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Table of Content

    20 September 2019, Volume 48 Issue 9
    Review
    Review of the development of LEO navigation-augmented GNSS
    ZHANG Xiaohong, MA Fujian
    2019, 48(9):  1073-1087.  doi:10.11947/j.AGCS.2019.20190176
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    Low Earth orbit (LEO) constellation has the advantages of stronger received signal and rapider change of spatial geometry, which can be complementary to the GNSS constellation of medium-or high-Earth orbit, and has significant advantages in augmenting the accuracy, integrity, continuity and availability of GNSS, and has become a hotspot in the field of current satellite navigation. Firstly, this paper briefly presents the existing GNSS augmentation systems and summarizes the developing actuality of LEO navigation augmentation constellations at home and abroad.In allusion to LEO navigation augmentation, the advantages and disadvantages of the low-, medium-and high-Earth orbits used for satellite navigation are compared and analyzed. Moreover, the opportunities that LEO navigation augmentation system brings in terms of the combined precise orbit determination (POD), rapid and precise positioning, space weather monitoring, and indoor positioning are emphatically discussed.The challenges that the space segment, ground segment and user segment will face are also analyzed and pointed out.
    Geodesy and Navigation
    Least-square variance-covariance component estimation method based on the equivalent conditional adjustment model
    LIU Zhiping, ZHU Dantong, YU Hang, ZHANG Kefei
    2019, 48(9):  1088-1095.  doi:10.11947/j.AGCS.2019.20180227
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    A VCE method termed the least-square variance-covariance component estimation method based on the equivalent conditional misclosure (LSV-ECM) is developed. Three steps are involved. First, the equivalent conditional misclosure is extracted using the projection matrix in the equivalent conditional adjustment model, of which the quadratic equations are established for variance-covariance component estimation. The quadratic equations in the form of matrix are then transformed to the linearized Gauss-Markov form using the half-vectorization operator. A simplified and generalized LSV-ECM method is derived using the least-square principle with an unbiased and optimal estimation.Furthermore, the equivalence between the LSV-ECM and the existing VCE methods is proven mathematically, and computational complexities of the LSV-ECM and the existing VCE methods are quantitatively analyzed and investigated in the indirect adjustment model. It is shown that the new method gives the highest computational efficiency. Finally, the performance and superiority of the new method is evaluated through an adjustment of a triangulateration network and an analysis of a coordinate time series of GNSS stations.
    Height nonlinear velocity field and variance fluctuation model construction method for CORS stations
    ZHANG Hengjing, CUI Dongdong, CHENG Pengfei
    2019, 48(9):  1096-1106.  doi:10.11947/j.AGCS.2019.20190017
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    The basic concept of establishing linear velocity field with fixed period term in CORS stations height time series is described, and the problem of deviation between given period and actual period is pointed out. Therefore, this paper proposes a nonlinear velocity field modeling method for CORS stations height time series. This method takes the linear least squares solution as the initial value of iteration, and uses the gauss-newtoni-teration algorithm to solve the unknown parameters of the nonlinear velocity field model, realizing the nonlinear fitting of height time series data of CORS stations. The test method for the heteroscedasticity of the residual square sequence of the fitting model is given, and the basic criteria for the establishment of GARCH (p, q) model to reflect the fluctuations of non-stationary sequence are expounded. The six CORS stations at home and abroad more than 20 years as the research object, the height of time series nonlinear velocity motion model is set up, the results show that the CORS stations height movement does not exist strict year or half year cycle, the approximate periodic motion is most obvious, the approximate period of two years than the minimum, cycle in deviation of 12%, half year cycle is 18%, two year period is 6%, nonlinear modeling accuracy and effect is better than the linear model as a whole. The ARCH test method is used to obtain the heteroscedasticity of the residual square sequence of the nonlinear model of CORS stations height, that is, the residual square sequence has non-stationary characteristics. GARCH (p, q) model is introduced to model the non-stationary residual square sequence of the height component of CORS stations, which reflects the non-stationary fluctuation of the residual square sequence. The feasibility of GARCH (p, q) model in modeling non-stationary residual square series of CORS stations height is verified, which provides an idea for future modeling of non-stationary noise series of CORS stations height and reconstruction of nonlinear velocity field with GARCH (p, q) model.
    An improved carrier phase smoothing pseudorange algorithm with self-modeling of ionospheric delay variation
    CHEN Zhengsheng, ZHANG Qinghua, LI Linyang, LI Xuerui, Lü Hao
    2019, 48(9):  1107-1118.  doi:10.11947/j.AGCS.2019.20180404
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    The traditional single-frequency carrier phase smoothing pseudo-range algorithm is prone to divergence and precision degradation due to the influence of ionospheric delay. However, the existing solutions have limited accuracy improvement or need external data support. In this paper, the regularity of ionospheric variation is studied and a regressive model is established. On this basis, a self-modelling algorithm for single-frequency carrier phase smoothing pseudorange with ionospheric delay variation is proposed. The algorithm uses the ionospheric delay information contained in the pseudo-range and carrier observations to model the ionospheric delay, and deducts the ionospheric delay variation between epochs from the smooth pseudo-range, thus effectively avoiding the divergence of the smooth pseudo-range. Carrier smoothing pseudo-range algorithm of ionospheric self-modeling is realized by using GNSSer software. Static and dynamic observation data are used to carry out positioning experiment and precision analysis. The example shows that:① the long period regular Hatch filtering is seriously affected by the ionosphere; ② the precision of the self-modelling ionospheric delay can reach centimeter level, and the linear moving window fitting method is the best in the 30-minute window; ③ self-modeling ionospheric correction can effectively eliminate the influence of smooth pseudo-range ionosphere. With the increase of time window, the precision does not decrease; ④ the proposed algorithm is used for epoch-by-epoch single-frequency smoothing pseudo-range single-point positioning, and the positioning accuracy reaches sub-decimeter level in both static and dynamic NEU directions. In the dynamic positioning test, the horizontal and elevation direction accuracy is 6.25 cm and 10.4 cm, which are 5.4 times and 3.3 times higher than the original pseudo-range respectively.
    Seasonal sea level variations in the Red Sea inferred from satellite altimetry, GRACE and temperature and salinity data
    ZHAO Hongbin, GU Yanchao, FAN Dongming, QIU Chunhong, SU Chunpeng, FANG Weihao
    2019, 48(9):  1119-1128.  doi:10.11947/j.AGCS.2019.20190034
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    Satellite altimetry, GRACE and temperature-salinity datas are used to analyze the sea level variations in the Red Sea over the period from 2003 to 2014, and we explore the precipitation-evaporation effect and the water exchange between the Gulf of Aden and the Red Sea on local sea level variations. Due to the poor coverage and imperfection for single temperature-salinity dataset, we averaged three datasets (CORA, SODA, and ORAS4) to improve the accuracy of the steric sea level variations. In order to correct the leakage errors induced by truncation and spatial smoothing during GRACE postprocessing, we proposed an improved scale factor, which is validated by using satellite altimeter measurements. Annual amplitudes of mass-induced sea level variations observed by GRACE measurements for traditional and improved scale factor are 16.1±1.3 and 20.5±1.7 cm, respectively, and that inferred from satellite altimetry and temperature-salinity data is 20.2±1.0 cm, indicating that the improved scale factor can restore the leaked signals effectively. Results demonstrate good agreement among the satellite altimetry, GRACE and temperature-salinity data. Annual amplitude of the total sea level variations combining the GRACE mass-induced and temperature-salinity steric sea level variations is 16.6±1.7 cm, which is consistent with satellite altimeter results (16.2±0.9 cm), implying that closed-loop verification can be established among the different sea level measurements in the Red Sea. Mass exchange with the Gulf of Aden through the Bab-el-Mandeb strait has an obvious effect on the mass variations in the Red Sea, which dominates the seasonal signals of mass variations in the Red Sea.
    Photogrammetry and Remote Sensing
    Structureadaptive feature point matching for urban area wide-baseline images with viewpoint variation
    CHEN Min, ZHU Qing, HE Haiqing, YAN Shaohua, ZHAO Yitao
    2019, 48(9):  1129-1140.  doi:10.11947/j.AGCS.2019.20180266
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    A feature point matching method based on structureadaptive feature is proposed for urban area wide-baseline images. Firstly, interest points and straight lines are detected from images. Structure adaptive feature region and descriptor are constructed by exploring the geometric relationship between the interest point and the straight lines located in the local neighborhood of the point, and initial matching results are obtained by using bi-directional matching strategy. Secondly, the fundamental matrix is estimated from the initial matching results. An epipolar geometry constrained structure adaptive feature matching method is proposed to match those features have not been matched in the initial matching step. Finally, a matching expansion method is proposed based on the previous matching results to improve the matching performance.The proposed matching method can generate similar feature regions and descriptors for corresponding features under significant image viewpoint variation benefiting from the proposed structure adaptive feature region construction method. The experimental results demonstrate that the proposed method provides significant improvements in correct matches number and matching precision compared with other traditional matching methods for urban area wide-baseline images (e.g. unmanned aerial vehicle images and oblique images) with viewpoint change and occlusion.
    Deep learning based dense matching for aerial remote sensing images
    LIU Jin, JI Shunping
    2019, 48(9):  1141-1150.  doi:10.11947/j.AGCS.2019.20180247
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    This work studied that the application of deep learning based stereo methods in aerial remote sensing images, including its performance evaluation, the comparison with classical methods and generalization ability estimation.Three convolution neural networks are applied, MC-CNN(matching cost convolutional neural network), GC-Net(geometry and context network) and DispNet(disparity estimation network), on aerial stereo image pairs. The results are compared with SGM (semi-global matching) and a commercial software SURE. Secondly, the generalization ability of the MC-CNN and GC-Net are evaluated with models pretrained on other datasets. Finally, fine tuning on a small number of target training data with pretrained models are compared to direct training. Three sets of aerial images and two open-source street data sets are used for test. Experiments show that:firstly, deep learning methods perform slightly better than traditional methods; secondly, both GC-Net and MC-CNN have demonstrated good generalization ability, and can get satisfactory 3PE (3-pixel-error) results on aerial images using a model pretrained on available stereo benchmarks; thirdly, when the training samples in target dataset are insufficient, the strategy of fine-tuning on a pretrained model can improve the effect of direct training.
    NMF linear blind unmixing method based on mixed pixel's spatial and spectral correlation model
    YUAN Bo
    2019, 48(9):  1151-1160.  doi:10.11947/j.AGCS.2019.20180054
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    The present hyperspectral unmixing methods based on correlation analysis, either lack of comprehensive analysis and utilization of hyperspectral image's spatial & spectral correlation characteristics, or have a high dependence degree on prior knowledge. This paper proposes a NMF linear blind unmixing method based on mixed pixel's spatial and spectral correlation model. The method sets up spatial correlation model of adjacent pixels by improving Markov Random Filed(MRF) model, sets up spectral correlation model of adjacent bands by adopting complexity mapping technology, and introduces the two models respectively into NMF objective function externally and internally, as the constraints of the blind unmixing method. Experimental result indicates that, the proposed method can significantly reduced the degree of dependence on prior knowledge, comparing with other representative NMF reference methods including area-correlated spectral unmixing method based on Bayesian nonnegative matrix factorization(ACBNMF), minimum spectral correlation constraint NMF(MSCCNMF) and minimum volume constrained nonnegative matrix factorization(MVCNMF), the unmixing accuracy is also improved.
    Marine Survey
    Using astronomical tidal time difference for water correction
    LIU Ju, BAO Jingyang, XU Jun
    2019, 48(9):  1161-1170.  doi:10.11947/j.AGCS.2019.20180556
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    In order to solve the problem that there may be a big difference between the traditional method of water level correction using distance interpolation to calculate the tidal time difference (TTD) of the stations to be determined and the actual situation, this paper puts forward a method of water level correction using astronomical tide to directly calculate the tidal time difference between stations, studies the difference and variation of the tidal time system between astronomical tide and the measured water level of some coastal stations in China, and analyzes the deviation magnitude of the tidal time difference between two groups of adjacent stations with astronomical tide determined by different tidal numbers instead of the measured water level. Using tide gauge stations along the Yellow Sea and Beibu Gulf, the experiment of astronomical tide time difference water level correction is designed, and the effect of the traditional method and astronomical tide time difference method is compared. The experiment and analysis show that using astronomical tide to calculate the tidal time difference is closer to the measured tidal time difference than the traditional method, and the median error of the correction result of the 8 tidal constituents is controlled within 5 cm, nearly double that of the traditional method, realizing the improvement of the traditional method and proving the feasibility of using astronomical tide to correct the water level of the time difference method.
    The MF method for multi-source bathymetric data fusion and ocean bathymetric model construction
    LIU Yang, WU Ziyin, ZHAO Dineng, ZHOU Jieqiong, SHANG Jihong, WANG Mingwei, ZHU Chao, LU Haohao
    2019, 48(9):  1171-1181.  doi:10.11947/j.AGCS.2019.20180495
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    In view of complex sources and various resolutions of global deep ocean bathymetric data being difficult in fusion to construct high-resolution digital bathymetric model (DBM), we present a MF method (merge-fusion) that is suitable for multi-source bathymetric data fusion in deep waters. Then we apply it to the DBM construction of the "Challenger Deep" in the Mariana Trench. By the workflow of "Merge-Fusion", the method combines electronic charts, multi-beam, single-beam bathymetric data with general bathymetric chart of the oceans (GEBCO) data. It can fill the blank area of data while preserving details in high-resolution bathymetric data. Finally, the constructed high-resolution DBM of the "Challenger Deep" is compared with GEBCO data. The results show that the DBM obtained by this method can better maintain the topographic details. This method possesses important practical application value.
    Widespread bathymetric outliers detection and elimination based on conditional variational autoencoder generative adversarial network
    ZHANG Ruichen, BIAN Shaofeng, LIU Yanchun, LI Houpu
    2019, 48(9):  1182-1189.  doi:10.11947/j.AGCS.2019.20180203
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    In view of the complexity and variability of bathymetric data missing and exception, an algorithm named CVAE-GAN to detect and eliminate the widespread bathymetric outliersis proposed. Firstly, the proposed model is an alternative to traditional generative adversarial network (GAN) training methods, combined with the advantages of conditional variational autoencoder (CVAE) and deep convolutional generative adversarial network (DCGAN).Secondly, the network structure is introduced in detail.The generalized CVAE algorithm is added to change and reshape the sample distribution, having a better ability of dimensionality reduction.The GAN method improves the robustness of the whole algorithm.Thirdly,using electronic chart data containing widespread outliers, long-time experiments were carried out to train the CVAE-GAN till optimality. Finally, compared with median filtering method and trend filtering algorithm(TFA), the results show that the proposed method has an improvement in accuracy, stability and robustness.It is also verified that the feasibility of the proposedmethod in bathymetric data processing.
    Academic Research
    Differential positioning algorithm for deep-sea control points on constraint of depth difference and horizontal distance constraint
    SUN Wenzhou, YIN Xiaodong, ZENG Anmin, BAO Jingyang
    2019, 48(9):  1190-1196.  doi:10.11947/j.AGCS.2019.20180514
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    To solve the problem of seafloor control point (transponder) absolute positioning with a large deviation of the vertical solution, this paper proposes a differential localization algorithm with depth difference and horizontal distance constraint between underwater control points. Firstly, the variation of sound velocity profile is studied. Based on this conclusion, the influence of uncertain sound velocity profile on the ranging error is analyzed. Secondly, according to the change law of ranging error, the corresponding measuring line is designed. And an underwater differential localization algorithm for this survey strategy is proposed. Finally, simulation experiments show that the deviation of the vertical solution is reduced from more than 30 cm to about 10 cm. It implies that the new method can effectively reduce the deviation of the vertical solution of the control point positioning compared with the traditional method (circular sailing).
    Some key points of submarine control network measurement and calculation
    ZHAO Jianhu, LIANG Wenbiao
    2019, 48(9):  1197-1202.  doi:10.11947/j.AGCS.2019.20190157
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    Several problems affecting the positioning accuracy of the submarine control network are analyzed. It is considered that the ocean sound velocity changes greatly in a short time and the regularity is not strong. Constructing the sound velocity field is an effective way to weaken the representative error of the sound velocity. The influence of sound velocity on the location is also related to the beam incident angle and depth. The impact is significant and cannot be ignored. In the sound-stable waters, when the incident angles are approximately the same, high accuracy can be achieved by differential positioning with observation distance, otherwise the accuracy is difficult to guarantee. The depth or depth difference provided by the pressure sensor is introduced to improve the vertical solution precision of the control network, but the difference of tide height between two control points should be taken into account.
    Summary of PhDThesis
    Detection and analysis of glacier mass balance in the southeastern Tibet Plateau and the western Qilian Mountains by bi-static InSAR
    SUN Yafei
    2019, 48(9):  1203-1203.  doi:10.11947/j.AGCS.2019.20180591
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    Study on the response of ENSO in the troposphere and lower stratosphere based on GNSS radio occultation observations
    CHEN Zhiping
    2019, 48(9):  1204-1204.  doi:10.11947/j.AGCS.2019.20180564
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    Establishment of strict three dimensional noise model for GPS coordinate time series
    MA Jun
    2019, 48(9):  1205-1205.  doi:10.11947/j.AGCS.2019.20180584
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    Research on resolving of three-dimensional displacement from multi-source InSAR data
    WANG Zhiwei
    2019, 48(9):  1206-1206.  doi:10.11947/j.AGCS.2019.20180490
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