Table of Content

20 March 2017, Volume 46 Issue 3

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System Design and Key Technologies of the GF-3 Satellite

ZHANG Qingjun

2017, 46(3):  269-277.  doi:10.11947/j.AGCS.2017.20170049

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GF-3 satellite, the first C band and multi-polarization SAR satellite in China, achieves breakthroughs in a number of core and key technologies. The satellite technology abides by the principle of “Demand Pulls, Technology Pushes”, forming a series of innovation point, and reaching or surpassing international level in main technical specification.

Precision Analysis of GGOS Tropospheric Delay Product and Its Application in PPP

YAO Yibin, XU Xingyu, HU Yufeng

2017, 46(3):  278-287.  doi:10.11947/j.AGCS.2017.20160383

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The tropospheric delay is the main error source in satellite navigation, for which GNSS wide area augmentation needs ZTD product of high accuracy to correct error. The tropospheric delay can be simultaneously estimated by GNSS, and be also obtained from numerical meteorological forecast model based on multi-sources data. The global zenith tropospheric delay product published by IGS is resolved by GNSS, whose accuracy reaches 4 mm and time resolution is 5 minutes. However, the uneven-distributed IGS sites makes the vast ocean area without data coverage. Based on ECMWF re-analysis material for 40 years, GGOS Atmosphere provides global total zenith tropospheric delay grid data since 1979,whose time resolution is 6 h and spatial resolution is 2.5°×2°. The GGOS-ZTD product was assessed compared with ZTD material of global IGS sites in 2015 and the systematic difference between GGOS-ZTD and IGS-ZTD was researched.Systematic difference coefficients in every site (proportional error a and fixed error b) were estimated by linear fitting and then spherical harmonic expansion with a and b was made to build spherical harmonic expansion model for systematic difference coefficients (a and b).Finally the application effect of the GGOS Atmosphere ZTD product was analyzed with systematic difference eliminated in satellite navigation and positioning in IGS and CMONOC sites. The results prove that: there are systematic difference between GGOS-ZTD and IGS-ZTD. The mean bias is -0.54 cm and mean RMS of discrepancy is 1.31 cm, which is accurate enough to satisfy the ZTD correction needs of vast GNSS real-time navigation positioning users. The GGOS-ZTD product with its systematic difference corrected is used in the precise point positioning experiment in ALBH、DEAR、ISPA、PALM、ADIS、YNMH、WUHN sites. The result showed that the speed of convergence effectively is obviously advanced, especially in U direction(10.58%、31.68%、15.96%、43.89%、51.46%、14.69%、18.40% respectively).

Wuhan University Deep-space Orbit Determination and Gravity Recovery System(WUDOGS) and Its Application Analysis

YE Mao, LI Fei, YAN Jianguo, HAO Weifeng, YANG Xuan, JIN Weitong, QU Chunkai

2017, 46(3):  288-296.  doi:10.11947/j.AGCS.2017.20160525

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WUDOGS(Wuhan University deep-space orbit determination and gravity recovery system) is a software system designed for deep spacecraft precise orbit determination and planetary gravity recovery, developed independently at Wuhan University. WUDOGS now has the function for Lunar and Mars spacecraft precision orbit determination. Its design pattern and main function are briefly introduced. The cross verification test(CVT) between WUDOGS and state of the art planetary precise orbit determination software GEODYN-Ⅱ are elaborated. The results show that:①for orbit propagation, with all the same forces and other configuration, the predicted orbit difference in R,T,N directions are less than 0.3 mm for one month arc, 5×10^-3 mm for 2 days arc, compared with GEODYN-Ⅱ;②the difference RMS of computed values of observables for two-way range and two-way range rate is at levels of 0.06 mm and 0.002 mm/s respectively;③for Chinese Chang'E-1 POD, the reconstructed orbit difference between WUDOGS and GEODYN-Ⅱ is at 2 cm level, for ESA MEX POD, the reconstructed orbit difference between WUDOGS and ESA is at 25 m level. Current developing situation of WUDOGS and comparison with international research level show that WUDOGS has a good application prospect, which will be important for meeting the demand of Chinese future planetary exploration and the development of deep space spacecraft POD software.

GEO NAV/CNAV-type Broadcast Ephemeris Fitting without Rotation of Inclination

DU Lan, LIU Zejun, ZHOU Peiyuan, FANG Shanchuan, LIU Li, MA Gaofeng

2017, 46(3):  297-306.  doi:10.11947/j.AGCS.2017.20160393

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The GPS-type broadcast ephemerides are currently used by BDS constellation. However, a 5°-rotation added on the original orbital inclination is needed in the GEOs ephemeris parameters fitting algorithm as well as in the user satellite position computation because of the singularity due to small inclination. Besides, the phenomena of exceeding the given boundary happen occasionally for some ephemeris parameters of GEOs. In order to unify the user ephemerides algorithm for the hybrid constellation, a two-step GEO broadcast ephemerides fitting algorithm was analyzed based on the first class nonsingular orbital elements. After the investigation on the reason for the variations of some ephemeris parameters out of limited range, a reduced fitting parameter set was adopted by giving the underlying one or two parameters with fixed values. Fit simulations for 5 GEOs during both eclipsing and non-eclipsing periods show that the two-step fitting algorithm has considerable robustness to ensure the success rate and fitting accuracy. The mean fitting user range error of GEOs with 2 h for NAV and 3 h data set for CNAV are better than 3 mm. For specific fit arcs with the boundary-exceeding problem, it can be fully avoided by using the fitting algorithm with a reduced fitting parameter set. However, the fitting URE will increase to 2 cm.

Total Least Squares Method Inversion for Coseismic Slip Distribution

WANG Leyang, LI Haiyan, WEN Yangmao, XU Caijun

2017, 46(3):  307-315.  doi:10.11947/j.AGCS.2017.20160212

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The coefficient matrix (Green matrix) is composed of surface point offset caused by unit slip of sub-fault patches. The elements of the coefficient matrix are related to the location, geometry of rupture surface, assumption of model and other factors. In this paper, we attempted to consider the Green'function matrix (coefficient matrix) errors in order to compensate for the effects of above-mentioned factors to some extent. The total least squares (TLS) method, which both errors of coefficient matrix and observation vector are considered, is proposed for fault slip inversion. So we dealt with the errors in both of coefficient matrix and observation at same time. And by analysis of the relations between observation vector and coefficient matrix elements, we obtained the covariance matrix of coefficient matrix elements and observation vector. Considering the coefficient matrix was ill-posed, we used the second-order Laplace smoothing to constrain the slip parameters each other, then we used the regularized total least squares method to estimate slip distribution. the total least squares (TLS)slip inversion method was applied to simulate oblique fault event and Mw6.3 earthquake occurred in L'Aquila (central Italy) on April 6, 2009, respectively. To L'Aquila earthquake, the results by total least squares method indicate that the inverted geodetic moment is 3.63×10¹⁸ N·m (Mw6.34). With a maximum slip of 0.95 m, and a average rake of -96.4°, the main slip occurred at depth of 4 km-15 km. The difference of slip distribution solutions between total least squares and least squares method is less than 10^-4 order.

Using High Spatial-resolution Regional Atmospheric Data for Computation of GRACE Atmospheric De-aliasing Models

YOU Wei

2017, 46(3):  316-324.  doi:10.11947/j.AGCS.2017.20160554

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Focusing on the problem that the spatial horizontal resolution of ECMWFop or ERA-Interim atmospheric data is not enough for the computation of atmospheric de-aliasing models in GRACE gravity recovery, a method of suitable fusion of local high spatial horizontal resolution atmospheric data and global atmospheric data is proposed. A set of improved atmospheric de-aliasing models is calculated by using the atmospheric data from the local area of Europe and ERA-Interim. The quality of the modified atmospheric de-aliasing models is analyzed from the aspects of spectral domain, spatial domain and satellite-to-satellite range-rate residuals. The results show that the improvement ratio of the improved atmospheric de-aliasing models is 1.87% compared with the conventional atmospheric de-aliasing models, which is comparable to that of the AOD1B RL05 relative to the RL04. It is verified that the atmospheric data with high spatial horizontal resolution could improve the quality of atmospheric de-aliasing models. So it provides a new approach to improve the ability to extract specific mass variation signal in local area using GRACE data.

Analysis of BDS+GPS Relative Positioning Dilution of Precision

YAN Li, LI Meng

2017, 46(3):  325-331.  doi:10.11947/j.AGCS.2017.20160227

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This paper defines new atmosphere DOP styles that are TrDOP and IDOP in GNSS relative positioning. From DOP standpoint, it is firstly demonstrated that the efficiency of BDS/GPS fusion precise relative positioning are improved. With the joining of BDS, the values of ADOP, RGDOP and TrDOP decrease efficiently that can be achieved by increasing observing sessions. Moreover, by analyzing TrDOP and IDOP values, it indicates that BDS/GPS fusion is favorable to estimate the tropospheric parameter and has a small impact on estimating ionospheric parameters.

Analysis of Location Accuracy without Ground Control Points of Optical Satellite Imagery

WANG Renxiang, WANG Jianrong, HU Xin

2017, 46(3):  332-337.  doi:10.11947/j.AGCS.2017.20160650

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There are two photography modes in optical satellite photogrammetry, including global continuous coverage and local area coverage, and each photography mode has its own characteristics about application and way to realize location accuracy without ground control points (GCPs). In this paper, the location accuracy without GCPs of typical satellite is introduced, and the key technical in bundle adjustment is described. Finally, the simulation experments are performed about location accuracy without GCPs using forward intersection and bundle adjustment. The results are shown: the attitude accuracy of exterior orientation elements is key factor to affect the location accuracy without GCPs, while the image resolution has little effect. When attitude accuracy of exterior orientation elements exceeds 0.5, the location accuracy without GCPs using bundle adjustment with 5 m resolution is better than it using forward intersection with 0.5 m resolution.

Automatic Texture Optimization for 3D Urban Reconstruction

LI Ming, ZHANG Weilong, FAN Dingyuan

2017, 46(3):  338-345.  doi:10.11947/j.AGCS.2017.20160467

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In order to solve the problem of texture optimization in 3D city reconstruction by using multi-lens oblique images, the paper presents a method of seamless texture model reconstruction. At first, it corrects the radiation information of images by camera response functions and image dark channel. Then, according to the corresponding relevance between terrain triangular mesh surface model to image, implements occlusion detection by sparse triangulation method, and establishes the triangles' texture list of visible. Finally, combines with triangles' topology relationship in 3D triangular mesh surface model and means and variances of image, constructs a graph-cuts-based texture optimization algorithm under the framework of MRF(Markov random filed), to solve the discrete label problem of texture optimization selection and clustering, ensures the consistency of the adjacent triangles in texture mapping, achieves the seamless texture reconstruction of city. The experimental results verify the validity and superiority of our proposed method.

A Matching Method of Space-borne Laser Altimeter Big Footprint Waveform and Terrain Based on Cross Cumulative Residual Entropy

YUE Chunyu, XING Kun, BAO Yunfei, ZHOU Nan, HE Hongyan

2017, 46(3):  346-352.  doi:10.11947/j.AGCS.2017.20160255

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A matching method of space-borne laser altimeter big footprint waveform and terrain based on cross cumulative residual entropy(CCRE) is proposed. Firstly, the waveform data and digital surface model(DSM) data are projected to the statistics domain, according to the terrain structure information of the waveform, where statistics signal vectors of the two data are in the same dimension. Then, the waveform data and DSM image are matched in the statistics domain with CCRE. Experiments show that the algorithm proposed is effective in waveform and terrain matching, and the matching accuracy is within 1 pixel.

Spatial Downscaling Research of Satellite Land Surface Temperature Based on Spectral Normalization Index

LI Xiaojun, XIN Xiaozhou, JIANG Tao, ZHANG Hailong

2017, 46(3):  353-361.  doi:10.11947/j.AGCS.2017.20160196

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Aiming at the problem that the spatial and temporal resolution of land surface temperature (LST) have the contradiction with each other, a new downscaling model was put forward, based on the TsHARP(an algorithm for sharpening thermal imagery) downscaling method, this research makes improvements by selecting the better correlation of spectral index(normalized difference vegetation index, NDVI; normalized difference build-up index, NDBI; modified normalized difference water index, MNDWI; enhanced bare soil index, EBSI) with LST, i.e., replaces the original NDVI with new spectral index according to the different surface land-cover types, to assess the accuracy of each downscaling method based on qualitative and quantitative analysis with synchronous Landsat 8 TIRS LST data. The results show that both models could effectively enhance the spatial resolution while simultaneously preserving the characteristics and spatial distribution of the original 1 km MODIS LST image, and also eliminate the “mosaic” effect in the original 1 km image, both models were proved to be effective and applicable in our study area; global scale analysis shows that the new model (RMSE:1.635℃) is better than the TsHARP method (RMSE:2.736℃) in terms of the spatial variability and accuracy of the results; the different land-cover types of downscaling statistical analysis shows that the TsHARP method has poor downscaling results in the low vegetation coverage area, especially for the bare land and building-up area(|MBE|>3℃), the new model has obvious advantages in the description of the low vegetation coverage area. Seasonal analysis shows that the downscaling results of two models in summer and autumn are superior to those in spring and winter, the new model downscaling results are better than the TsHARP method in the four seasons, in which the spring and winter downscaling improvement is better than summer and autumn.

An Improved Contextual Classification Method of Point Cloud

HE Elong, WANG Hongping, CHEN Qi, LIU Xiuguo

2017, 46(3):  362-370.  doi:10.11947/j.AGCS.2017.20160096

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To address the lacking of effectively utilization of nonlocal spatial context information on complex scene when classifying point cloud, an improved contextual classification method is proposed for point cloud with linear distribution and uneven density. Firstly, the local point cloud features and interaction spatial context were estimated based on the curvature based adaptive neighborhoods. Then, the supervoxel based distribution spatial context was extracted from point cloud. Finally, the point cloud classification was achieved automatically via higher-order conditional random field, which overcomes the limitation of local feature based point cloud classification. The experimental results show that the proposed method is able to improve the accuracy of point cloud classification effectively.

A Finite State Machine Aided Pedestrian Navigation State Matching Algorithm

FANG Zhixiang, LUO Hao, LI Ling

2017, 46(3):  371-380.  doi:10.11947/j.AGCS.2017.20160530

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The automatic identification of pedestrian's navigation state is a difficult problem in pedestrian navigation research. It is important to improve the precision feedback and navigation performance of pedestrian navigation services, and few researches have been done in this field. This paper proposes a pedestrian navigation state matching algorithm based on finite state machine (FSM). The main idea of this method is to identify the pedestrian navigation state on the basis of recognizing pedestrian's actions. The pedestrian's action characteristics are recognized by using multiple sensor data collected by Google glass and mobile phone. Then, the pedestrian navigation states are divided into familiar, unfamiliar and lost state. The state transition model is established according to the FSM theory, and the pedestrian navigation state matching algorithm based on the model is designed. Finally, this algorithm is implemented, and experiments are conducted to validate its effectiveness. Experimental results show that the proposed algorithm can reach a good precision of recognizing the state transitions during pedestrian navigation process, and especially the accuracy of recognizing lost state achieves 90%.

Algorithms for Road Networks Matching Considering Scale Variation and Data Update

GUO Qingsheng, XIE Yuwu, LIU Jiping, WANG Lin, ZHOU Lin

2017, 46(3):  381-388.  doi:10.11947/j.AGCS.2017.20160364

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Road network matching is an important prerequisite for the change detection and data updating of spatial database, and the matching of road networks at different scales is very important. In this paper, the existing algorithms road networks matching are summarized and analyzed firstly, and according to the problems and difficulties in the road networks matching at different scales, an algorithm integrating multiple matching techniques was designed. Based on the characteristics of road networks at different scales, the method of evaluating the structure of spatial scene was improved. The limitations of the algorithm based on stroke matching were analyzed for road networks data at the different scales, and the algorithm named “partial stroke matching” was put forward. The experiments indicate that the algorithm given in this paper can be used in matching of road networks at different scales, the effect of matching is good, and the running efficiency is high as well.

The DEM Grid Aggregation Based on the Principal Component Transform Model and Its Uncertainty Analysis

HUANG Zechun, ZHANG Qianning, XU Zhu, HONG Andong, ZHANG Ruifang

2017, 46(3):  389-397.  doi:10.11947/j.AGCS.2017.20160104

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The object is to present a new DEM aggregation method which not only can ensure high precision of DEM, but also can maintain the terrain morphology better according to the characteristic of principal component analysis which can reveal the relationship between variables. First of all, the mathematical formula deduction and practical calculation procedures about the new DEM grid aggregation method are presented on the basis of principal component transformation model. The principal component aggregation method is applied to get the weights of DEM grid cells in the 3×3 filter window to rebuild new DEM. Then taking converting DEM with 30 m resolution into the DEM with 90 m resolution as an example, three new DEMs are rebuilt respectively using principal component aggregation, mean aggregation and bilinear resample aggregation.Based on the model, the uncertainty characteristic of the DEM rebuilt with three aggregation methods are analyzed from elevation deviation before and after grid aggregation, the spatial distribution and spatial autocorrelation, and the keeping level of the terrain feature. Finally, the quality of DEM rebuilt with principal component aggregation is evaluated with descriptive statistics, semi variance function and contour overlay method.Experimental analysis results show that the new method can maintain the terrain feature better under keeping the high precision of DEM compared with mean aggregation and bilinear resampling aggregation methods.

Study on the Noise Model of GPS Coordinates Time Series

HE Xiaoxing

2017, 46(3):  398-398.  doi:10.11947/j.AGCS.2017.20160549

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Research on Crawling and Consistency Processing of POIs from Deep Web

WANG YONG

2017, 46(3):  399-399.  doi:10.11947/j.AGCS.2017.20160610

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Sparse Manifold Learning for Hyperspectral Imagery

LUO Fulin

2017, 46(3):  400-400.  doi:10.11947/j.AGCS.2017.20160621

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Built-up Area Detection from High-resolution Stereo Imagery

PENG Feifei

2017, 46(3):  401-401.  doi:10.11947/j.AGCS.2017.20160508

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Real-time GIS Data Model Supporting Dynamic Data Management and Spatiotemporal Porcess Simulation

LI Xiaolong

2017, 46(3):  402-402.  doi:10.11947/j.AGCS.2017.20160557

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