Table of Content

20 November 2020, Volume 49 Issue 11

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Geodesy and Navigation

Orbit determination and clock estimation via two ionosphere-free combinations of observation from BDS triple-frequency data and its application

LI Jie, ZHANG Rongzhi, ZENG Guang, GONG Bing, WANG Chong, FANG Yanan, ZHU Jun, LI Junfeng, QIANG Wen

2020, 49(11):  1377-1387.  doi:10.11947/j.AGCS.2020.20190237

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The international GNSS monitoring and assessment system (iGMAS) and the multi-GNSS experiments (MGEX) receive BeiDou navigation signals on different frequencies. In this paper, orbit determination and clock estimation based on two ionosphere-free combinations of observation (B1/B3 and B1/B2) from BDS triple-frequency data is proposed. In this method, data of both networks from BeiDou 2nd generation (BDS-2), BeiDou 3rd generation test system (BDS-3e) and BeiDou 3rd generation global system (BDS-3g) can be processed uniformly in one program run, which can effectively improve data usage at one run, thereby improving parameter estimation accuracy. The GPS and BDS data of iGMAS and MGEX were collected for several days for testing. The results show that for the BDS-3e+BDS-2+GPS joint orbit determination, the orbit overlap RMS of the BDS MEO is 9.5 cm after using the triple-frequency two-combination method, which is 29% higher than the accuracy of traditional dual-frequency processing. The new method introduces a code bias parameter related to three frequencies of each involving BDS-2 satellite. The result shows values of the parameter are quite stable for continuous one-day solutions, which proves that the model is reliable. The new method is used for BDS-3g+BDS-3e+BDS-2+GPS joint orbit determination. The 6 BDS-3g MEO satellite orbit overlap RMS is 14.5 cm, and the clock error overlap RMS is 0.43 ns, which is equivalent to 15.1 cm and 0.49 ns of BDS-3e. The BDS precise point positioning (PPP) test was carried out. The results show that after adding the precise orbit and clock difference of the six MEOs of BDS-3g, the horizontal positioning accuracy of the station is 39.6 mm, and the zenith accuracy is 37.8 mm, which increases positioning accuracy by 11.1% than BDS-2 and BDS-3e satellites only.

The algorithm of integer ambiguity resolution with BDS triple-frequency between reference stations at single epoch

ZHU Huizhong, LEI Xiaoting, LI Jun, GAO Meng, XU Aigong

2020, 49(11):  1388-1398.  doi:10.11947/j.AGCS.2020.20200110

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The carrier phase integer ambiguity resolution between reference stations is very important in BDS network RTK. The algorithm of determining the BDS triple-frequency carrier phase ambiguity between reference stations at single-epoch is studied in this paper. Firstly, the linear relations of triple-frequency carrier phase ambiguity between the reference stations are deduced. Then the ambiguity candidates of B1 and B2 carrier phase are selected by ambiguity candidates of B1 carrier phase ambiguity and the linear relationship of dual-frequency carrier phase ambiguities, and the same as the ambiguity candidates of B1 and B3 carrier phase. The ambiguity candidates of triple-frequency carrier phase are controlled and fixed by the linear relationship between triple-frequency carrier phase ambiguities without errors. In order to reduce the influence of tropospheric delay on the constraint ability of linear relations between multi-frequency carrier phase ambiguities, the method of selecting a reference satellite with altitude and azimuth is used by the spatial correlation of atmospheric errors. The results of test indicate that the carrier phase integer ambiguities of triple-frequency between reference stations can be fixed at single-epoch, and the algorithm is simple and efficient.

Robust UKF algorithm with motion constraint in BDS navigation

YIN Xiao, CHAI Hongzhou, XIANG Minzhi, DU Zhenqiang

2020, 49(11):  1399-1406.  doi:10.11947/j.AGCS.2020.20200149

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In a complex urban environment,navigation based on single BeiDou navigation satellite system (BDS) will be interfered by multipath (MP) and non-line-of-sight (NLOS) signals, which degrades the accuracy of positioning. In order to solve this problem, a robust unscented Kalman filter (UKF) with motion constraint is proposed. The algorithm constructs an equivalent weight function based on the innovation vector, which will overcome the problem of performance degradation of conventional robust method caused by inaccurate initial values of the position and receiver clock offset. In addition, the approximate moving direction and elevation of the carrier are used to further enhance the filtering solution. The actual on-board experiment results show that this method can effectively suppress the interference of MP and NLOS signals, and improve the accuracy of BDS navigation in urban environments.

Modeling and assessment of regional atmospheric corrections based on undifferenced and uncombined PPP-RTK

WU Guanbin, CHEN Junping, WU Xiaomeng, HU Jinlin

2020, 49(11):  1407-1418.  doi:10.11947/j.AGCS.2020.20200103

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High-precision atmospheric modification is an important prerequisite for accelerating the convergence of PPP-RTK. Based on regional tracking network stations, we first extract the slant ionospheric and zenith tropospheric delays based on the undifferential and uncombined PPP model. Then the estimated ionospheric and zenith tropospheric delays are used as the source observations for regional PPP-RTK atmospheric modeling. The slant ionosphere correction model is based on the single difference among satellites, while troposphere correction is modeled as undifferential zenith model. Based on the proposed method, prototype PPP-RTK server and client software systems are developed, where regional server generates and broadcasts atmospheric models and the user client realizes PPP-RTK with fast convergence by receiving the broadcast parameters from the server. Experiments using CORS network in Shanghai, the results on the server end show that both ionospheric and tropospheric model of GPS, GALILEO, and BDS systems achieve an accuracy of few mm. The 646 sets of PPP-RTK experiments on the client side show that: ①For horizontal coordinates, 89.16% of all solutions converged in 30 s, 91.80% in 1 minute, and 95.98% in 2 minutes. ②For the three-dimensional positions, 86.22% converged in 30 s, 88.70% in 1 minute and 93.34% in 2 minutes. With the addition of atmospheric constraints, the fixed rate of ambiguity is 95.59%, and the localized RMSE in the horizontal and three-dimensional directions after convergence is 2.35 and 4.63 cm, respectively. The real-time PPP-RTK test experiment shows similar results, where time to first fix (TTFF) is 36 seconds,accuracy of horizontal and three-dimensional coordinates reach 1.13 and 3.21 cm, respectively.

A squared M_split similarity transformation method for stable points selection of deformation monitoring network

GUO Yinggang, LI Zongchun, HE Hua, ZHANG Guanyu, FENG Qiqiang, YANG Hao

2020, 49(11):  1419-1429.  doi:10.11947/j.AGCS.2020.20200023

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In order to improve the correctness and robustness of existing stable points selection methods of reference network when there are many unstable points, a robust stable points selection method using squared M_split similarity transformation is proposed. This method still works when the number of unstable points is close to or even more than the number of stable points. Firstly, the reference points are divided into two groups with square M_split estimation in the process of calculating the similar transformation parameters of two measurement epochs. Then, by taking the group with more points as stable one, the stable points group is divided into two groups continually until the similarity transformation parameters of the two groups have little difference. Finally, deformation analysis is conducted with the similarity transformation parameters which are calculated with the final stable points group. Experiments are carried out to compare the effect of traditional S transformation, robust S transformation and the proposed method under the condition that there exists some points with large deformation in reference network or the number of unstable points is close to or even more than the number of stable points. And the experimental results show that the proposed method has the highest correctness rate of stable points determination, gets the smallest difference between the calculated deformation and the simulated deformation, and gains the smallest root mean square of coordinates difference of the stable points group between two measurement epochs, which means that the result of the proposed method can correctly reveal the deformation of control points.

Rapid calculation of local topographic correction based on GPU parallel prism method

HUANG Yan, WANG Qingbin, FENG Jinkai, XING Zhibin, FAN Diao, TAN Xuli, LÜ Minghao

2020, 49(11):  1430-1437.  doi:10.11947/j.AGCS.2020.20190403

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In gravity reduction, local topographic correction is of great significance in the fields of gravity exploration, crustal structure analysis and geoid calculation. However, the calculation efficiency of strict prism formula is low, while the calculation accuracy of fast formula will be reduced. In this study, it is proposed that a method of topographic grid re-encoding and an eight-component strict prism integral disassembly using a CUDA parallel programming platform which realizes a fast parallel algorithm of topographic correction based on CPU+GPU heterogeneous parallel technology. The problem of task allocation and thread overload in each thread of GPU is effectively solved. And the high score of local topographic correction is solved. The results of this study provide a rigorous, fast, and accurate solution for high-resolution and high-precision topographic correction. Experimental verification shows that it takes only 1.5 s to calculate the local topographic correction in the range of 4°×6°, with the integral radius of 40' and the resolution of 1' using Tesla V100, and only 14.6 min to calculate the local topographic correction with 10″ resolution and 40 minute integral radius. It takes 45.7 h to calculate the 3″ resolution, while the traditional serial algorithm is difficult to complete the calculation. Under the condition of guaranteeing the accuracy above the micro-Gal level, the acceleration ratio of calculation can reach more than 850 times, which effectively shortens the calculation time and improves the calculation efficiency. Based on the parallel algorithm mentioned above, the topographic correction in China is calculated. The result shows that the topographic correction in China is generally lower than 80 mGal (1 Gal=10^-2 m/s²), with an average of 1.83 mGal and a maximum of 196 mGal.

Photogrammetry and Remote Sensing

Road boundaries extraction from mobile laser scanning point clouds based on discrete point Snake

FANG Lina, LU Lijing, ZHAO Zhiyuan, WANG Yunyun, CHEN Chongcheng

2020, 49(11):  1438-1450.  doi:10.11947/j.AGCS.2020.20190370

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Due to large volume of data, uneven spatial distribution of point densities, and complex scene, it is difficult to automatically extract and delineate road boundaries from mobile laser scanning (MLS) point clouds. This paper proposed a method for extracting road boundaries from MLS point clouds based on Snake. Different from the traditional Snake model defined within 2D image, we modified the Snake model directly based on 3D point clouds. Firstly, we developed a way of initializing Snake curves using pseudo-trajectory data to match multi-type road boundaries. Then, the Snake’s energy function was designed with internal, external and constrained energy terms derived from Snake curve points with their neighborhood points. Finally, the road boundaries were precisely extracted by minimizing the Snake’s energy function. Experiments were undertaken to evaluate the validities of the proposed algorithm with three different urban scene datasets acquired by different MLS system. Quantitative evaluations on the selected MLS datasets indicate that the Precision, Recall and F₁-Measure of road boundaries extraction results were over 97.62%, 98.04%, 97.83%, respectively, which validate that the proposed method proved a promising and robust solution for regular and irregular road boundaries extraction in complex urban environments.

Advanced ESD coregistration of inteferometric processing for Sentinel-1 TOPS data

WU Wenhao, ZHANG Lei, ZHANG Tengxu, WANG Mingzhou, LONG Sichun, DUAN Meng, ZHOU Zhiwei, ZHU Chuanguang

2020, 49(11):  1451-1462.  doi:10.11947/j.AGCS.2020.20180578

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The TOPS mode images of Sentinel-1 satellite usually use the overlapping regions between bursts to achieve high-precision coregistration by using enhanced spectral diversity (ESD) technique after carrying out geometric coregistration. The geometric coregistration relies on the use of satellite orbit parameters which limiting the registration accuracy. Consequently, the key of sentinel-1 image registration is to accurately estimate the residual offset after geometric registration through enhanced spectral diversity. However, the ESD suffers from incoherent noise making it difficult to meet the requirement of 0.001 of the pixels spacing. In this study, we first improve the ESD performance for single interferometric pair in following aspects: ①develop ESD multi-looking theory, optimized the ESD workflow by using early-multi-looking process; ②apply weighted periodogram to improve the parameter estimation on the basis of the residual offset equal weight observations of ESD phase; ③propose the ESD weighted estimation that exploits range overlapping areas, and an increased number of overlapping areas contribute to the estimated accuracy. On this basis of single-baseline co-registration, we proposed the optimized solutions for time-series image processing: ①use the redundant ESD observations from interferometric pairs to conduct multi-baseline coregistration; ②improve the interferogram quality by distributed scatterers technique so that increase the accuracy of the ESD estimation. The above improvement schemes are mutually complemental and can also be implemented independently. The experiment results show that the above improvement methods can improve the registration accuracy.

View selection strategy for photo-consistency refinement

ZHU Yan, YAN Qingsong, QU Yingjie, CHEN Xin, DENG Fei

2020, 49(11):  1463-1472.  doi:10.11947/j.AGCS.2020.20190499

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In 3D reconstruction, mesh refinement is generally applied to deal with noise and lack of details in triangular mesh built from dense point cloud. The existing variational refinement methods optimize the photo-consistency of the initial mesh by utilizing all the image data, but ignore the redundancy of image information and the impact of view quality on mesh refinement to some extent. In this regard, this paper proposes the strategies of master view selection and slave view selection, so as to improve the efficiency and quality of mesh refinement. Firstly, Markov random field is constructed by combining image gradient magnitude and contour detection to select master view for each triangular facet, and then slave view is selected according to the corresponding observation condition for each master view. Afterwards, we calculate the norm-weighted photo-consistency between master view and slave view, and finally surface energy function is minimized by using gradient decent method to obtain the refined mesh. The experiments show that the proposed method can recover more fine-scale details, meanwhile shorten time and increase accuracy of refinement, which confirms the validity of the proposed method qualitatively and quantitatively.

Multi-temporal remote sensing imagery semantic segmentation color consistency adversarial network

LI Xue, ZHANG Li, WANG Qingdong, AI Haibin

2020, 49(11):  1473-1484.  doi:10.11947/j.AGCS.2020.20190439

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Using deep convolutional neural network (CNN) to intelligently extract buildings from remote sensing images is of great significance for digital city construction, disaster detection and land management. The color difference between multi-temporal remote sensing images will lead to the decrease of generalization ability of building semantic segmentation model. In view of this, this paper proposes the attention-guided color consistency adversarial network (ACGAN). The algorithm takes the reference color style images and the images to be corrected in the same area and different phases as the training set and adopts the consistency adversarial network with the U-shaped attention mechanism to train the color consistency model. In the prediction stage, this model converts the hue of the images to that of the reference color style image, which is based on the reasoning ability of the deep learning model, instead of the corresponding reference color style image. This model transforms the hue of the images to be corrected into that of the reference color style images. This stage is based on the reasoning ability of the deep learning model, and the corresponding reference color style image is no longer needed. In order to verify the effectiveness of the algorithm, firstly, we compare the algorithm of this paper with the traditional image processing algorithm and other consistency adversarial network. The results show that the images after ACGAN color consistency processing are more similar to that of the reference color style images. Secondly, we carried out the building semantic segmentation experiment on the images processed by the above different color consistency algorithms, which proved that the method in this paper is more conducive to the impro-vement of the generalization ability of multi-temporal remote sensing image semantic segmentation model.

Cartography and Geoinformation

A method to shape reconstruction from planar point sets with Gestalt proximity and simplification principle

YAN Jinbiao, WU Bo, PENG Xin

2020, 49(11):  1485-1496.  doi:10.11947/j.AGCS.2020.20190406

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The widely used shape reconstruction algorithms based on Delaunay triangulation are far from sophisticated,and some problems are to be further addressed. First of all, the current methods involve a few of user-defined parameters, obstructing the effective use of them in practice. Secondly, the current methods cannot guarantee the perfect shape reconstruction if a planar point set follows a randomly distribution. To overcome these aforementioned problems, a method for planar point set shape reconstruction, namely SRGT (shape reconstruction based on Gestalt) based on Gestalt proximity and simplification is developed. On the one hand, based on the proximity theory, the gross error detection technique is used to identify and locate the extreme long edges in the Delaunay triangulation network, and then the inner and outer boundaries of the Delaunay are refined step by step. On the other hand, according to the simplification theory of Gestalt, the inner and outer holes are optimized by gross error detection technique again, and finally the small holes are removed from the list of inner boundary set. To validate the effectiveness of the proposed method, the SRGT was validated on several cases, and 4 widely used algorithms, i.e. α-shape, χ-shape, ∂RGG, and edge length ratios were selected for comparisons. The results demonstrate that SRGT can achieve the fine shape reconstruction from planar point sets in both uniform and random distribution. Moreover, the SRGT generally outperforms the other 4 methods in terms of the L² measure. Finally, the shape reconstructions with the SRGT using two actual datasets corresponding to typical GIS applications were implemented to verify the effectiveness of the proposed method, and the results consistently suggest the superior ability of the SRGT.

Relative exponential entropy model on classification evaluation of geographic information data

XIAO Jia, TIAN Qin, HE Zongyi

2020, 49(11):  1497-1505.  doi:10.11947/j.AGCS.2020.20190528

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In this paper, we propose an evaluation model of geographic information data classification based on relative exponential entropy. The internal relative exponential entropy of class and external exponential entropy among classes are designed to respectively quantify the agglomeration level of the data within each class and the discrete level among classes. With these two indexes, the relative exponential entropy of geographic information data classification is constructed. We implement the classification of the geographic information data and relative exponential entropy calculation of the classification in the Python platform, based on which the experiments are conducted. Six datasets of 5 classical distributions and a census dataset are classified with 5 frequently-used classification methods and the relative exponential entropies of the classifications are calculated. The experimental results demonstrate that when facing different distributed data the relative exponential entropy index could well indicate the optimal classification method. Meanwhile, the relative exponential entropy could reflect the tiny differences of different classification methods. The relative exponential entropy proves to be valid for the evaluation of geographic information data classification.

Summary of PhD Thesis

Object points extraction and classification of mobile LiDAR point clouds

LIU Hua

2020, 49(11):  1506-1506.  doi:10.11947/j.AGCS.2020.20190434

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Temporal and spatial analysis of tropospheric ozone, simulation of influencing factors and surface ozone estimation

MA Mingliang

2020, 49(11):  1507-1507.  doi:10.11947/j.AGCS.2020.20190438

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Temporal characteristic of climatic, soil, and hydrological elements and their influencing factors in the upper reaches of the Heihe river

SHEN Shi

2020, 49(11):  1508-1508.  doi:10.11947/j.AGCS.2020.20190458

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Key issues in the kinematic method of accurate estimation of OTL displace-ments and its application

WANG Junjie

2020, 49(11):  1509-1509.  doi:10.11947/j.AGCS.2020.20190468

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Research on full polarimetric SAR speckle filtering for coastal tidal flats

JIANG Chang

2020, 49(11):  1510-1510.  doi:10.11947/j.AGCS.2020.20190459

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