在沙尘天气进行有效探测,浮尘、扬沙、沙尘暴天气现象在雷达回波强度时间-高度图上有清晰的印记和表现,浮尘、扬沙、沙尘暴发生时间段与回波强度大值区对应一致,从回波强度图上可以大致识别沙尘输送高度,沙尘天气的雷达等效回波强度约在-18~10 dBZe范围变化;②塔克拉玛干沙漠夏季典型晴空湍流旺盛区域发展高度可达到3 500~4 000 m,湍流平均以0.13~0.16 m/s的上升速度向高空发展,下午15:00以后,湍流强度最大区域不在近地边界层,而在大气边界层顶附近;C²n时间-高度变化在一定程度上反映了大气边界层的演变特征,沙漠夏季晴天边界层高度有可能达到3 500~4 000 m。     

Detection of ice types in the Eastern Weddell Sea by fusing L- and C-band SIR-C polarimetric quantities

This article discusses the use of spaceborne polarimetric L-band and C-band synthetic aperture radar (SAR) data for sea-ice detection and classification. The benefits of combining L-band with C-band polarimetric quantities for supervised sea-ice classification in the Eastern Weddell Sea, Antarctica, are investigated. In the experiments, we compared the performance of a maximum likelihood (ML) classifier when used with the combined preferred polarimetric parameters and the individual ones, respectively. The relation between the classification accuracy and the preferred number of polarimetric parameters for classification was examined as well as whether principal component analysis (PCA) and locally linear embedding (LLE) can be used to reduce the dimensionality of the parameter sets. Combining dual-frequency polarimetric quantities improves classification accuracy compared to using individual single-frequency polarimetric quantities. By increasing the dimensionality of the preferred polarimetric parameter sets, the classification using high dimensionality can either result in improvements over the smaller subsets or result in no significant differences. Therefore, using all available polarimetric quantities over the study region is recommended. Further, data fusion with a PCA-based approach is found to be beneficial for sea-ice detection and classification, and poor results have been produced with an LLE-based approach.     

小卫星大气微波探测仪及其应用模拟研究

小卫星大气微波探测仪技术是目前微波遥感技术的一个研究热点。通过研制一台小卫星大气微波探测仪（以下简称大气微波探测仪,英文简称SAMS）并搭载在我国的商业小卫星上,实现对大气温湿度、极端天气和降雨的快速测量。介绍了SAMS的应用方面设计的特点,并结合目前的灵敏度测试数据,分析了在轨应用性能,尤其是在海面气压、大气湿路径延迟反演方面小卫星微波探测仪提供了一种新型灵活的探测手段,同时也对载荷在大气温度和湿度廓线探测常规的探测能力方面也进行了总结和分析,为卫星数据的应用和开发打下基础。     

机头结冰对大气数据系统测量影响研究

大气数据传感器安装于机头部位的飞机在遭遇结冰气象时,机头结冰会影响大气参数的测量精度。采用计算流体力学方法,对某两型运输飞机的大气数据系统进行模拟,考虑在机头结冰情况下的大气数据系统静压系数和迎角测量值的变化,获得了机头结冰对高度测量和速度测量的影响差量。研究表明,在两型运输飞机机头结冰状态下,中小迎角对大气数据系统静压和迎角测量的影响较小;大迎角对大气数据系统静压和迎角测量的影响较大,对应的高度测量影响量超过了10 m,速度测量影响量超过了2 kn。研究结果对于同类型飞机类似方向的研究具有一定的参考意义。     

SAR变化检测技术发展综述

合成孔径雷达(SAR)具有全天候、全天时的特点,是很好的变化检测信息源,研究SAR图像变化检测技术有着非常广阔的应用前景。系统介绍了SAR变化检测的整个流程--数据预处理、变化检测算法、检测后处理及变化检测算法评价。为了方便算法设计者,分门别类地阐述了变化检测算法的主要方法及核心决策规则,包括差值法、统计假设检验法、预测模型、相干模型;并对每种方法的特征进行了分析和比较。针对SAR技术的迅猛发展,我们对将来SAR变化检测技术的发展方向给予了预测。     

Integration of TerraSAR-X and PALSAR PSI for detecting ground deformation

In connection with the detection of various spatial- and temporal-scale ground settlements, an integrated persistent scatterer interferometry (PSI) approach is discussed using multi-source, multi-temporal, and multi-resolution synthetic aperture radar (SAR) data. Based on the comprehensive analysis of characteristics of available radar sensors, two remote-sensing SAR data sets were selected: 1 m resolution X-band TerraSAR-X and 10 m resolution L-band Advanced Land Observing Satellite (ALOS) phased array L-band SAR. ‘Tianjin Binhai New Area’ has become one of the most important economic centres in China, and one of its fast-developing urban areas, Tanggu, was selected as the study area. PSI processing was conducted on both data sets. Substantial validation was performed for PSI results from both data sources using levelling measurement. The overall good agreement confirmed the ground deformation maps derived from both data sets. Integration of PSI results appears to be a potentially significant contribution to solving the problems related to common spatial and temporal gaps when using single-type data sets. Application of both data sets revealed the capability of integrated PSIs to measure ground deformation with strong temporal and spatial variation, thereby improving the interpretation of ground deformation characteristics which increases the confidence of hazard assessment and provides some insight into complex underlying mechanisms.     

基于机器视觉的雨雾天驾驶辅助系统设计

随着私家车数量日益增多,雨雾天交通安全问题成为了亟待解决的难题;在嵌入式硬件资源有限的情况下,为驾驶用户设计了基于机器视觉的雨雾天语音辅助驾驶系统;系统结合了湿度传感器、轻量化去雾神经网络AOD-NET和目标检测模型YOLOv5n;在目标检测模型YOLOv5n上,利用K-means++算法重新设计锚框,选取较优的骨干网络并利用模型剪枝进一步压缩模型大小;实验结果表明,改进的模型在Jetsonnano上的FPS达到了17.78,最终mAP在人工加雾、分辨率变化的TT100K (Tsinghua-Tencent 100K)数据集到达了65.8%,满足了正常天气与雨雾天气下的驾驶辅助实际应用。