MODIS水汽反演用于InSAR大气校正的理论研究

大气效应尤其是大气水汽的影响是InSAR干涉测量中主要的误差源和限制因素之一,因此高精度的InSAR应用迫切需要及时掌握大气水汽含量及其时空变化。本文深入分析了利用MODIS的水汽反演结果进行InSAR干涉测量大气校正的可行性,对MODIS近红外水汽反演结果与地基GPS水汽探测结果进行了比较和分析。同时根据GPS解算结果,利用实例讨论了基于地面气象参数的水汽延迟模拟的效果。     

The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction

For lack of sufficient observations, the definition of atmospheric moisture fields (including water vapor and clouds) remains a difficult problem whose solution is essential for improved weather forecasts. Moisture fields are under-observed in time and space, primarily because the distribution of water in the atmosphere is highly variable. Because water is important in weather and climate processes, a significant effort has been expended to develop new or improved remote sensing systems to mitigate this problem. One such system uses ground-based Global Positoning System (GPS) receivers to make accurate all-weather estimates of atmospheric refractivity at very low cost. This largely unanticipated application of GPS had led to a new and potentially significant upper-air observing system for meteorological agencies and researchers around the world (Wolfe & Gutman, 2000). The first and most mature use of GPS for this purpose is in the estimation of integrated (total column) precipitable water vapor above a fixed site (Duan et al., 1996, with improvements by Niell, 1996, and Fang et al., 1998). The techniques currently used by the National Oceanic and Atmospheric Administration's Forecast Systems Laboratory (NOAA/FSL) to collect, process, and distribute GPS water vapor observations are mature and almost ready for transition to operational use. NOAA/FSL has shown that GPS integrated water vapor data can be used effectively in objective (i. e., numerical weather prediction) and subjective weather forecasting. To understand the strengths and limitations of GPS for weather forecasting, it is essential to understant what types of information are currently available to forecasters and modelers, and how models use the data to describe the current and probable future state of the atmosphere. It is also important to understand the current trends in modern weather prediction to ensure that GPS observing system play a significant role in the future. ? 2001 John Wiley & Sons, Inc.     

Interpolating atmospheric water vapor delay by incorporating terrain elevation information

In radio signal-based observing systems, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR), the water vapor in the atmosphere will cause delays during the signal transmission. Such delays vary significantly with terrain elevation. In the case when atmospheric delays are to be eliminated from the measured raw signals, spatial interpolators may be needed. By taking advantage of available terrain elevation information during spatial interpolation process, the accuracy of the atmospheric delay mapping can be considerably improved. This paper first reviews three elevation-dependent water vapor interpolation models, i.e., the Best Linear Unbiased Estimator in combination with the water vapor Height Scaling Model (BLUE + HSM), the Best Linear Unbiased Estimator coupled with the Elevation-dependent Covariance Model (BLUE + ECM), and the Simple Kriging with varying local means based on the Baby semi-empirical model (SKlm + Baby for short). A revision to the SKlm + Baby model is then presented, where the Onn water vapor delay model is adopted to substitute the inaccurate Baby semi-empirical model (SKlm + Onn for short). Experiments with the zenith wet delays obtained through the GPS observations from the Southern California Integrated GPS Network (SCIGN) demonstrate that the SKlm + Onn model outperforms the other three. The RMS of SKlm + Onn is only 0.55 cm, while those of BLUE + HSM, BLUE + ECM and SKlm + Baby amount to 1.11, 1.49 and 0.77 cm, respectively. The proposed SKlm + Onn model therefore represents an improvement of 29–63% over the other known models.     

Improvement in PWV estimation from GPS due to the absolute calibration of antenna phase center variations

Climatology of column-integrated atmospheric water vapor over Spain has been carried out by means of three techniques: soundings, sun photometers and GPS receivers. Comparing data from stations equipped with more than one of these instruments, we found that a large discontinuity occurred on November 6, 2006, in the differences between the data series from GPS receivers and those from the other two techniques. Prior to that date, the GPS data indicate a wet bias of 2–3 mm for all stations when compared with sounding or photometer data, whereas after that date this bias practically reduces to zero. The root mean square error also decreases about half of its value. On November 6, 2006, the International GNSS Service adopted an absolute calibration model for the antennas of the GPS satellites and receivers instead of the relative one. This change is expected to be an improvement, increasing the accuracy of station position determination and consequently benefiting post-processing products such as zenith total delay from which the atmospheric water vapor content is calculated.     

GPS可降水汽含量在强降雨过程中的特征分析

针对水汽在大气中易于变化,高时空分辨率水汽资料的欠缺,造成强降雨短时临近的预报水平不高的问题,探讨分析了GPS水汽反演的精度。利用香港CORS数据,通过GAMIT软件解算获得各测站1 h大气可降水量时间序列,将其与探空数据获得的液态水含量（PWV）和实际降水量进行比较分析。结果表明,GPS／PWV与Radio／PWV在整体变化趋势上具有很好的一致性,其相关系数大于0.9;GPS／PWV与Radio／PWV精度相当,两者平均偏差小于1 mm,均方根误差小于3 mm;GPS反演的大气可降水量与实际降水量具有较好的对应关系,能够精确地监测到水汽变化的过程,可以用于水汽的监测和预报研究。      

Tight integration of GPS observations and persistent scatterer InSAR for detecting vertical ground motion in Hong Kong

A method for tightly integrating GPS observations and the persistent scatterer (PS) interferometric synthetic aperture radar (InSAR) is proposed to detect vertical ground motion in Hong Kong, China. The tropospheric zenith wet delays (ZWD) derived from GPS observations at sites in the SAR scenes are used first to model and correct for the tropospheric effects in the interferograms generated from the SAR images. The vertical motion rates (VMR) of the GPS sites determined based on the continuous GPS observations obtained at the sites are then used as constraints in the PS InSAR solutions to further enhance the quality of the solutions. Data from 12 continuous tracking GPS sites in Hong Kong and 8 ENVISAT ASAR images acquired during 2006–2007 are used to demonstrate the application of the proposed method. The results from the example show that the method is capable of detecting accurately the vertical ground motion.     

地基GPS技术遥感香港地区大气水汽含量

提出了分段多项式方法计算大气水汽含量,并结合无线电高空气象探测资料,分析并评估了地基ＧＰＳ遥感技术的精度。香港地区的可降水份计算结果表明,地基ＧＰＳ遥感技术的精度为１ ｍ ｍ ～２ ｍ ｍ     

InSAR生成DEM中WRF大气校正

利用星载重复轨道合成孔径雷达干涉测量InSAR技术获取数字高程模型(DEM),无法避免大气延迟效应的影响。InSAR大气校正的方法很多,但在DEM获取方面的大气校正研究却非常少见。本文研究星载重轨InSAR生产DEM时利用大气数值模式WRF(Weather Research and Forecasting model)得到的水汽结果进行大气校正的问题,重点讨论大气校正的策略,包括WRF模式设置和大气校正时机的选择,简要介绍了基于WRF运算结果的大气校正方法。利用Terra SAR-X数据进行实验,检验了所提出方法的有效性,证明了在干涉相位解缠前进行大气校正,比在相位解缠后进行的效果更好。将所提出方法应用于多基线、多波段InSAR干涉结果融合中,实验结果表明大气校正能够有效降低误差,对于相干性较高的地区效果更好。     

应用GPS观测量改正InSAR大气误差的空间插值比较

大气水汽的空间变化和时间分布是限制重复轨道干涉测量技术精度的主要因素之一。基于GPS数据,研究比较了改进后的基于地形的GPS扰动模型(GTTM)和基于地形的湍流混合模型(TDTM)。结果表明,改进的GTTM模型和TDTM模型都能有效地降低大气水汽对InSAR测量地面形变精度的影响,且TDTM插值效果更佳。     

利用GPS反解大气水汽含量

介绍地基和空基ＧＰＳ气象技术,简要讨论了ＧＰＳ遥感大气水汽含量对误差源。     

A case study of using Raman lidar measurements in high-accuracy GPS applications

This paper investigates the impact of rapid small-scale water vapor fluctuations on GPS height determination. Water vapor measurements from a Raman lidar are used for documenting the water vapor heterogeneities and correcting GPS signal propagation delays in clear sky conditions. We use data from four short observing sessions (6 h) during the VAPIC experiment (15 May–15 June 2004). The retrieval of wet delays from our Raman lidar is shown to agree well with radiosonde retrievals (bias and standard deviation (SD) were smaller than 1 and 2.8 mm, respectively) and microwave radiometers (from two different instruments, bias was 6.0/−6.6 mm and SD 1.3/3.8 mm). A standard GPS data analysis is shown to fail in accurately reproducing fast zenith wet delay (ZWD) variations. The ZWD estimates could be improved when mean post-fit phase residuals were removed. Several methodologies for integrating zenith lidar observations into the GPS data processing are also presented. The final method consists in using lidar wet delays for correcting a priori the GPS phase observations and estimating a scale factor for the lidar wet delays jointly with the GPS station position. The estimation of this scale factor allows correcting for a mis-calibration in the lidar data and provides in the same way an estimate of the Raman lidar instrument constant. The agreement of this constant with an independent determination using radiosonde data is at the level of 1–4%. The lidar wet delays were derived by ray-tracing from zenith pointing measurements: further improvement in GPS positioning is expected from slant path lidar measurements that would properly account for water vapor anisotropy.     

成都地区地基GPS观测网遥感大气可降水量的初步试验

利用首个成都地区地基GPS观测网2004年7～9月30s间隔的测量数据，通过Bernese GPS SoftwareV4．2解算出30min间隔的天顶总延迟量，结合自动气象站获得的气象资料计算出30min间隔的GPS遥感的大气可降水量。与根据气象探空站探测资料算出的可降水量进行统计对比，确定出本次GPS遥感可降水量试验的精度为3．09mm，两种可降水量时间序列呈现高度的一致性。同时验证了计算对流层加权平均温度的Bevis经验公式在成都地区的适用性。     

Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS

The revitalized Russian GLONASS system provides new potential for real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV) in order to support time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a method of real-time ZTD/PWV retrieval based on GLONASS and/or GPS observations. The performance of ZTD and PWV derived from GLONASS data using real-time precise point positioning (PPP) technique is carefully investigated and evaluated. The potential of combining GLONASS and GPS data for ZTD/PWV retrieving is assessed as well. The GLONASS and GPS observations of about half a year for 80 globally distributed stations from the IGS (International GNSS Service) network are processed. The results show that the real-time GLONASS ZTD series agree quite well with the GPS ZTD series in general: the RMS of ZTD differences is about 8 mm (about 1.2 mm in PWV). Furthermore, for an inter-technique validation, the real-time ZTD estimated from GLONASS-only, GPS-only, and the GPS/GLONASS combined solutions are compared with those derived from very long baseline interferometry (VLBI) at colocated GNSS/VLBI stations. The comparison shows that GLONASS can contribute to real-time meteorological applications, with almost the same accuracy as GPS. More accurate and reliable water vapor values, about 1.5–2.3 mm in PWV, can be achieved when GLONASS observations are combined with the GPS ones in the real-time PPP data processing. The comparison with radiosonde data further confirms the performance of GLONASS-derived real-time PWV and the benefit of adding GLONASS to stand-alone GPS processing.     

GPS反演大气综合水汽含量的影响因素分析

目前地基GPS遥感大气综合水汽含量的可行性已经被众多实验所验证,为进一步改善地基GPS遥感大气综合水汽含量的精度,本文对2004年6月哈尔滨GPS跟踪站的观测数据进行了解算,并结合探空资料计算的水汽结果对各项误差进行了分析。结果表明:广播星历不能用于高精度GPS水汽遥感;5cm的测站坐标误差将引起3mm的水汽误差,截止高度角的不同以及通用模型均会对水汽结果造成不同程度的影响。     

GPS与InSAR数据融合在矿山开采沉陷形变监测中的应用探讨

GPS与InSAR数据融合具有重要的研究意义,本文分析了传统测量方法在矿山开采沉陷形变监测中的不足,讨论了GPS与InSAR数据融合的技术优势及其在InSAR相位解缠算法、水汽模型和大气层延迟误差改正模型、时间域与空间域的融合模型和算法等方面研究内容,提出了GPS与InSAR数据融合的研究特点与具体方法,并给出了比较详细的研究方案。     

Quality assessment of GPS rapid static positioning with weighted ionospheric parameters in generalized least squares

Precise GPS positioning requires the processing of carrier-phase observations and fixing integer ambiguities. With increasing distance between receivers, ambiguity fixing becomes more difficult because ionospheric and tropospheric effects do not cancel sufficiently in double differencing. A popular procedure in static positioning is to increase the length of the observing session and/or to apply atmospheric (ionospheric) models and corrections. We investigate the methodology for GPS rapid static positioning that requires just a few minutes of dual-frequency GPS observations for medium-length baselines. Ionospheric corrections are not required, but the ionospheric delays are treated as pseudo-observations having a priori values and respective weights. The tropospheric delays are reduced by using well-established troposphere models, and satellite orbital and clock errors are eliminated by using IGS rapid products. Several numerical tests based on actual GPS data are presented. It is shown that the proposed methodology is suitable for rapid static positioning within 50–70 km from the closest reference network station and that centimeter-level precision in positioning is feasible when using just 1 min of dual-frequency GPS data.     

Experiment on driving precipitable water vapor from ground-based GPS network in Chengdu Plain

The estimates of total zenith delay are derived using Bernese GPS Software V4. 2 based on GPS data every 30 s from the first measurement experiment of a ground-based GPS network in Chengdu Plain of Southwest China during the period from July to September 2004. Then the estimates of 0.5 hourly precipitable water vapor (PWV) derived from global positioning system (GPS) are obtained using meteorological data from automatic weather stations (AWS). The comparison of PWV derived from GPS and those from radiosonde observations is given for the Chengdu station, with RMS (root mean square) differences of 3.09m. The consistency of precipitable water vapor derived from GPS to those from radiosonde is good. It is concluded that Bevis’ empirical formula for estimating the weighted atmospheric mean temperature can be applicable in Chengdu area because the relationship of GPS PWV with Bevis’ formula and GPS PWV with radiosonde method shows a high correlation. The result of this GPS measurement experiment is helpful both for accumulating the study of precipitable water vapor derived from GPS in Chengdu areas located at the eastern side of the Tibetan Plateau and for studying spatial-temporal variations of regional atmospheric water vapor through many disciplines cooperatively.     

Tropospheric corrections to SAR interferometry from GPS observations

Interferometric synthetic aperture radar (InSAR) techniques have been recognized as an ideal tool for many ground deformation monitoring applications. However, the spatially and temporally variable delay of the radar signal propagating through the atmosphere is a major limitation to accuracy. The dominant factor to be considered is the tropospheric heterogeneity, which can lead to misinterpretation of InSAR results. In this paper, a between-site (BS) and between-epoch (BE) double-differencing algorithm for the generation of tropospheric corrections to InSAR results based on GPS observations is tested. In order to correct the radar results on a pixel-by-pixel basis, the GPS-derived corrections have to be interpolated. Using experimental data it has been found that the inverse distance weighted and kriging interpolation methods are more suitable than the spline interpolation method. Differential corrections as large as several centimeters may have to be applied in order to ensure sub-centimeter accuracy for the InSAR result. The algorithm and procedures described in this paper could easily be implemented in a continuous GPS network data center. The interpolated image of BS, single-differenced tropospheric delays can be derived as a routine product to assist radar interferometry.     

An improvement to ionospheric delay correction for single-frequency GPS users – the APR-I scheme

 For the commonly used GPS wide-area augmentation systems (WAAS) with a grid ionospheric model, the efficient modelling of ionospheric delays in real time, for single-frequency GPS users, is still a crucial issue which needs further research. This is particularly necessary when differential ionospheric delay corrections cannot be broadcast, when users cannot receive them, or when there are ionospheric anomalies. Ionospheric delays have a severe effect on navigation performance of single-frequency receivers. A new scheme is proposed which can efficiently address the above problems. The robust recurrence technique is based on the efficient combination of single-frequency GPS observations by users and the high-precision differential ionospheric delay corrections from WAAS. Its effectiveness is verified with examples. Received: 24 December 1999 / Accepted 21 February 2001     

地基GPS遥感大气水汽含量的误差分析

讨论并分析了利用地基ＧＰＳ遥感大气水汽含量时的误差源及其数值评估。其误差来自三个方面：一是计算ＧＰＳ讯号传输时间中湿延迟的误差;二是将该湿延迟转换为大气水汽含量公式中测定转换因子的误差;三是转换模型的误差。