摘要
近些年来,我国灾害频发,地震、地面沉降、滑坡、泥石流等,严重威胁到人民群众的生命财产安全。为保证可持续发展战略的顺利实施和建立以人为本的和谐社会,我国持续在全国范围内实施了地质灾害大调查以及防治项目。InSAR作为一种大范围内灾害监测的有效手段在地质灾害调查中发挥了重要的作用。然而由于大气水汽的存在,当雷达信号穿过大气层时,会导致信号传播路径的延迟和以及传播速度的减缓,使得我们的观测相位具有一个附加的延迟量,即大气延迟相位,从而影响了InSAR的监测精度,限制了其在滑坡、危岩体等高精度形变监测要求灾害中的应用。尤其是满足高速经济发展需要的地铁、高铁建设,更是迫切需要获取大范围内地铁、高铁沿线高精度的地表形变信息,因此研究如何改正InSAR中大气延迟误差提高大范围InSAR的监测精度,不仅对拓展InSAR应用范围和监测能力具有重要意义,而且也是积极发挥InSAR在地质灾害大调查及经济建设中重要作用所面临的一个急需解决的问题!
本文针对InSAR中大气延迟问题,从两方面展开了大气延迟改正理论和方法的研究,即基于外部数据MODIS、GPS、ECMWF等的大气延迟改正的理论方法研究,和基于SAR影像自身的大气延迟改正方法研究。详细讨论了各种数据改正SAR影像中大气延迟的基本理论和方法,并提出了相关新算法,通过对各类方法的实例研究得到了一些有益结论。
通过研究,本文取得了以下主要成果及创新:
1)针对MODIS水汽反演算法受各种反射误差的影响而使得MODIS反演水汽值存在误差的问题,本文利用西安地区的GPS和MODIS晴空数据,研究了MODIS水汽产品的误差纠正模型,同时还研究建立了湿延迟ZWD与可降水汽值PWV之间的转换关系与系数。研究指出由MODIS获取的水汽值比GPS水汽值要大,两者间约存在1.127倍的关系且与高程无关;考虑了季节性变化的转换系数精度较高,针对西安地区值夏季采用6.0,冬季采用6.52较为合适。
2)研究了利用MODIS水汽改正InSAR中大气延迟相位的方法,针对云污染情况下的像素插值问题进行了讨论,通过不同情况的大气延迟改正实例,证明了MODIS纠正大气延迟的能力和程度,同时指出当大气状态变化较大时,用MODIS数据改正甚至会引入观测误差,因此利用MODIS数据改正D-InSAR结果须谨慎。
3)针对利用GPS改正InSAR中大气延迟相位中的空间插值问题,本文提出了顾及地形影响的GPS湿延迟插值算法和顾及地形因素的Kriging插值新算法(IKriging),研究表明,本文提出的两种插值新算法相比传统的Kriging和IDW插值方法,更能够反映地形对大气分布的影响,且更能够反映大气的细节信息。同时本文提出的IKriging方法,还可使用于多影响因素的插值应用。
4)ECMWF数据用于InSAR大气延迟改正面临其空间分辨率和时间分辨率过低的限制,本文针对其空间分辨率较低的缺点,研究建立了基于边界层伸缩模型SBLM的ECMWF空间加密的模型算法,推导了相关公式,并编制了相应的软件。利用欧洲大陆夏季连续两个月5600多个采样点的GPS水汽和地表温度、气压数据对模型进行验证,结果表明SBLM计算得到的PWV、P和T与GPS PWV以及地面观测气压、温度之间相关系数分别高达0.94、0.99和0.95,模型精度分别为2.38mm、2.97hpa和2.42K。对SBLM特性研究表明,相对于纬度,高程变化的对模型精度影响更大。将SBLM模型应用于太原盆地两对条幅干涉相位的大气延迟改正,发现ECMWF可以改正结果中部分地形相关延迟相位和长波相位,纠正幅度分别达28%和43%。
5)针对无可用外部数据情况的大气延迟改正,本文提出了单幅差分干涉图中的大气纠正算法,并用Akaike信息准则研究了地形相关湿延迟的模型显著水平,指出相比于线性模型,指数函数模型更符合差分延迟相位与地形回归关系。为避免噪声对差分延迟相位与地形回归模型的影响,本文提出了分段中位数(SMM)特征点选取方法,简化并精化了回归模型。该方法用于实际数据的大气延迟纠正实验表明,改正效果明显,改正幅度达到70%以上。在没有任何外部数据辅助数据用于大气延迟相位改正时,该法为单幅干涉图的大气相位改正提供了思路。
6)首次研究和评价了InSAR时间序列分析方法中分离大气相位的可靠性及改正效果。研究表明InSAR时间序列分析方法分离出大气延迟相位与高程具有一定的相关性,符合大气延迟在空间上的分布特征。研究指出大气延迟改正前后,形变量最大改正幅度可达10mm,且对分离大气进行改正后的形变序列结果相对平滑。PS-InSAR和SBAS-InSAR大气延迟改正后的形变结果具有较高的一致性,两种结果的平均不符值在5mm以内。总体而言,基于多幅SAR影像长时间序列分析方法大气延迟相位改正前后的形变趋势基本一致,说明InSAR时间序列分析方法对大气延迟相位具有很好的抑制作用。
In recent years, geological disasters frequently occurred in our country, such asearthquake, ground subsidence, landslides, debris flows and so on, which have caused aserious threats to people's life and property security. In order to ensure the smoothimplementation of the sustainable development strategy and establish people-orientedharmonious society, a series of geological disaster investigation and prevention projectshave been carried out in our country. As an effective tool in a wide range of geologicaldisaster survey and monitoring, InSAR plays an important role. However, due to theexistence of water vapor, the radar signal will get propagation path delay and propagationspeed slow down when it through the atmosphere. those will lead an additional delay valuesin our observation phase, i.e. atmospheric delay phase, which affects the accuracy of theInSAR technology and limits its application in the landslide, dangerous rock massdeformation monitoring and so on. Especially with the subway and high-speed railconstruction meeting the rapid economic development needs, it is an urgent need to acquirea large range of high precision surface deformation information around subway andhigh-speed rail line. So study on how to correct the atmospheric delay error and improve thelarge-scale InSAR monitoring accuracy has great significance not only to expand InSARapplication fileds and monitoring ability, but also to geological hazard survey and economicconstruction.
For atmospheric delay error, two kinds of the atmospheric delay correction methodshave been studied in this paper, namely based on SAR image themself methed and based onexternal data method, such as using MODIS, GPS, ECMWF data. The principle and methodof two kinds of the atmospheric delay correction methods have been described in n detail.and some new algorithms have been recommended. Some useful conclusions have beenobtained basing on the case study of all kinds of methods.
Through the study, this paper made the following main achievements and innovation:
1) For the problem that the MODIS water vapor retrieval algorithm is affected byvarious reflection errors, the MODIS water vapor error correction model has been studiedby using GPS and cloud free MODIS data cover xian area. The conversion coefficient between zenith wet delay and precipitable water vapor value has been studied. The studiesshow that MODIS water vapor value larger than GPS water vapor value about1.127times,which there is no relation with the elevation. The conversion coefficient considering theseasonal changes has a high precision. For Xi'an area the conversion coefficient is6.0insummer and6.52in winter.
2) The atmospheric delay correction method by using MODIS water vapor has beenstudied. The interpolation problem for the cloud of pollution pixels are discussed, and theatmospheric delay correction ability and extend have been proved by the correctionexamples. At the same time, this paper points out that under the conditions of atmospherechanges greatly, using MODIS data to correct even will introduce observation error, sousing MODIS image for correction of D-InSAR results must be cautious.
3) For the problem of space interpolation by using GPS to correct atmospheric delay,GPS wet delay interpolation algorithm considering topographic effects and new algorithmKriging interpolation lgorithm considering terrain factors are proposed. Studies show thattwo kinds of interpolation methods proposed in this paper can reflect the topography effecton atmospheric distribution and detail information better than that of the traditional Kriginginterpolation method and IDW. At the same time, the proposed IKriging method can also beused for multiple factors influencing interpolation.
4) For atmospheric delay correction by using ECMWF data, low spatial resolution andtime resolution are two important limited factors. For the disadvantage of the ECMWF datawith lower spatial resolution, the strected boundary layer model (SBLM) has been studied andcarried out, and the corresponding software is compiled. When they are compared to morethan5600sampling points GPS and surface temperature, pressure data for two months insummer of Europe, the results showed that the correlation coefficients between the SBLMcalculated PWV, P and T and true values were as high as0.94,0.99and0.95, the precision ofthe model were2.38mm and2.97hpa and2.42K. Study on SBLM characteristics showedthat the precision of the model were more affected by elevation change than the latitude.When SBLM was used to correct two pairs tripe SAR interferograms atmospheric delaycorrection cover taiyuan basin, part of the terrain related delay phase and long wave phasewere corrected, and the correction of amplitude were up to28%and43%respectively.
5) When there is no available external data for the atmospheric delay correction, theatmospheric correction algorithm for single differential interferograms were presented. Thesignificant level of terrain correlation wet delay model were studied by Akaike informationcriterion, which shows that exponential model is more consistent with differential delayphase and topography regression relationship compared with linear model. In order to avoidthe effect of noise on the differential delay phase and topography regression model, theSection Median Method (SMM) is presented, which simplified and refined the regressionmodel. The method is used for the actual data of the atmospheric delay correction showsthat the correction effect is very obvious and up to70%. The method provides a train ofthought for single interferogram atmospheric delay phase correction when the absence ofany external data for atmospheric delay phase correction.
6) The reliability of the atmospheric phase separated from InSAR time series analysismethod and the correction effect are researched and evaluated for the first time in this paper.The study shows that there are certain relationship between the atmospheric phase separatedfrom InSAR time series analysis method and height, which is consistent with the spacedistribution feature atmospheric delay.The study shows that the maximum correction ratecan reach up to10mm before and after the atmospheric delay correction, and the resultsshow more smooth after the atmospheric correction than that befor. The results has highconsistency between PS-InSAR and SBAS-InSAR after the atmospheric delay correction,and the average discrepant values is within5mm. The deformation trend of the resultsbefore and after the atmospheric delay correction is basically the same. The methods ofInSAR time series analysishas a very good inhibitory effect on the atmospheric delay phase.
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