Multibeam radar altimetry: spaceborne feasibility

An analysis of the inherent height and spatial resolution of an off-nadir radar altimeter is presented. For the general case, mean-square height uncertainty is shown to be proportional to the cross-track beamwidth divided by the along-track beamwidth. Thus, the cross-track beamwidth should be minimized and the along-track beamwidth maximized, subject to resolution and other constraints. A pure multibeam system with a 50-km beam offset, an altitude of 800 km, a 13.5-GHz frequency, and a 4.5-m-diameter antenna is found to yield a height random error of less than 5 cm. For the same conditions, errors decrease with increasing frequency: however, rain attenuation becomes a factor     

Estimation of raindrop size distribution from spaceborne Radar observations

The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar uses surface reference method to estimate the attenuation encountered in the observation of radar reflectivity. The cumulative attenuation estimated from the surface reference method can be distributed along the radar range using a power law relation between the specific attenuation (k) and reflectivity factor (Z). A physical interpretation of the variability in the k-Z relation can be provided with the normalized drop size distributions. This paper describes an algorithm to estimate the drop size distribution (DSD) parameters from the measured attenuation and reflectivity values obtained from TRMM precipitation radar observations. Coincident data collected with ground polarimetric radar during the TRMM field campaigns is used to cross-validate the estimates of drop size distribution parameters obtained from the TRMM precipitation radar. The results of cross validation show fairly good agreement with the drop size distribution parameters retrieved from TRMM precipitation radar and the ground-radar-based estimates. The algorithm is subsequently used to generate monthly global maps of DSD. The global distribution of DSDs is critically important for development of retrieval algorithms used by the Global Precipitation Mission Radiometers.     

Analysis of cross-beam resolution effects in rainfall rate profileretrieval from a spaceborne radar

The performance (stability and accuracy) of a range profiling algorithm (kZS), using the measurement of surface echo as a constraint on total path integrated attenuation, for rainfall retrieval from a spaceborne radar was presented and discussed by C. Matzler (1987). Omitting other causes of errors previously examined, the present authors focus specifically on possible bias due to nonuniform beam filling effects. This problem is studied analytically to identify the physical origin of the biasing terms. In addition, bias in rainfall profile estimates is quantified through simulations of Ku-band spaceborne radar data processing, featuring the intercept of a raincell model by the downward looking radar beam     

Range adjustment for ground-based radar, derived with the spaceborne TRMM precipitation radar

We show how the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) can be used to monitor and adjust ground-based radar (GR) data, as a function of the distance from the radar site. Problems caused by the variability of precipitation and differences in sampling volume of the two instruments are reduced to a level that is achievable with, and acceptable for, the present analysis. Throughout the region under surveillance, TPR has poorer spatial resolution than GR. The sampling volume of the GR changes quite remarkably according to the range from the GR site: it increases with the square of the range. TPR, on the other hand, has similar sampling volumes in all the locations. The analysis is based on the average linear radar reflectivity, in circular rings around the GR site, /sub 2/spl pi//, as a function of the range from the GR site. The GR/TPR ratio varies, for the Cyprus radar, on average from 2 dB, at 10 km, to -8 dB at 100 km. The average departure at the average range is considered to be mainly caused by the calibration of the GR. The range dependence of the GR/TPR ratio is significant and similar, in all the investigated cases. This is interpreted to be caused by the increasing sampling volume of the GR with range, combined with nonhomogeneous beam filling, e.g., at longer ranges of GR, the lower part of the volume could be in rain, whereas the upper part of the same pulse could be filled with snow, or even be without an echo. After correcting the GR data by using the derived averaged relationship, a significantly better agreement between the GR and TPR is found in all the overpasses analyzed. The agreement between the results of the two instruments is better for both the percentage of echo areas and the rain amount within each area. It is also better for the agreement of the GR with the gauges. In the absence of TPR data, it will be useful to investigate to what extent long-term, climatological data can be used to substitute TPR data.     

Image simulation of geometric targets for spaceborne syntheticaperture radar

A technique of synthetic aperture radar (SAR) image simulation is proposed. The method is based upon embedding of simulated man-made targets in a real background taken among the scenes captured by a spaceborne SAR. Scenes observed at 30 and 3 cm wavelength are used and the target dimensions are large enough with respect to the wavelength in order to compute the radar cross section from high frequency approximation techniques. Once the simulated image of the target is computed, the embedding process is performed bearing in mind the problems involved with this particular process. Although the simulation possibilities are restricted due to the simplifying assumptions, the results are sufficiently realistic to allow for the study of the detectability of a particular man-made target in a SAR environment     

Precipitation retrieval from spaceborne microwave radiometers basedon maximum a a posteriori probability estimation

A retrieval technique for estimating rainfall rate and precipitating cloud parameters from spaceborne multifrequency microwave radiometers is described. The algorithm is based on the maximum a posteriori probability criterion (MAP) applied to a simulated data base of cloud structures and related upward brightness temperatures. The cloud data base is randomly generated by imposing the mean values, the variances, and the correlations among the hydrometeor contents at each layer of the cloud vertical structure, derived from the outputs of a time-dependent microphysical cloud model. The simulated upward brightness temperatures are computed by applying a plane-parallel radiative transfer scheme. Given a multifrequency brightness temperature measurement, the MAP criterion is used to select the most probable cloud structure within the cloud-radiation data base. The algorithm is computationally efficient and has been numerically tested and compared against other methods. Its potential to retrieve rainfall over land has been explored by means of Special Sensor Microwave/Imager measurements for a rainfall event over Central Italy. The comparison of estimated rain rates with available raingauge measurements is also shown     

Meteorological passive-active radar observations

The results of passive-active radar investigations of atmospheric objects, including determination of the microphysical characteristics of clouds and precipitation (cloud water content and precipitation intensity) and the characteristics of lightning activity in thunderstorm-hazardous cloudiness, are presented. The possibilities of both active and passive methods have been discussed. It is shown that their combined application makes it possible to acquire data on the cloud water content at different stages of their evolution and detect dangerous weather phenomena related to clouds (thunderstorms, hail, and showers). These data can be employed in supershort-term forecasts of such phenomena. The principles of constructing passive-active meteorological radar systems have been analyzed.     

一种新的星载SAR图像定位求解方法

目前对于无地面控制点的R-D构像方程的求解方法多为采用繁杂的坐标参数变换后进行解析处理.为使求解方法简化,首先将R-D构像方程中的星地距离矢量作为变元进行泰勒级数展开导出误差方程,然后利用最小二乘平差原理迭代求解目标点的位置信息.利用苏州地区ERS-2 SAR图像产品和该地区1:10万地形图对该方法进行了实验验证,结果表明该方法平面定位精度达到200m量级,可以满足无控制点条件下中分辨率星载SAR图像中目标像元定位的需求.     

A fast approximate imaging algorithm for spaceborne synthetic aperture radar

A fast algorithm of azimuth processing for spaceborne aperture radar (SAR), which is called SPECAN algorithm, is proposed. Compared with general frequency algorithms, SPECAN has advantages in computation, memory and structure. SPECAN algorithm is very important for surveying real time processing of spaceborne SAR. The structure and special problems for SPECAN algorithm used in spaceborne SAR are mainly engaged in this paper. Finally, raw data of SEASAT-A satellite is used to verify the feasibility of SPECAN algorithm.     

实际应用中星载SAR的相位修正

利用大气折射理论对实际应用中星载合成孔径雷达(SAR)的大气层路径延时和相位的修正进行了推导,给出了仿真数据,并总结了延时和相位修正的规律.     

Effects of signal decorrelation on pulse-compressed waveforms fornadir-looking spaceborne radar

Pulse-compressed waveforms for partially coherent radar return signals are formulated with an incoherent-scatter autocorrelation function, ρ(τ). Numerical calculations are made for a nadir-looking spaceborne radar with linear FM pulses, and effects of signal decorrelation on the compressed waveforms are qualitatively evaluated. The calculations indicate that the transmitted pulse width should be shorter than half the correlation time, defined as the time at which ρ(τ) decreases by 0.1, in order to keep signal decorrelation effects negligible     

改进的星载合成孔径雷达天线方向图综合方法

天线方向图综合在星载合成孔径雷达(SAR)中抑制模糊提高系统性能方面起着非常关键的作用[1].重新考虑了Sergio Barbarossa和Guido Levrini所提出来的天线方向图综合优化过程,将原方法所忽略的天线方向图与干扰功率分布的相互作用引入到优化过程当中,重新推导了一种迭代优化算法.改进后的方向图综合方法以提高信号强度与干扰信号强度的比值SIR(Signal-to-Interference Ratio)为目的,计算机仿真结果表明该方法在降低模糊度ASR(Ambiguity-to-Signal Ratio)方面较先前的结果有了明显提高.     

星载光子计数激光测距雷达的实时去噪方法

星载光子计数体制激光测距雷达系统具有高重频、高精度等显著优势,但也面临原始数据量大且噪声数据占比过高的问题。为适应星上数据通道的传输能力,需压缩原始数据量并保障信号光子的查全率,因此必须发展以硬件为主体的实时去噪算法。本文提出一种粗精结合的快速去噪算法,首先基于激光器发射脉宽、系统噪声率、目标特性以及接收光子事件的局部密度信息进行粗去噪,剔除部分噪声光子;再利用直方图统计,对保留的光子事件进行精去噪,确定信号光子区间及最终的信号光子及其时间信息。通过蒙特卡洛仿真和ICESat-2实测数据对算法进行验证,测试结果表明,本算法查全率大于94%、查准率大于93%、调和平均值大于94%,运行效率提高了10%。算法可以实现光子事件的快速实时去噪,为星上硬件实时去噪处理提供了理论基础。     

基于最小熵星载合成孔径雷达电离层效应校正

分析了电离层闪烁效应对低频段星载合成孔径雷达(Synthetic Aperture Radar,SAR)方位向分辨率的影响,并基于相位屏方法进行了仿真研究.结果表明,随着电离层闪烁强度的增强,方位向分辨率逐渐降低,当处于强闪烁条件下时,方位向分辨率严重降低,甚至无法成像.利用最小熵方法对加入电离层闪烁效应误差的一副相控阵L波段合成孔径雷达(Phased Array L-Band Synthetic Aperture Radar,PALSAR)图像进行了校正,仿真试验结果表明,最小熵方法可有效校正电离层闪烁效应造成的方位向分辨率恶化的影响,校正后图像方位向分辨率得到了很好的恢复,接近原始无误差图像方位向分辨率,图像质量明显提高.     

Perspectives for the future of spaceborne synthetic aperture radar for Earth observation

Future satellite SAR systems must be small, easy to handle, and cost effective. Starting from the status quo and from user requirements as well as trends, expected developments and perspectives for innovative SAR techniques, technologies and systems for the next two decades will be presented.     

多通道星载合成孔径雷达姿态误差影响分析与补偿

针对高分辨率条件下,多通道星载合成孔径雷达(Synthetic Aperture Radar,SAR)姿态控制误差对成像质量影响问题开展研究.首先建立多通道姿态控制误差数学模型,在此基础上推导了姿态控制误差与接收天线相位中心位置、控制误差角度以及天线下视角等参数的数学表达式,定量化地分析了该误差对成像质量的影响方式与影响大小,并提出一种高效精确的误差补偿方法.最后,计算机仿真实验验证了本补偿方法的正确性及有效性.     

Analysis of algorithms for the retrieval of rain-rate profiles froma spaceborne dual-wavelength radar

The ability to retrieve rain-rate profiles from a dual-wavelength spaceborne radar system operating at 13.6 and 35 GHz is analyzed. The fundamental problem of extracting either the attenuation and/or the reflectivity from the backscatter echo, which contains both contributions, is addressed. Three algorithms, the backscatter, the attenuation coefficient, and the dual-wavelength methods, are examined. These algorithms are tested using four rain-rate profiles derived from radar measurements. In particular, measured (true) values are compared with calculated (retrieved) rain rates applying the algorithms with superimposed uncertainties assuming a suggested spaceborne dual-wavelength radar system. Error values of rain rates are determined where these values reflect failure of the assumptions utilized in the derivation of the algorithms, rain backscatter noise, and instrument noise     

星载合成孔径雷达不同工作模式下的PRF优化选取研究

星载合成孔径雷达中,脉冲重复频率（PRF）是非常重要的参数。它的选择受到很多因素的影响,尤其是受到发射干扰、星下点回波、距离模糊以及方位模糊的影响,也正是受到这些因素的影响,导致在不同的工作模式下,PRF的选取有很大的差异。这里在研究常用的条带工作模式下PRF选取的基础上,讨论了聚束和滑动聚束模式下PRF选取的特殊性,给出了这两种工作模式下PRF选取的方法,并进行了仿真验证其有效性。     

联合星载毫米波雷达和激光雷达资料的云相态识别技术

依据星载偏振激光雷达云相态识别原理,借鉴星载毫米波雷达温度阈值云相态识别方法,利用支持向量机(SVM)构建了联合CloudSat和CALIPSO卫星资料的云相态识别模型并进行了实例反演验证.SVM方法训练和测试样本集采用了CloudSat的2B-GEOPROF-LIDAR云廓线数据、CALIPSO的2级1km云层数据以...     

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