Table of Content

20 May 2017, Volume 46 Issue 5

Previous Issue    Next Issue

A Pseudo-range and Phase Combined SBAS Differential Correction Model

CHEN Junping, YANG Sainan, ZHOU Jianhua, CAO Yueling, ZHANG Yize, GONG Xiuqiang, WANG Jungang

2017, 46(5):  537-546.  doi:10.11947/j.AGCS.2017.20160299

Asbtract ( )   HTML   PDF (3856KB) ( )  

References | Related Articles | Metrics

BeiDou Navigation Satellite System (BDS) integrates legacy PNT service and authorized SBAS service, where SBAS service provides differential corrections and integrity information for authorized users. Current BDS differential corrections include one-dimensional equivalent satellite clock and ionospheric grids corrections, which is derived based on CNMC-smoothed pseudo-range observations. To improve the performance of BDS SBAS service, an algorithm is developed to estimate the real-time satellite clock and orbit corrections. In the algorithm, phase smoothed pseudo-range observation is used to define absolute value, and epoch differenced phase observation is used to define epoch-wise variation of the satellite clock/orbit corrections. It is analyzed that the impact of data sampling rate and station number on the correction parameter estimation. Real-time data of the BDS tracking network in China is used to validate the new algorithm. Compared with the current system performance:① mean UDRE using the new algorithm is reduced by 27%,35% and 27% for GEO, IGSO and MEO satellites, ② mean positioning error using the new algorithm is reduced by 23%,32% and 52% in the North, East and Up components, respectively. Implementing the new algorithm, BDS SBAS service supports the user positioning requirement with accuracy better than 1 m.

The Preliminary Result and Analysis for BD Orbit Determination with Inter-satellite Link Data

SONG Xiaoyong, MAO Yue, FENG Laiping, JIA Xiaolin, JI Jianfeng

2017, 46(5):  547-553.  doi:10.11947/j.AGCS.2017.20160203

Asbtract ( )   HTML   PDF (3907KB) ( )  

References | Related Articles | Metrics

The experimental satellite of BD navigation system has assembled inter-satellite link (ISL) payloads and has obtained the real ISL observation data. The paper presents the preprocessing method of ISL and the POD method and result for Ka only observation and the combination Ka observation with L-band. It's showed that:the radial orbit error is less than 0.5 m with Ka only observation; the radial orbit error is less than 0.3 m with the observation by combining the Ka ISL with L-band data which has improved the orbit accuracy remarkably in contrast to L-band only data; the accuracy of calibrating device delay is better than 0.1 m。

Automatic Tie-point Extraction Based on Multiple-image Matching and Bundle Adjustment of Large Block of Oblique Aerial Images

ZHANG Li, AI Haibin, XU Biao, SUN Yushan, DONG Youqiang

2017, 46(5):  554-564.  doi:10.11947/j.AGCS.2017.20160571

Asbtract ( )   HTML   PDF (12757KB) ( )  

References | Related Articles | Metrics

Due to advantages such as ease of interpretation, completeness through mitigation of occluding areas, as well as system accessibility, the aerial oblique images have found their place in numerous civil applications. However, for these applications high quality orientation data are essential. A fully automatic tie-point extraction procedure is developed to precisely orient the large block of oblique aerial images, in which a refined ASIFT algorithm and a window-based multiple-viewing image matching (WMVM) method are combined. In this approach, the WMVM method is based on the concept of multi-image matching guided from object space and allows reconstruction of 3D objects by matching all available images simultaneously, and a square correlation window in the reference image can be correlated with windows of different size, shape and orientation in the search images.Then another key algorithms, i.e. the combined bundle adjustment method with gross-error detection & removal algorithm, which can be used for simultaneously orient the oblique and nearly-vertical images will be presented. Finally, through the experiments by using real oblique images over several test areas, the performance and accuracy of the proposed method is studied and presented.

GPS-supported Bundle Adjustment Method of UAV by Considering Exposure Delay

ZHANG Chunsen, ZHU Shihuan, ZANG Yufu, XIAO Xiongwu, XUE Wanchang

2017, 46(5):  565-572.  doi:10.11947/j.AGCS.2017.20160583

Asbtract ( )   HTML   PDF (1616KB) ( )  

References | Related Articles | Metrics

The existing GPS-supported bundle adjustment method does not take into account the influence of camera exposure delay error impact in UAV photogrammetry is inconsistent which leading to the actual adjustment results are worse than the theoretical results. The mechanism of exposure delay is studied. The impact of exposure delay on GPS-supported bundle adjustment is analyzed. And a GPS-supported bundle adjustment method by considering the exposure delay is proposed. The effectiveness of the proposed method is verified by a typical dataset of 142 images. The meaning of the proposed method is that it can achieve the better aero-triangulation accuracy than the traditional GPS-supported bundle adjustment method.

All-pixels Participated Image Matching Algorithm for Geometric Solution

YANG Ying, LIN Zongjian

2017, 46(5):  573-582.  doi:10.11947/j.AGCS.2017.20160368

Asbtract ( )   HTML   PDF (6619KB) ( )  

References | Related Articles | Metrics

The purpose of geometric matching is to extract the geometric transformation parameters between the corresponding images. It is widely used in photogrammetric mapping, deformation detection, and flying platform's posture analysis, etc. In this paper, a new image matching method which is different from the traditional features based image matching algorithm is proposed, it takes all the pixels of the corresponding images to participate the matching procedure and calculate the geometric parameters by least square criterion. The principle of the algorithm, including the gray corresponding equation, the information quantity inequation and procedure of least square solution are expressed. Particularly, the wavelet analysis for gray signal and calculating the information quantity by signal to noise ratio are discussed in detail. For verifying the theory and algorithm, a series of sequential images taking from a video camera mounted on a helicopter are selected for experiment. The results of two typical models according to the relative orientation elements model and parallax grid model are given, and the experimental results show that the proposed algorithm is feasible and effective. The comparison of APM with ordinary features based method by the information quantity inequation is given in the conclusion.

A Back Projection Algorithm for Linear Array Imageries Based on the Constraints of Object-space Relation

MO Delin, ZHANG Yongsheng, WANG Tao, YANG Guopeng, XIA Qin

2017, 46(5):  583-592.  doi:10.11947/j.AGCS.2017.20160622

Asbtract ( )   HTML   PDF (2186KB) ( )  

References | Related Articles | Metrics

Back projection is the key technology for rectification of linear array CCD imageries. On the basis of analyzing the imaging mode and characteristics of linear whiskbroom image, a back projection algorithm based on the constraints of object-space relation was proposed, aiming at the inefficiency of conventional image-based sequential or iterative search methods. The best scan-line of the adjacent point was used as a priori value, to estimate the number of the scan-lines between the adjacent point and the current point, thus locating the initial best scan-line. Then, a search window was constructed by the center of the initial best scan-line, and an accurate searching was implemented. At last, according to the orientation elements of the best scan-line, the coordinates back projection was carried out. The feasibility, accuracy and efficiency of the proposed method were verified by the experimental results of the airborne linear array whiskbroom simulated image data and the pushbroom real image data.

Robust Total Least Squares Estimation of Space Intersection Appropriate for Multi-images

LI Zhongmei, BIAN Shaofeng, QU Yong

2017, 46(5):  593-604.  doi:10.11947/j.AGCS.2017.20160081

Asbtract ( )   HTML   PDF (2445KB) ( )  

References | Related Articles | Metrics

In order to take full advantage of available observation resources, based on theory of space intersection with stereo images, by conducting weighted quadratic sum of spatial distance from the target point to multiple space lines as the objective function and carrying out its first as well as second derivatives, robust total least squares estimation of space intersection appropriate for multi-images was realized. Compared to stereopair, more observed information and theories of robust estimation were considered in the process of space intersection with multi-images, bringing about higher intersection accuracy and robustness. Finally, correctness and robustness of the method was verified though example analysis, which can enrich the space intersection theory in photogrammetry to some degree.

Changed Image Objects Extraction Algorithms Considering Texture Feature Contribution

WEI Dongsheng, ZHOU Xiaoguang

2017, 46(5):  605-613.  doi:10.11947/j.AGCS.2017.20160581

Asbtract ( )   HTML   PDF (6725KB) ( )  

References | Related Articles | Metrics

Remote sensing image change detection is an important part of global change research.The change detection methods based on two-temporal remote sensing images consist of drawbacks which affect the accuracy of change detection results, such as rigorous data requirements, inadequate adoption of multi-source remote sensing image data. At present, there are some existing classification vector dataset available for change detection in many regions, and some prior knowledge are included in the existing classification vector dataset, e.g., the position, shape, size and class. Making full use of the prior information is beneficial to improve the accuracy of change detection result. Extracting changed image objects is the key step in the change detection using the existing vector data and the latest remote sensing image,Therefore,a new change detection method based on texture feature contribution is proposed. The vector data is used to segment remote sensing image, the image objects can be extracted, and the texture feature value of image objects can be calculated. According to the principle of information gain, the feature contribution of texture feature parameters is defined, and it is used to select texture feature parameters for texture feature analysis. A similar coefficient of texture feature is defined and is used to extract changed image objects. The experimental results show that selecting texture feature parameters based on feature contribution can effectively improve the accuracy of extracting changed image object result.

Hyperspectral Image Denoising Based on Tensor Group Sparse Representation

WANG Zhongmei, YANG Xiaomei, GU Xingfa

2017, 46(5):  614-622.  doi:10.11947/j.AGCS.2017.20150403

Asbtract ( )   HTML   PDF (9404KB) ( )  

References | Related Articles | Metrics

A novel algorithm for hyperspectral image (HSI) denoising is proposed based on tensor group sparse representation. A HSI is considering as 3 order tensor. First, a HSI is divided into small tensor blocks. Second, similar blocks are gathered into clusters, and then a tensor group sparse representation model is constructed based on every cluster. Through exploiting HSI spectral correlation and nonlocal similarity over space, the model constrained tensor group sparse representation can be decomposed into a series of unconstrained low-rank tensor approximation problems, which can be solved using the tensor decomposition technique. The experiment results on the synthetic and real hyperspectral remote sensing images demonstrate the effectiveness of the proposed approach.

Cloud Removal in ZY-3 Remote Sensing Image Based on Atoms-reordered Dictionary Learning AO-DL

LU Wanyun, WANG Jizhou, CAO Meng

2017, 46(5):  623-630.  doi:10.11947/j.AGCS.2017.20160474

Asbtract ( )   HTML   PDF (5009KB) ( )  

References | Related Articles | Metrics

In this paper, a new cloud removal method in remote sensing images is adopted.Based on the theory of compressive sensing,this method combines K-SVD dictionary learning with the orthogonal matching pursuit(OMP) algorithm of sparse representation.At the same time, a specific sorting rule is added to the process of dictionary atoms training, so that each image dictionary has its own image properties while its atoms also have a similar arrangement order to reduce the interference between image differences.In this method,the good effect of reconstruction of the contaminated region by clouds and shadows in remote sensing images is achieved.To illustrate the performance of the proposed method,experiments on two sets of data of multitemporal ZY-3 images at the same area are discussed.

The Method of Extracting Spatial Distribution Characteristics of Buildings Combined with Feature Classification and Proximity Graph

GUO Qingsheng, WEI Zhiwei, WANG Yong, WANG Lin

2017, 46(5):  631-638.  doi:10.11947/j.AGCS.2017.20160374

Asbtract ( )   HTML   PDF (4843KB) ( )  

References | Related Articles | Metrics

Spatial distribution characteristics of building clusters should be recognized and detected in generalization of building clusters. Based on analysis of relevant research at home and abroad, four major measures(area of the convex hull, compactness, number of edges, orientation of the smallest minimum bounding rectangle) are summarized and put forward from the existing measures with the help of principal component analysis. According to these selected measures, the building classification are studied. When MST(minimum spanning tree) is used to partition the building clusters, factors such as rivers and roads are taken into consideration. Furthermore, a method detecting linear patterns in building clusters automatically is proposed by means of NNG(nearest neighborhood graph), MST, RNG(relative neighborhood graph) and GG(Gabriel graph). Then the influence factors and usability about the recognized results are analysed. Finally, a part of map from OSM (open street map) in Beijing is chosen as experimental data, classification and clustering of the buildings are realized, and the linear patterns in the sub-clusters are recognized.

Integrated Storage and Management of Vector and Raster Data Based on Oracle Database

WU Zheng, LI Chengming, WU Pengda, SHEN Jianming, SUN Wei

2017, 46(5):  639-648.  doi:10.11947/j.AGCS.2017.20160586

Asbtract ( )   HTML   PDF (1745KB) ( )  

References | Related Articles | Metrics

At present, there are many problems in the storage and management of multi-source heterogeneous spatial data, such as the difficulty of transferring, the lack of unified storage and the low efficiency. By combining relational database and spatial data engine technology, an approach for integrated storage and management of vector and raster data is proposed on the basis of Oracle in this paper. This approach establishes an integrated storage model on vector and raster data and optimizes the retrieval mechanism at first, then designs a framework for the seamless data transfer, finally realizes the unified storage and efficient management of multi-source heterogeneous data. By comparing experimental results with the international leading similar software ArcSDE, it is proved that the proposed approach has higher data transfer performance and better query retrieval efficiency.

An Extraction Method for Point Pattern Convergence under Voronoi Adjacency Relation

KANG Shun, LI Jiatian, WU Hao

2017, 46(5):  649-657.  doi:10.11947/j.AGCS.2017.20150506

Asbtract ( )   HTML   PDF (1661KB) ( )  

References | Related Articles | Metrics

Point pattern convergence exerts a fundamental way in quantifying similar spatial patterns, which plays an essential function in revealing geographical phenomena emergence, development and evolution. Nevertheless, the independence test for traditional unary point pattern was based on a given frequency or random distribution. Moreover, the local correlation analysis for binary point pattern was focused on single observation and the surroundings were measured by Euclidean distance. Hereto, the issues on correlation in clustering, comprehensive convergence quantization for the point pattern under multiple observations and topological adjacency and non-adjacency relations need to be addressed. In facets of adjacency clustering and local convergence values over the criteria of spatial pattern, an extraction method for point pattern convergence under Voronoi adjacency relation was proposed. Firstly, independent spatial point patterns were tessellated using a clustering algorithm based on the Voronoi Adjacency Correlation Table, abbr. VACT. Secondly, the Nearest Neighbor Index was calculated through the Voronoi Adjacency Index algorithm, VAI for short, and in combination with the hypothesis testing results including mean distance and variance, the comprehensive convergence hypothesis was quantified via Laplace smoothing. Thirdly, according to λ truncated matrix, the strong convergent point patterns were extracted under the support of Voronoi adjacency and non-adjacency relations. Last but not least, taking the resident point set of Tengchong Yunnan for example, through point pattern construction and comparison, convergence calculation and strong convergence extraction, this method was evaluated to be promising.

Multi-beam Bathymetry Data Processing Using Iterative Algorithm of Robust Least Squares Collocation

WANG Leyang, CHEN Hanqing

2017, 46(5):  658-665.  doi:10.11947/j.AGCS.2017.20160491

Asbtract ( )   HTML   PDF (3966KB) ( )  

References | Related Articles | Metrics

In the process of dealing with multi-beam bathymetry data by least squares collocation, the quadric curved mathematical model of trend term can not express accurately the whole variation trend of seafloor topography in general. Moreover, the covariance function estimated by general method is incapable of accurately expressing statistical characteristics with the multi-beam bathymetry data contains gross errors or outliers. So the iterative algorithm of robust least squares collocation is proposed in this paper. Firstly, the initial weight matrix of observations and the initial parameters of covariance function are both given in this method, then the trend term is fitted by polyhedral function and equivalent weights scheme is applied into robust estimation in this method. Finally, the robust parameters of covariance function and solutions of least squares collocation are iteratively calculated. The experimental results show that the method proposed in this paper can express well the whole variation trend of seafloor topography and overcome the effect of gross error or outlier in multi-beam bathymetry data to a certain extent. Compared with the conventional robust method, the proposed method in this paper more effectively probes the outliers in bathymetry data with the robust and better predicted results.

Study of Estimating Surface Soil Moisture Based on Radar and Hyperspectral Data

MA Jianwei

2017, 46(5):  666-666.  doi:10.11947/j.AGCS.2017.20160668

Asbtract ( )   HTML   PDF (681KB) ( )  

Related Articles | Metrics

The Technology of Geo-ontology Modeling Driven Object Classification for Remote Sensing Image

GU Haiyan

2017, 46(5):  667-667.  doi:10.11947/j.AGCS.2017.20170054

Asbtract ( )   HTML   PDF (681KB) ( )  

Related Articles | Metrics

Spatio-temporal Interpolation Methods for Heterogeneous Spatio-temporal Data

FAN Zide

2017, 46(5):  668-668.  doi:10.11947/j.AGCS.2017.20170003

Asbtract ( )   HTML   PDF (687KB) ( )  

Related Articles | Metrics

Study on the Relationship between Crust Movement, Gravity Variation and Regional Strong Earthquakes in Sichuan-Yunnan Region

JIANG Yongtao

2017, 46(5):  669-669.  doi:10.11947/j.AGCS.2017.20170007

Asbtract ( )   HTML   PDF (688KB) ( )  

Related Articles | Metrics

Research on the Theory and Methods of Multi-GNSS Relative Positioning with High Precision

XIAO Yugang

2017, 46(5):  670-670.  doi:10.11947/j.AGCS.2017.20170068

Asbtract ( )   HTML   PDF (701KB) ( )  

Related Articles | Metrics