Acta Geodaetica et Cartographica Sinica

A GNSS water vapor tomography method considering boundary signals and vertical constraint

HE Xiufeng, ZHAN Wei, SHI Hongkai

2021, 50(7): 853-862. doi:10.11947/j.AGCS.2021.20200433

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GNSS three-dimensional water vapor tomography technology is used to obtain all-weather atmospheric water vapor distribution information with high spatial and temporal resolution. At present, the observation data of the tomographic model considering only the top signal have low utilization rate and large grid space rate, and the vertical constraint equation adopted is less consistent with the actual water vapor distribution. This paper based on the function fitted with sounding information to establish a vertical constraints, designs and implements a tomographic method considering boundary signals, uses the observation data of Hong Kong CORS network and radio sounding products. The improvement of the results of water vapor tomography by introducing boundary signals and for vertical constraint equation are analyzed in detail. The results show that the addition of boundary signals increases the observation equation by 51.9%, decreases the grid space rate significantly, and reduces the root-mean-square error of the solution results by 12.1%. Compared with the traditional constraint equation based on the exponential decline characteristic in the vertical direction, the root-mean-square error of the vertical constraint solution adopted in this paper is reduced by 5.7%.

Bootstrap method and the modified method based on weighted sampling for nonlinear model precision estimation

WANG Leyang, LI Zhiqiang

2021, 50(7): 863-878. doi:10.11947/j.AGCS.2021.20200136

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The Bootstrap resampling method is introduced to the nonlinear theory for solving the precision estimation in this paper. By resampling the original sample observation data or the residuals of the dependent variable to obtain Bootstrap samples instead of the complex derivative calculations, the complete algorithms of Bootstrap method for solving the problem of nonlinear accuracy evaluation are given. Aiming at the equal probability resampling of model stochastic variable, this paper obtains the empirical distribution function of the stochastic variable in the sampling process, proposes the weighted sampling strategy, and gives the detailed calculation steps of the improved method for the accuracy evaluation. The results of experiments show that the Bootstrap method based on the resampling observations and the Bootstrap method based on the resampling residuals have stronger applicability, and can obtain more reasonable parameter standard deviations than the approximate function method and Jackknife method. Furthermore, the weighted resampling Bootstrap method based on the resampling observations and the weighted resampling Bootstrap method based on the resampling residuals can obtain more accurate precision information with extensive advantages. Those which verified the feasibility and effectiveness of using Bootstrap method and the improved algorithms proposed in this paper for precision estimation of nonlinear adjustment.

Evaluation of the availability of BDS ARAIM

TIAN Yunqing, WANG Li, SHU Bao, HAN Qingqing, LI Long, YI Chen, XU Hao

2021, 50(7): 879-890. doi:10.11947/j.AGCS.2021.20200518

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With the completion of the BDS-3, the performance of the BDS has been comprehensively improved, which greatly improves the accuracy and integrity of navigation and positioning, and provides an opportunity for the development of advanced receiver autonomous integrity monitoring (ARAIM). Based on this, this paper selects one week of observation data from ten evenly distributed multi-GNSS experiment (MGEX) stations around the world for the ARAIM experiment. At the same time, the seven-day broadcast ephemeris is used for availability simulation prediction to evaluate the ARAIM availability of the BDS in the Asia-Pacific region and the world. In order to increase the authenticity of the experiment, the aviation test data is also added for experiment. The experimental results of measured data show that the ARAIM availability of the BDS-2/BDS-3 is more than 95%, and BDS-3 is more than 85% among the MGEX stations that can receive the BeiDou satellite signal with the PRN number 1-46. The ARAIM availability of BDS-2/BSD-3 or BDS-3 is 100% in aviation flight data. The simulation results show that the availability coverage of BDS-2/BDS-3 greater than 90% and 99.5% are 100% and 96.15%, respectively, and the availability coverage of BDS-3 greater than 90% and 99.5% are 100% and 57.69%, respectively in the Asia-Pacific region. Globally, the availability coverage of BDS-2/BDS-3 greater than 90% and 99.5% are 79.94% and 42.82%, respectively, and the availability coverage of BDS-3 greater than 90% and 99.5% are 56.33% and 25.32%, respectively. In addition, the combination of BDS and GPS systems can greatly improve the availability of the ARAIM algorithm.

Analysis and outlook of the operational topographic surveying and mapping capability of the SAR satellites

LI Tao, TANG Xinming, GAO Xiaoming, CHEN Qianfu, ZHANG Xiang

2021, 50(7): 891-904. doi:10.11947/j.AGCS.2021.20200199

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In this paper, we reviewed the operational topographic surveying and mapping capability, i. e., plane and height accuracy, that synthetic aperture radar (SAR) satellites achieve. The plane accuracy of TerraSAR-X, COSMO-SkyMed and Tianhui-2 meets the need of 1:50 000 digital orthophoto map standard. The state-of-the-art plane accuracy is 2 m which is achieved by TerraSAR-X. Meanwhile, the accuracy of operational ground control point production provided by TerraSAR-X is 3 cm. We reviewed the error sources and the calibration methods for centimetric SAR image location. The height accuracy of TanDEM-X and Tianhui-2 meets the needs of 1:50 000 digital elevation model standard. The state-of-the-art height accuracy is 0.88 m which is achieved by TanDEM-X if the dense vegetation areas and the snow-and-ice covered areas are exclusively included in the statistical results. We reviewed the error sources and the calibration methods for height measurement without ground control information. The paper is expected to provide references for the geolocation and height measurement of the domestic SAR satellites.

The co-polarized phase difference model for dry snow depth inversion

SONG Yina, XIAO Pengfeng, ZHANG Xueliang, ZHUO Yue, MA Wei

2021, 50(7): 905-915. doi:10.11947/j.AGCS.2021.20200125

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Snow depth is an important structure parameter of snow cover. Obtaining high-precision spatial distribution of snow depth is significant to regional water resources management, climate change research, and disaster prediction. Recently, the co-polarized phase difference (CPD) model based on the polarimetric synthetic aperture radar (PolSAR) technique has shown promising results regarding the dry snow depth estimation. The model is established based on the birefringent properties of snow and on the Maxwell-Garnett mixing formulas providing a link between the snow microstructure and CPD. In this study, the dry snow depth is computed using the PolSAR CPD method with C band GF-3 quad-polarization data and measured samples. The study area is selected from the upstream of Kelan River basin, which is located in the north Altai Mountains in Xinjiang, China. To improve the retrieving accuracy, we divide the study area into deep snow area and shallow snow area. The results show that: ①In the ideal case with constant snow anisotropic relative permittivity, CPD is only a function of snow depth. The semi-empirical linear fit model can be used to invert snow depth and the inversion accuracy is related to the window size of the Gaussian low-pass filter used in the CPD calculation. The optimal filter window in shallow snow area is 55×55 pixels and the corresponding accuracy is R=0.83 and RMSE=2.72 cm, and the optimal filter window in deep snow area is 37×37 pixels and the corresponding accuracy is R=0.54 and RMSE=11.69 cm. ②With the increase of slope, the inversion error of snow depth shows a trend of increasing. The inversion uncertainty is affected by the degree of snow metamorphism, water content of snow and the incidence angle. The inversion method is more applicable to the snow layers with dry, homogeneous and low metamorphic crystallization and the SAR with larger incidence angle. ③Compared with the existing CPD model-based snow depth inversion methods, the proposed inversion method has higher accuracy and reduces the required parameters for inversion. Therefore, this study shows the practicability of CPD model in the dry snow depth estimation over mountain areas and provides a new idea for improving snow depth accuracy using CPD models.

A hybrid model combining tensor and mutual information for multi-modal image registration

LI Pei, JIANG Gang, MA Qianli, XUE Wanfeng, YANG Weihua

2021, 50(7): 916-929. doi:10.11947/j.AGCS.2021.20200492

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There are significant nonlinear intensity differences between multi-modal images. Moreover, the noise in these images will cause image degradation. Therefore, the automatic registration of multi-modal images is a challenging task. To address the two problems, this paper proposes a multi-modal image automatic registration method, which is divided into two stages: pre-registration and fine registration. In the pre-registration stage, an improved SIFT algorithm is used to roughly align multi-modal images. In the fine registration stage, the block Harris detector is first used to extract evenly distributed feature points on the pre-registered reference image. Then, the structure information in the multi-modal images is captured by the anisotropic structure tensor to construct a feature descriptor, which is robust to noise. Furthermore, a similarity criterion named TOMI (tensor orientation and mutual information) is proposed combining the tensor orientation parallelism and gradient mutual information. Finally, Multi-modal images (including Optical, LiDAR, SAR, and Map data) are used to evaluate the proposed algorithm. The experimental results show that the method proposed in this paper is robust to nonlinear intensity differences and noise, and the matching effect is superior.

High spatial resolution imagery scene classification based on semi-supervised CNNs

YANG Qiulian, LIU Yanfei, DING Lele, MENG Fanxiao

2021, 50(7): 930-938. doi:10.11947/j.AGCS.2021.20200017

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The large amount of labeled dataset is always required to train the deep convolutional neural networks (CNNs) for high spatial resolution (HSR) imagery scene classification. However, the generalization of the learned deep features is decayed when limited labeled data is available. To solve this problem, the scene classification based on semi-supervised CNNs (3sCNN) is proposed. In the proposed method, the labeled data is first used to train the model and then the prediction label and confidence of the unlabeled data is obtained with the trained model. Finally, the unlabeled data with high confidence is considered as the labeled data to train the network again and the progress described above is repeated. To demonstrate the effectiveness of the proposed method, the experiments on three datasets are performed. The results show that the proposed method can effectively improve the classification.

Positioning model and analysis of the sailing circle mode of seafloor geodetic datum points

ZENG Anmin, YANG Yuanxi, MING Feng, MA Yueyuan

2021, 50(7): 939-952. doi:10.11947/j.AGCS.2021.20200529

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Sailing circle is a commonly used surveying pattern in determining the position of seafloor datum points. In this paper, the positioning efficiency of sailing circle mode is analyzed systematically. Firstly, the acoustic ranging non-differential positioning model considering the variation of sound velocity profile and the inter-epoch differential positioning model weakening the influence of systematic error are analyzed. Then, the positioning efficiency of non-differential and single-difference positioning models in sailing circle mode is analyzed, including the measurability of position parameters, the optimal measurement radius of different component position accuracy, the theoretical accuracy achieved, and the influence of ranging error on positioning parameters, et al. Theoretical analysis shows that in the standard sailing circle mode, to ensure the accuracy of different components of the datum position, different optimal measurement radiuses are derived, and the elevation component cannot be estimated with the pre epoch and post epoch differential positioning model. Both the simulation data and the measured examples show that the differential positioning model in sailing circle mode weakens the influence of the ranging system error, but also reduces the geometric observation intensity of the design matrix, which even lead to an ill-posed model and obvious weakening of the depth information estimation accuracy of the differential model.

Seafloor topography inversion using least square collocation considering nonlinear term

FAN Diao, LI Shanshan, OUYANG Yongzhong, MENG Shuyu, CHEN Cheng, XING Zhibin, ZHANG Chi

2021, 50(7): 953-971. doi:10.11947/j.AGCS.2021.20200341

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The linear term of seafloor topography and satellite altimetry gravity data draws much attention and non-linear term tends to be ignored in current seafloor topography inversion. We proposed to use least square collocation (LSC) to estimate the linear term and non-linear term of seafloor topography and gravity data. A certain area in the sea of Japan was selected as the target sea area and corresponding bathymetry models were constructed by vertical gravity gradient anomaly (VGG) and gravity anomaly (GA) as the input data based on LSC. The accuracy of the inversion models was evaluated using shipboard sounding data as external checking points, and the spectral characteristics of the inversion models were analyzed. The results in the study area showed that the accuracy of the inversion models derived by the same GA and VGG based on LSC was improved by 2.5 times and 3.5 times at least, the relative accuracy was improved by 9.76% and 13.07%, compared with the least-square bathymetry models which only consider the linear term of seafloor topography and gravity data in the paper, which indicated that LSC greatly improved the quality of bathymetry inversion. The correlation coefficients between the inversion models and some other models, i. e. S&S V18.1, ETOPO1, GEBCO and BAT_VGG, were all above 0.95, which verifies the validity of the method (LSC) in the study area. The accuracy of the models by LSC was similar to S&S V18.1 and much higher than ETOPO1 and other bathymetry models in the study area. The inversion models could improve the relevant band information of ship measuring data effectively. The bathymetry models derived by VGG improved the relevant band information of shipboard sounding data more obviously than the bathymetry models by GA (the range of inversion waveband was 15 km to 160 km). In summary, the results in the study area verified the LSC’s feasibility and effectiveness.

Multibeam acoustic seabed classification combining SVM and adaptive boosting algorithm

JI Xue, TANG Qiuhua, CHEN Yilan, LI Jie, DING Deqiu

2021, 50(7): 972-981. doi:10.11947/j.AGCS.2021.20200556

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As a new technology, multibeam acoustic classification has been rapidly developed in recent years. A seabed sediment classification approach, GA-SVM-AdaBoost algorithm, is proposed by using the genetic algorithm (GA) optimized support vector machines (SVM) classifier as the AdaBoost weak classifier to solve the multi-classification problem in multibeam acoustic seabed classification. The sonar mosaic is obtained from multibeam echo sounder backscatter data collected in the Jiaozhou Bay within fine processing. The 10 dimensions advantage features are selected by SVM-RFE-CBR algorithm before input GA-SVM-AdaBoost classification model. Compared with SVM, GA-SVM and AdaBoost based on single-layer decision tree, the classification results of GA-SVM-AdaBoost algorithm are more satisfactory. The total classification accuracy is as high as 92.19%, which is better than the other three models. It is proved that the proposed method can be effectively applied to high precision seabed sediment identification.

Disturbance analysis of underwater positioning acoustic ray and design of piecewise exponential weight function

WANG Xinpu, XUE Shuqiang, QU Guoqing, LIU Yixu, YANG Wenlong

2021, 50(7): 982-989. doi:10.11947/j.AGCS.2021.20200424

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The sound velocity error is an important error source of underwater positioning, which mainly includes the uncertainty of sound velocity measurement and the sound velocity error caused by the temporal-spatial variation of the sound speed field. Based on the constant gradient sound ray tracking model, we derive a mathematical model for the sound ray disturbance analysis about the incident angle, sound velocity gradient and water depth. The results show that, for the same water depth and sound velocity error, the greater the incident angle is, the greater the impact of incident angle perturbation on the sound ray, and the greater the impact of sound ray bending will be. According to the derived function response relation between incident angle disturbance and acoustic ray disturbance, a piecewise exponential function stochastic model of underwater positioning based on incident angle correlation is established. The positioning results of the piecewise-exponential function random model are compared with the equal weight model. The piecewise-cosine weighting model is also validated, but the random model in this article will retain more observation information.

Research on methodology and the key technology of indoor 3D structured reconstruction from mobile LiDAR point clouds

CUI Yang

2021, 50(7): 990-990. doi:10.11947/j.AGCS.2021.20200592

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Feature extraction and intelligent analysis of deformation based on variational mode decomposition and relevant vector machine

LUO Yiyong

2021, 50(7): 991-991. doi:10.11947/j.AGCS.2021.20210059

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Mass changes of glaciers in eastern Pamir using remote sensing and GIS

ZHANG Zhen

2021, 50(7): 992-992. doi:10.11947/j.AGCS.2021.20200335

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Regional augmented PPP-RTK using reference networks with different scales

WANG Siyao

2021, 50(7): 993-993. doi:10.11947/j.AGCS.2021.20200336

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Research on key issues and service performance analysis of BDS/GNSS global augmentation system

CHEN Liang

2021, 50(7): 994-994. doi:10.11947/j.AGCS.2021.20200355

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