Application of Radar-Measured Rain Data in Hydrological Processes Modeling during the Intensified Observation Period of HUBEX

On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km2 of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.

Space-time clutter model for airborne bistatic radar with non-Gaussian statistics

To validate the potential space-time adaptive processing （STAP） algorithms for airborne bistatic radar clutter suppression under nonstationary and non-Gaussian clutter environments, a statistically non-Gaussian, space-time clutter model in varying bistatic geometrical scenarios is presented. The inclusive effects of the model contain the range dependency of bistatic clutter spectrum and clutter power variation in range-angle cells. To capture them, a new approach to coordinate system conversion is initiated into formulating bistatic geometrical model, and the bistatic non-Gaussian amplitude clutter representation method based on a compound model is introduced. The veracity of the geometrical model is validated by using the bistatic configuration parameters of multi-channel airborne radar measurement （MCARM） experiment. And simulation results manifest that the proposed model can accurately shape the space-time clutter spectrum tied up with specific airborne bistatic radar scenario and can characterize the heterogeneity of clutter amplitude distribution in practical clutter environments.

A New RCS Statistical Model of Radar Target

In this paper, the drawbacks of conventional target fluctuation models used in radar target modeling are set out. It is usually difficult to statistically model a real target because there are very few parameters which can be used to approximate the probability density function (PDF) of a real target's radar cross section (RCS) in conventional target models. A new method of statistical modeling is suggested, according to which the first nth central moment of real target's RCS, combined with the Legendre orthogonal polynomials, is used to reconstruct the PDF of the target's RCS. The relationship between the coefficients of the Legendre polynomials and the central moments of RCS are deduced mathematically. Through a practical computing example, the error-of-fit is shown as a function of the orders of Legendre coefficients. By comparing the errors-of-fit caused by both the new model and the conventional models, it is concluded that the new nonparametric method for statistical modeling of radar targets is superior.

A Model for Retrieval of Dual Linear Polarization Radar Fields from Model Simulation Outputs

An algorithm for retrieving polarimetric variables from numerical model fields is developed. By using this technique, radar reflectivity at horizontal polarization~ differential reflectivity, specific differential phase shift and correlation coefficients between the horizontal and vertical polarization signals at zero lag can be derived from rain, snow and hail contents of numerical model outputs. Effects of environmental temperature and the melting process on polarimetric variables are considered in the algorithm. The algorithm is applied to the Advanced Regional Prediction System （ARPS） model simulation results for a hail storm. The spatial distributions of the derived parameters are reasonable when compared with observational knowledge. This work provides a forward model for assimilation of dual linear polarization radar data into a mesoscale model.

A Composite Approach of Radar Echo Extrapolation Based on TREC Vectors in Combination with Model-Predicted Winds

Extending the lead time of precipitation nowcasts is vital to improvements in heavy rainfall warning, flood mitigation, and water resource management. Because the TREC vector （tracking radar echo by correlation） represents only the instantaneous trend of precipitation echo motion, the approach using derived echo motion vectors to extrapolate radar reflectivity as a rainfall forecast is not satisfactory if the lead time is beyond 30 minutes. For longer lead times, the effect of ambient winds on echo movement should be considered. In this paper, an extrapolation algorithm that extends forecast lead times up to 3 hours was developed to blend TREC vectors with model-predicted winds. The TREC vectors were derived from radar reflectivity patterns in 3 km height CAPPI （constant altitude plan position indicator） mosaics through a cross-correlation technique. The background steering winds were provided by predictions of the rapid update assimilation model CHAF （cycle of hourly assimilation and forecast）. A similarity index was designed to determine the vertical level at which model winds were applied in the extrapolation process, which occurs via a comparison between model winds and radar vectors. Based on a summer rainfall case study, it is found that the new algorithm provides a better forecast.

Modified GIT model for predicting wind-speed behavior of low-grazing-angle radar sea clutter

A modified GIT model for describing the variational trend of mean clutter reflectivity as a function of wind speed is proposed. It uses two slope adjustment factors and two critical wind-speed factors to define and adjust the increasing slope of reflectivity with respect to wind speed. In addition, it uses a constant factor to compensate the overall amplitude of clutter reflectivity. The performance of the modified GIT model has been verified on the basis of the L-band low-grazing-angle radar sea clutter data. The results are in good agreement with the experimental data, indicating that the model is more effective in predicting the wind-speed behavior of clutter reflectivity than the conventional GIT model, especially for lower and higher wind speeds. We believe that the proposed model can provide deeper insights into the relationship between radar sea clutter reflectivity and sea state conditions.

HIGH RESOLUTION PARAMETRIC MODELLING FOR TWO-DIMENSIONAL RADAR TARGET USING PRONY ALGORITHM

On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.

Evaluation of Unified Model Microphysics in High-resolution NWP Simulations Using Polarimetric Radar Observations

The UK Met Office Unified Model（UM） is employed by many weather forecasting agencies around the globe. This model is designed to run across spatial and time scales and known to produce skillful predictions for large-scale weather systems. However, the model has only recently begun running operationally at horizontal grid spacings of ～1.5 km [e.g.,at the UK Met Office and the Korea Meteorological Administration（KMA）]. As its microphysics scheme was originally designed and tuned for large-scale precipitation systems, we investigate the performance of UM microphysics to determine potential inherent biases or weaknesses. Two rainfall cases from the KMA forecasting system are considered in this study： a Changma（quasi-stationary） front, and Typhoon Sanba（2012）. The UM output is compared to polarimetric radar observations in terms of simulated polarimetric radar variables. Results show that the UM generally underpredicts median reflectivity in stratiform rain, producing high reflectivity cores and precipitation gaps between them. This is partially due to the diagnostic rain intercept parameter formulation used in the one-moment microphysics scheme. Model drop size is generally both underand overpredicted compared to observations. UM frozen hydrometeors favor generic ice（crystals and snow） rather than graupel, which is reasonable for Changma and typhoon cases. The model performed best with the typhoon case in terms of simulated precipitation coverage.

A Model Study of Three-Dimensional Wind Field Analysis from Dual-Doppler Radar Data

A three-dimensional wind field analysis sollware based on the Beigng-Gucheng dual-Doppler weather radar system has been built, and evaluated by using the numerical cloud model producing storm flow and hydrometeor fields. The effects of observation noise and the spatial distribution of wind field analysis error are also investigated.

Weather Radar Data and Distributed Hydrological Modelling: An Application for Mexico Valley

The frequent occurrence of exceptionally very heavy rainfall in Mexico during the summer causes flash floods in many areas and major economic losses. As a consequence, a significant part of the annual government budget is diverted to the reconstruction of the disasters caused by floods every year, resulting hold up in the country development. A key element to mitigate the flash flood hazards is the implementation of an early warning system with the ability to process the necessary information in the shortest possible time, in order to?increase structural and non-structural resilience in flood prone regions. The real-time estimation of rainfall is essential for the implementation of such systems and the use of remote sensing instruments that feed the operational rainfall-runoff hydrological models is becoming of increasing importance worldwide. However, in some countries such as Mexico, the application of such technology for operational purposes is still in its infancy. Here the implementation of an operational hydrological model is described for the Mixcoac river basin as part of the non-structural measures that can be applied for intense precipitation events. The main goal is to examine the feasibility of the use of remote sensing instruments and establish a methodology to predict the runoff in real time in urban river basins with complex topography, to increase the resilience of the areas affected by annual floods. The study takes data from weather radar operated by the National Meteorological Service of Mexico, as input to a distributed hydrological model. The distributed unit hydrograph model methodology is used in order to assess its feasibility in urban experimental basin. The basic concepts underlying the model, as well as calibration and validation are discussed. The results demonstrate the feasibility of using weather radar data for modeling rainfall-runoff process with distributed parameter models for urban watersheds. A product resulting from this study was the development of software Runoff Forecast Model (ASM), for application in distributed hydrological models with rainfall data in real time in watersheds with complex terrain, which are usually found in Mexico.

CROSS-RANGE RESOLUTION OF SYNTHETIC APERTURE RADAR BASED ON DIVING MODEL

This paper concentrates on the cross-range resolution of Synthetic Aperture Radar(SAR) based on diving model.In comparison to the azimuth resolution,the cross-range resolution can manifest the two-dimensional resolution ability of the imaging sensor SAR correctly.The diving model of SAR is an extended model from the conventional stripmap model,and the cross-range resolution expression is deduced from the equivalent linear frequency modulation pulses' compression.This expression points out that only the cross-range velocity component of the horizontal velocity contributes to the cross-range resolution.Also the cross-range resolution expressions and the performance of the conventional stripmap operation,squint side-look operation and beam circular-scanning operation are discussed.The cross-range resolution expression based on diving model will provide more general and more accurate reference.

Hybrid micromotion-scattering center model for synthetic aperture radar micromotion target imaging

Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.

ANALYSIS OF THE RETURNED SIGNAL MODEL IN BISTATIC RADAR SYSTEMS

Taking the relativistic effect of high velocity moving target into account, the Doppler shift, polarization deflection, reflection coefficient and phase delay of reflected electric field are analyzed rigorously under the assumptions that incident signal to the target is a plane wave and the target is a perfect conductor plane; and their analytic expressions are obtained. The present results are of practical significance to some extent for the accurate expression of the wideband returned signal of a high velocity moving target in the bistatic radar system and for the understanding of wideband ambiguity functions.

煤矿巷道空间毫米波雷达测量特性与重建方法

【目的】煤矿井下空间测量是煤矿透明地质建模的重要组成,然而煤矿巷道环境复杂、信息获取不全、感知数据精度不足等难题亟待解决。【方法】首先,深入研究粉尘、水雾、围岩结构等复杂环境因素下毫米波雷达信号特性,建立煤矿巷道围岩毫米波信号衰减模型,对比分析复杂环境因素毫米波雷达的影响机理。其次,针对煤矿复杂环境下毫米波雷达的巷道数字建模问题,提出巷道空间毫米波雷达点云泊松表面重建方法。通过实验测试与模拟巷道环境验证,在揭示煤矿复杂环境条件下的毫米波雷达感知机理基础上,实现了煤矿巷道空间测量与数字建模重构。【结果和结论】结果表明:(1)毫米波雷达能够适应煤矿井下多粉尘、多水雾、围岩粗糙的巷道环境,为煤矿巷道空间重建提供有效数据。(2)泊松表面重建方法能够充分展示真实巷道围岩信息,重建巷道整体宽度的平均绝对误差百分比为0.59%,巷道整体高度的平均绝对误差百分比为0.78%。煤矿复杂环境下毫米波雷达空间测量特性与重建方法的研究,为煤矿井下透明地质建模提供巷道空间测量数据,对推动煤矿智能开采具有重要意义。

基于网格化和雷达图的建筑抗震设防最优烈度决策模型研究

目前的建筑抗震设防最优烈度研究主要是从经济性或安全性进行考虑,然而合理的建筑抗震设防最优烈度需要综合考虑经济和安全性指标。本文将研究区域进行网格化,结合其周围历史地震数据进行地震危险性分析,以经济性指标和安全性指标作为抗震设防最优烈度评价指标;运用博弈论组合赋权法确定各指标权重,建立基于网格化和雷达图的建筑抗震设防最优烈度决策模型,将该模型运用到四川省崇州市钢混结构和砖混结构的抗震设防研究中。通过对比分析该模型数据发现:钢混结构按8度设防时,相比于6度、7度和9度设防,其抗震设防综合效益分别提升57.2%、29.6%和3.9%;砖混结构按8度设防时,相比于未设防、6度、7度和9度设防的抗震设防综合效益分别提升60.6%、19.2%、2.4%和1.9%。因此,崇州市钢混结构和砖混结构按8度设防时,为最优抗震设防烈度,抗震设防综合效益最佳,验证了该模型的有效性。

天气雷达站电磁环境影响监测研究

天气雷达站产生的超标电磁辐射会对人体造成严重的损伤。为此,提出天气雷达站电磁环境影响监测与分析。分析天气雷达站电磁影响因素,结合发射天线的方向函数,构建雷达功率密度模型。测试结果表明,对于S波、C波段、X波段,真实值与计算值呈现随距离增加而降低的趋势。对于三个波的频段,当接近天线的远场区时,计算值与真实值逐渐接近,相对误差均较小,说明模型在远场区的适用性更强;研究算法与实测值的拟合程度较高;在模型的应用中,真实反映了某市区的电磁辐射情况。

基于DEM的雷达阵地选址预处理方法研究

防空预警雷达阵地选址的优劣直接影响雷达本身及防空武器作战效能的发挥.针对基于数字高程模型(DEM)的常规实时计算方法存在耗时、耗力的问题,在明确阵地选址预处理内容的基础上,提出了预处理的具体流程和参数计算方法.通过数据预处理,以空间换时间的方式解决了阵地自动选址计算量大、耗时长的问题.实例仿真结果表明,该雷达阵地选址预处理方法大大缩短了自动选址时间,有效提高了选址效率.

基于机载多角度InSAR技术的复杂地形高精度DEM重建方法

干涉合成孔径雷达(Interferomtric Synthetic Aperture Radar,InSAR)是全天时、全天候获取三维地表信息重要的技术手段。机载InSAR系统具有机动灵活、多角度获取数据的优势,可以高效率、高精度获取数字高程模型(Digital Elevation Model,DEM)数据。但是,在地形复杂区域,InSAR侧视成像易在地形陡峭区域形成较大范围的阴影和严重的叠掩现象,阴影和叠掩区域在SAR图像上体现为信息的丢失,从而导致DEM数据大面积无效数据的存在,严重影响DEM数据的质量及应用。针对这一问题,本文提出了基于机载多角度InSAR技术的复杂地形高精度DEM重建方法,基于考虑地形起伏的机载多角度InSAR数据获取任务规划设计,最大程度的避免阴影和叠掩导致的无效数据;基于高精度InSAR数据处理,保证每个角度DEM数据精度的高度一致性;基于快速多角度DSM数据融合与滤波处理,实现多角度InSAR体制复杂地形DEM高精度重建。本文以四川省西部山区大坡度、非连续等复杂地形为例,基于本文提出的方法,利用3个角度InSAR数据融合处理,生成了高精度DEM数据,试验结果表明,本文提出的方法获取复杂地形DEM数据高程均方根误差为0.6 m,同时,数据有效率大于99%。

雷达侦察接收机电磁环境评估和分级方法

针对雷达侦察接收机电磁环境分级困难、描述粗略、评估不准、操作性弱等研究现状,通过深入分析侦察接收机的作战环境、工作原理,以及性能指标受电磁环境的影响程度,提出了一种基于电磁环境效应的雷达侦察接收机电磁环境复杂度评估与分级方法。首先对雷达侦察接收机面临的电磁环境进行了分析,根据侦察接收机的工作机理及其技战术性能提炼并构建了针对侦察接收机复杂电磁环境评估的指标体系,最后给出了层次结构评估模型以及电磁环境等级划分规则,为研究雷达侦察接收机面临的复杂电磁环境及其分析评估提供技术支撑,同时也为提高侦察接收机在复杂电磁环境下的作战能力提供技术支持。

基于雷达估测降雨及WRF-Hydro模型的典型山洪模拟研究

受复杂地形与基础气象水文资料缺乏限制,山区小尺度流域的水文预警预报技术较为薄弱,利用高分辨率雷达观测资料驱动分布式水文模型是提高山区小流域洪水预报性能的有效途径之一。本文以位于重庆中部的山区小流域二河流域为研究区域,开展基于雷达估测降雨数据的WRF-Hydro模型在山区小流域的山洪模拟研究,以评估雷达估测降雨的水文应用效果和WRF-Hydro模型在山区小流域的适用性。选取流域内典型的暴雨洪水过程,利用S波段的多普勒天气雷达的估测降雨数据驱动WRF-Hydro模型,并结合新安江模型进一步对比分析模拟效果。研究结果表明:(1)在二河流域,采用雷达估测降雨数据驱动WRF-Hydro模型,可以较好地模拟洪水过程、洪水流量以及峰现时间,纳什效率系数高于0.65,克林-古普塔效率系数高于0.50,相关系数高于0.85。(2)将WRF-Hydro模型与新安江模型进行比较分析,在二河流域,WRF-Hydro模型的模拟效果优于新安江模型,纳什系数差值0.03,相关系数差值为0.04,进一步表明WRF-Hydro模型在山区小流域较优的洪水模拟性能。总体而言,基于雷达估测降雨数据的WRF-Hydro模型在二河流域表现出了良好的模拟洪水的性能,可进一步在类似小尺度山区流域进行应用研究。