Use of dual-polarization radar data for evaluation of attenuation on a satellite-to-earth path

Using conventional (single-polarization) radar data to assess attenuation due to rain on satellite-to-Earth paths requires the assumptions that the drops have a particular statistical distribution of sizes, and that the drops are of water. In the very localised regions of intense rain which influence such paths most severely, these assumptions can lead to large errors. This paper presents comparisons between direct measurements of attenuation and those computed using data from a dual-polarization radar technique. This technique can considerably reduce the errors of radar-derived estimates of attenuation. It also gives a clear distinction between ice and water.     

基于进化神经网络的地空路径雨衰减模型

雨衰减对工作在高频的地空通信链路稳定性具有很大影响。本文在考虑多个参数对雨衰减非线性影响的基础上,建立了基于进化神经网络的雨衰模型,并与ITU－R模型进行了比较。结果表明,利用本文提出的模型进行高频电波的预测具有更好的精度,可降低平均误差0.64dB,并减小标准偏差0.79bD,为雨衰减预测提供了一种新的方法。     

Slant path rain attenuation and path diversity statistics obtained through radar modeling of rain structure

Single and joint terminal slant path attenuation statistics at frequencies of 28.56 and 19.04 GHz have been derived employing a radar data base obtained over a three-year period at Wallops Island, VA. Statistics were independently obtained for path elevation angles of20deg,45deg, and90degfor purposes of examining how elevation angles influences both single terminal and joint probability distributions. Both diversity gains and autocorrelation function dependence on site spacing and elevation angles were determined employing the radar modeling results. Comparisons with other investigators are presented. An independent path elevation angle prediction technique was developed and demonstrated to fit well with the radar derived single and joint terminal radar derived cumulative fade distributions at various elevation angles.     

Annual and diurnal slant path rain attenuation statistics in Athens obtained with the synthetic storm technique

We present annual/seasonal rainfall rate statistics derived from a 29-month data bank of 1 sample/min, measured by a disdrometer located inside the National Technical University of Athens Campus. We discuss both the inaccuracy and the unavailability of the measuring equipment, as well as the statistical reliability of the rainfall rate sample. Additionally, after applying the Synthetic Storm Technique on the measured rainfall rate time series, we present the first long term simulated annual/seasonal and diurnal rain attenuation statistics, at 12 GHz for a hypothetical downlink from Hellas Sat 2 to Athens. According to the results, we predict that communication downlinks working in the afternoon and early evening hours must be given an extra power margin, to compensate for high rain attenuation.     

New radar studies of slant-path attenuation due to rain

Approximately 40 h of data from the summer of 1976 were employed in a comparison of radar and radiometer estimates of slant-path attenuation due to rain. McGill Radar Weather Observatory is situated 20 km west of Montreal; the radiometers, separated by 18 km at two sites located about 90 km northwest of the radar, had fixed antennas pointed approximately southeast at an elevation of 18.5 deg. Values of radar reflectivity along the two radiometer paths were used to calculate the slant-path attenuation at 13 GHz as a function of time with a 1 min resolution for direct comparison with the radiometer measurements. It was found that the cumulative distribution of attenuation inferred by radar from each site could be made to agree satisfactorily with the radiometer distribution assuming that rain was present everywhere along the path with a Marshall-Palmer distribution and applying a 1 dB correction to the independently-determined radar calibration. This agreement, close to within a fraction of a decibel, gives confidence to the use of radar records in compiling attenuation statistics. An example is presented of a new application of such records, namely the assessment of rain-induced interference over adjacent earth-space paths.     

Prediction of slant path rain propagation statistics usingdual-polarized radar

The authors conducted a year-long experiment in which a dual-polarized S-band radar probed the volume surrounding two 11.45-GHz satellite downlink paths during rain. Accuracy was assessed by comparison to directly measured link attenuation with two 11-GHz beacon receivers 7.3-km apart at an 18.5° elevation angle, one colocated with the radar. Drop size distributions calculated from the radar horizontal reflectivity (Z_H) and differential reflectivity (ZDR) measurements were used to predict 11.45-GHz satellite beacon attenuations. The radar-predicted attenuations and those measured on the radio links agree, both on an event basis and in terms of annual cumulative distributions     

Attenuation of propagation through rain for an earth--Satellite path correlated with predicted values using radar

During the summer of 1974 and spring of 1975, measurements of attenuation of propagation through rain were made at Wallops Island, VA, using 13 and 18 GHz transmitters operating in the uplink mode toward the ATS-6 satellite. Simultaneously, rain reflectivity levels were measured along the earth-satellite path using a high resolution (0.4degbeamwidth)S-band radar having a scanning antenna. Four raingages and two disdrometers were also located in the vicinity of the transmitters. The radar and disdrometer data were used in a modeling program to predict attentuation levels which were subsequently compared to the directly measured fades over nearly simultaneous time intervals. Predicted attentuation levels were obtained for three drop size distributions; namely, those of Joss et al. for thunderstorm activity, Marshall-Palmer, and the average distribution measured in the vicinity of the transmitter (APL distribution). Comparisons between predicted and measured attenuation levels showed the APL dropsize distribution gave the smallest rms difference of 1.3 dB at 13 and 18 GHz although the rms difference corresponding to Marshall-Palmer was close to this value. Although the sample sizes were relatively small, the good agreement suggests the validity of using radar to model path attenuation to obtain attenuation statistics.     

Frequency dependence of effective path length in prediction of rain attenuation statistics

Theoretical and numerical results are presented which demonstrate that the effective path length commonly used in the prediction of rain attenuation statistics for earth-space paths is frequency dependent. Also presented is a method of translating effective path length measurements in frequency.     

Correcting C-band radar reflectivity and differential reflectivitydata for rain attenuation: a self-consistent method withconstraints

Quantitative use of C-band radar measurements of reflectivity (Z _h) and differential reflectivity (Z_dr) demands the use of accurate attenuation-correction procedures, especially in convective rain events. With the availability of differential phase measurements (Φ_dp) with a dual-polarized radar, it is now possible to improve and stabilize attenuation-correction schemes over earlier schemes which did not use Φ_dp. The recent introduction of constraint-based correction schemes using Φ_dp constitute an important advance. In this paper, a self-consistent, constraint-based algorithm is proposed and evaluated which extends the previous approaches in several important respects. Radar data collected by the C-POL radar during the South China Sea Monsoon Experiment (SCSMEX) are used to illustrate the correction scheme. The corrected radar data are then compared against disdrometer-based scattering simulations, the disdrometer data being acquired during SCSMEX. A new algorithm is used to retrieve the median volume diameter from the corrected Z_h, corrected Z_dr , and K_dp radar measurements which is relatively immune to the precise drop axis ratio versus drop diameter relation. Histograms of the radar-retrieved D₀ compared against D₀ from disdrometer data are in remarkable good agreement lending further validity to the proposed attenuation-correction scheme, as well as to confidence in the use of C-band radar for the remote measurement of rain microphysics     

Comparison of the synthetic storm technique with a conventional rain attenuation prediction model

It is confirmed that the synthetic storm method is in some way related to one year's existing attenuation data in Greece, but that also one of the standard models (in particular Lin's empirical) works as well and even better. Since agreement between prediction and observation has not been clear for the synthetic storm technique, an extension of the present work is now planned to include a longer data sample.     

Development of a neural network based algorithm for radar snowfallestimation

Using radar to measure snowfall accumulation has been a research topic in radar meteorology for decades. Traditionally, a parametric reflectivity-snowfall (Z-S) relationship is used to estimate ground snowfall amounts based on radar observations. However, the accuracy and reliability of Z-S relationship are limited by the wide variability of the Z-S relationship with snowfall type. In this paper, the authors introduce a neural network based approach to address the problem of snowfall estimation from radar by taking into account the vertical structure of precipitation. The motivation for using a multilayer feedforward neural network (MFNN), such as the radial-basis function (RBF) network, is the good universal function approximation capability of the network. The network is trained using vertical reflectivity profiles averaged over a 9-km² area as the input and ground snowfall amounts as the target output. Separate data, which are not part of the training data, are used to test the generalization performance of the RBF network after the training is done. Radar reflectivity data collected by the CSU-CHILL multiparameter radar and ground snowfall measurements recorded by snowgages located at the Stapleton International Airport (SIA), Stapleton, CO, and the Denver International Airport (DIA), Denver, CO, during the Winter and Icing and Storms Projects (WISP94) were used for this study. The snowfall estimates from the RBF network are shown to be better than those obtained from conventional Z-S algorithms. The neural network based approach provides an alternate method to the snowfall estimation problem     

Antenna beamwidth independence of measured rain attenuation on a 28-GHz Earth-space path

Rain attenuation measured at 28 GHz on an earth-space path is independent of antenna beamwidth for beamwidths as small as0.1degand for attenuations up to 30 dB. The measurements imply that angle-of-arrival fluctuations are less than0.02deg.     

Constrained sequences with embedded redundancy for error control

A method for constructing constrained sequences with embedded redundancy for error control is reported. These sequences are constructed such that the first stage of decoding can be performed with standard error control decoding techniques, avoiding the problem of error propagation with prior constrained-sequence decoding     

Cumulative slant path rain attenuation statistics associated with the Comstar beacon at 28.56 GHz for Wallops Island, VA

Cumulative slant path rain attenuation statistics at 28.56 GHz are given for the year period April 1, 1977 through March 31, 1978 for Wallops Island, VA. These results were arrived at using the direct measurements of a beacon signal emanating from the Comstar geosynchronous satellite. Yearly, monthly, and time-of-day fade statistics are presented and characterized. In addition, a 19.04-GHz yearly fade distribution, corresponding to a second Comstar beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain-rate results. Specifically, it is shown that the yearly attenuation and rain-rate distributions follow with good approximation lognormal variations for most fade and rain-rate levels, respectively. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. These months thus represented the "worst" and "best" months at all attenuation levels. The eight-hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 dB were approximately between 1600-2400, and 0400-1200 h (local time), respectively. In employing the predictive method for obtaining the 19.04-GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent on raindrop-size distribution, providing these frequencies are not widely separated (such as 28 and 19 GHz).     

Measurements of cloud contribution to rain millimeter wave attenuation by using a radar and radiometers

The measurement technique of cloud contribution to rain attenuation and the equipment consisted of the coherent pulse Doppler radar at wavelength λ=3.2 cm, the radiometers at λ=0.4; 0.8 and 1.35 cm and apparatus for signal recording and processing is described. The results of such measurements are given. The Doppler spectrum of the rain backscattered radar signal was used for determination of rain drop size distribution height profile then rain attenuation was calculated and cloud attenuation was determined as the difference between the total attenuation measured by using the radiometers and rain attenuation. The results of this work gave possibility to improve the known rain model of P.Misme for prediction of rain attenuation statistics for Earth-satellite links at millimeter wave.     

基于BP神经网络的雷达干扰效果评估

雷达干扰效果是衡量雷达干扰措施是否有效和雷达干扰设备性能优劣的重要指标,如何准确、客观、快捷地评估雷达干扰效果,对雷达干扰双方均具有重大的现实意义。本文主要研究一种了基于人工神经网络的雷达干扰效果评估的方法,并进行了举例说明。     

Comparison of a one- and a two-frequency technique for frequency scaling of rain attenuation statistics

The theory underlying Hogg's technique for the frequency scaling of rain attenuation statistics at two frequencies is presented, and the inherent approximations given. The technique is compared theoretically and numerically with a new method for scaling single frequency statistics recently proposed by the authors.     

基于神经网络法的焦平面器件非均匀性校正技术研究

首先分析了传统的非均匀性校正方法的缺点,指出自适应校正红外焦平面器件非均匀性的必要性。根据焦平面器件非均匀性噪声特性和算法研究的需要,介绍了非均匀性失真图像的产生方法。在上述工作的基础上,研究了基于神经的自适应非均匀性校正算法,探讨了最近４领域像素平均、最近４邻域像素灰度加权和８邻域像素灰度加权等三种情况。实验结果表明,８邻域灰度加权算法校正效果较好。     

基于独立变量的神经网络的最短路径计算

已知一个有向图，求解两点间的最短路径的决策变量满足基尔霍夫约束关系。决策变量对应神经网络的状态，可以分为独立的和非独立的两部分。非独立变量的解可由独立变量的解线性组合而得到，给出了求解独立变量神经网络方程。     

Development of a neural network based algorithm for rainfallestimation from radar observations

Rainfall estimation based on radar measurements has been an important topic in radar meteorology for more than four decades. This research problem has been addressed using two approaches, namely a) parametric estimates using reflectivity-rainfall relation (Z-R relation) or equations using multiparameter radar measurements such as reflectivity, differential reflectivity, and specific propagation phase, and b) relations obtained by matching probability distribution functions of radar based estimates and ground observations of rainfall. In this paper the authors introduce a neural network based approach to address this problem by taking into account the three-dimensional (3D) structure of precipitation. A three-layer perceptron neural network is developed for rainfall estimation from radar measurements. The neural network is trained using the radar measurements as the input and the ground raingage measurements as the target output. The neural network based estimates are evaluated using data collected during the Convection and Precipitation Electrification (CaPE) experiment conducted over central Florida in 1991. The results of the evaluation show that the neural network can be successfully applied to obtain rainfall estimates on the ground based on radar observations. The rainfall estimates obtained from neural network are shown to be better than those obtained from several existing techniques. The neural network based rainfall estimate offers an alternate approach to the rainfall estimation problem, and it can be implemented easily in operational weather radar systems