Table of Content

20 April 2023, Volume 52 Issue 4

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Review

Exploring the Geodesy principle architecture and development from the perspective of Granted NSFC Projects

CHENG Huihong, YAO Yibin, ZHAO Qian, WU Yunlong

2023, 52(4):  523-535.  doi:10.11947/j.AGCS.2023.20220663

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As a significant development field of Earth science, Geodesy is concerned with the meticulous observation and analysis of the geometric and physical characteristics of both the Earth and planets, which inform our understanding of their shape, material movement status, and space environmental response. Moreover, this discipline plays a pivotal role in the provision of spatio-temporal and gravity benchmarks, which are instrumental in the construction and maintenance of national infrastructure and defense. With the continuous extension and rapid development of Geodesy moving forward to both sides of earth science fundamental research and cross-application of relevant technologies, its research capability has been significantly improved, especially playing an increasingly important role in depicting, structuring and recognizing the Earth, in solving issues of earth science. Based on the application and funding projects of National Natural Science Foundation of China (NSFC) over recent years, this paper performs a statistical analysis in terms of the project types, branch fields, supporting units, research directions, and key words, discusses the development characteristics of the discipline, and constructs knowledge map of Geodesy discipline architecture—Geodesy discipline tree, aiming at providing valuable reference for scholars of Geodesy-related field.

Geodesy and Navigation

The method of sound speed errors correction in GNSS-acoustic location service

CHEN Guanxu, GAO Kefu, ZHAO Jianhu, LIU Jingnan, LIU Yanxiong, LIU Yang, LI Menghao

2023, 52(4):  536-549.  doi:10.11947/j.AGCS.2023.20220097

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Sound speed error is the main error source in GNSS-acoustic positioning, which restricts the accuracy of GNSS-acoustic positioning service. Based on the idea of marine space-time frame network, this paper studies the correction method of sound speed error in GNSS-acoustic location service. First, an improved empirical orthogonal function (EOF) method is proposed to construct the sound speed model hierarchically to eliminate the temporal-spatial representation error of sound speed. Then, for the sea area without sound speed profile, the idea of GNSS-acoustic location argument service is proposed based on GNSS tropospheric error processing method. Finally, for the underwater vehicle location argument service, the analysis of the ocean sound speed tomography method is carried out. The above correction idea of sound speed error is verified by using the measured data of 3000 m depth sea area in the South China Sea. The results show that the sound speed field constructed by the improved EOF method can determine the position of seafloor reference station with the decimeter-level accuracy. Based on the seafloor reference stations, the GNSS-acoustic location argument service proposed in this paper can provide decimeter-level accuracy location service for the ship within 3 km. The regional accuracy of the tomographic ocean sound speed profile in the depth interval below the underwater vehicle is better than 3.5 m/s.

Effect of satellite attitude quaternions on BeiDou precise point positioning during the eclipse season

LIU Tianjun, CHEN Qusen, JIANG Weiping, CHEN Hua, XIA Fengyu, FAN Caoming

2023, 52(4):  550-558.  doi:10.11947/j.AGCS.2023.20220245

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In order to obtain high-precision positioning, precise point positioning (PPP) user side should keep the the consistent satellite attitude model with analysis centers. Based on the satellite attitude quaternions products provided by the Wuhan university analysis centers (WUM), we introduce the yaw angle computation method that uses satellite attitude quaternions. When the BDS-2/BDS-3 satellite is at a low sun elevation angle, the satellite attitude model strategy of WUM is analyzed. By using the open-source positioning software GAMP, the BDS-2/BDS-3 PPP solutions are also investigated with different satellite attitude strategies. During the deep eclipse season, the results demonstrate that the differences between nominal and quaternion yaw angles can reach 360°, which can cause the decimeter-level biases in the phase wind-up and antenna phase center offset correction. In this period, compared with the nominal attitude, the positioning accuracy of PPP solutions with satellite attitude quaternions can be improved approximately 32%, 29% and 38% in the earth (E), north (N) and up (U) components, respectively. Furthermore, the positioning accuracy of PPP solutions with satellite attitude quaternions can be improved approximately 29%,25% and 28%in the E, N and U components, respectively, when compared to that of the deleting the eclipsing satellite strategy(deleting satellite at the farthest and closest point of the orbit). The inconsistent attitude models would reduce the reliability of PPP positioning results, so the satellite attitude quaternions that provided from the analysis centers should be used for phase wind-up and antenna phase center offset correction in the PPP user side.

Dynamic nolinear Gauss-Helmert model and its robust total Kalman filter algorithm for GNSS-acoustic underwater positioning

KUANG Yingcai, Lü Zhiping, LI Linyang, WANG Fangchao, XU Guochang

2023, 52(4):  559-570.  doi:10.11947/j.AGCS.2023.20210467

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The GNSS-acoustic combined observing is an important means to determine the position of seafloor control points, but it will be interfered by error factors such as the uncertainty in sound velocity and the positioning deviation of the sea surface platform. However, the processing strategy of general method based on the error propagation law for various errors makes the seafloor point coordinate solution inaccurate. To solve the above problems, this paper sets the time-invariant term of sound velocity ranging as the parameter to be solved, and discusses the influence of time-varying error of sound velocity ranging and transducer position error in the coefficient matrix of underwater observation equation. Thus, the dynamic nonlinear Gauss-Helmert (GH) model for GNSS-acoustic underwater positioning is constructed, and the total Kalman filter solution of this method is derived. On this basis, taking into account the gross errors polluting of the observations, the robust method and solution steps of the new model are given. Finally, simulation experiments and a testing experiment in the sea area near Jiaozhou Bay are used to verify the performance of the new model. The results show that under conditions with no gross errors and either different water depths or different transducer position errors, the accuracy and stability of the proposed method are both higher than those of the general method. When the observations are polluted by gross errors, the robust filter algorithm of the new model can accurately identify and locate the abnormal information. The precision of its 3D point deviation results can be obviously optimized, and the solution performance is superior to that of the general method.

A method of removing abnormal data from linear array total station astronomical measurement based on star position prediction

ZHANG Xu, ZHANG Chao, ZHAN Yinhu, MAO Qingzhou

2023, 52(4):  571-578.  doi:10.11947/j.AGCS.2023.20210675

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Aiming at the trend of miniaturization and automation of astronomical surveying instruments, this paper proposes a method for astronomical surveying data processing based on linear array total station. First, the methods for star centroid extraction and observation epoch determination are introduced. Then, the causes of gross errors are analyzed, and a method for gross error elimination based on star centroid prediction is proposed. Finally, two field experiments are designed and conducted, and the positioning accuracies are compared before and after the gross error elimination. The results show that the single-period positioning results are relatively stable after the gross errors are eliminated, and the mean square error of 8-period positioning result is less than ±0.3", which meets the requirements of first-class astronomical measurement. At the same station, after four-night joint measurement, the errors of astronomical longitude and latitude are reduced to 0.23" and 0.61", respectively. Compared with traditional astronomical surveying instruments, our method not only achieves miniaturization, automation, and precision, but also avoids human-eye observation, which doubles the observation efficiency.

Research and ground-based validation on Mars rover localization based on multi-level images matching

CAO Zilong, TONG Xiaohua, XU Xiong, YE Zhen, XIAO Changjiang

2023, 52(4):  579-587.  doi:10.11947/j.AGCS.2023.20210635

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The high-precision positioning of the rover in deep space exploration is essential for its safety and the success of the exploration missions. Two types of positioning methods for rovers are commonly used: relative and absolute positioning. The absolute positioning method mainly uses the orbiter/lander images as a reference to determine the rover location in the global coordinate system. Considering that an unmanned aerial vehicle (UAV) was carried in the Mars 2020 Project for the first time and finally verified in the Mars environment, high-resolution images from the UAV can therefore be used for rover localization. In this paper, a novel localization framework for Mars rover was proposed by matching multi-source images from orbiter, UAV and the rover respectively. Firstly, the structure from motion method was introduced to reconstruct the regional 3D high-resolution terrain from UAV images. Furthermore, a multi-view matching strategy was designed for UAV and rover images to determine the rover position in the reconstructed local 3D map by the space resection method. Finally, the rover position in the global coordinate system can be obtained by matching the UAV with the orbiter images. To verify the effectiveness of the proposed method, a simulated experiment was designed based on the test field for deep space exploration in Tongji university. The experimental result shows that the proposed localization method can generate high accuracy positions for Mars exploration with the assistance of high-resolution UAV images, and therefore support the following similar exploration missions for rovers.

Orbit determination of Tianwen-1 with one-way Doppler

KONG Jing, ZHANG Yu, DUAN Jianfeng, CHEN Lue, WANG Hong, FAN Min

2023, 52(4):  588-595.  doi:10.11947/j.AGCS.2023.20220085

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Precision orbit determination of Tianwen-1 using one-way Doppler is a first trial in deep space exploration of China. In this paper, a method of orbit determination with one-way Doppler is proposed. Firstly, the observation model of one-way Doppler is established and the theoretical error is analyzed. Secondly, the orbit determination of Tianwen-1 is carried out using one-way Doppler during the relay orbit phase. The orbital accuracy is evaluated in two ways, the first one is orbital comparison with precision orbit determined using UXB and VLBI, the second one is overlap comparison. The results show that the instability of ultra-stable oscillator and phase scintillation error are the main error sources that affect the accuracy of one-way Doppler measurement. The orbital accuracy can be better than 1 km using only one-way Doppler during the relay phase, and can provide important support for China's future deep space exploration missions.

Analysis and solution of pseudorange layering between BDS-2 and BDS-3 systems

ZENG Huiyan, AI Lun, CHENG Jie, GENG Pengfei, ZHANG Ruwei, CHEN Mohan, SUN Shujie, LI Mingzhe

2023, 52(4):  596-604.  doi:10.11947/j.AGCS.2023.20210518

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BDS-2 and BDS-3 satellites not only have the same problem of pseudorange bias as other navigation systems, but also have the decimeter-level pseudorange layering between the two systems. In order to minimize the influence of pseudorange layering, two receivers with configurable loop parameters are selected for experimental analysis, and the influence relationship between the design of receiver loop parameter and pseudorange layering is analyzed.The results show that the pseudorange layering of B1I signal between BDS-2 and BDS-3 can be reduced from decimeter-level to centimeter-level when the correlator spacing parameter configuration value of 0.3 chip and above is selected to track the B1I signal. For B3I signal, the correlator spacing parameter of 0.6 chip and below is required for tracking. According to the research in this paper, the pseudorange layering problem between BDS-2 and BDS-3 can be significantly improved by tracking the B1/B3I signal with a reasonable correlator spacing value. At the same time, it can also reduce the relative deviation positioning accuracy between receivers. The research in this paper has reference significance for promoting the development and improvement of BeiDou navigation receivers and chips.

An improved multi-surface function method with residual constraint for the fusion of shipborne and satellite altimetry derived gravity data

ZHAO Chuang, JIN Taoyong, QIN Pengbo, YANG Lianjun

2023, 52(4):  605-613.  doi:10.11947/j.AGCS.2023.20210444

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In order to obtain accurate regional gravity field, it is necessary to fuse multi-source gravity data. In this study, an improved analytical fusion method based on multi-surface functions by introducing residual constraint factors is proposed. Taken the surrounding the Japanese archipelago area as example, collecting the shipborne gravity data and satellite altimetry derived gravity field model, several factors which affect the accuracy of fusion results, including the block size, the quantity and distribution of the fused shipborne gravity data, are analyzed. And with optimal above factors, the fused results of the improved method are compared with those of the least square collocation method and the multi-surface function method. Compared to the shipborne gravity data for verification, the improved method with residual constraint has the best accuracy, as well as the smallest extreme values and standard deviations. Furthermore, the improved method reduced the discrepancy of two kinds of data near the control shipborne measuring points, and extrapolate to the other areas to improve the accuracy of satellite altimetry derived gravity model with reasonable distributed residuals.

Photogrammetry and Remote Sensing

Surface-volume-bottom joint-filtering algorithm for Airborne LiDAR bathymetric point cloud

SU Dianpeng, YAN Doudou, CHEN Liang, CHEN Yu, DONG Jian, WU Di, YU Xiaolin

2023, 52(4):  614-623.  doi:10.11947/j.AGCS.2023.20220248

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The data quality of airborne LiDAR bathymetry (ALB) is affected by many factors (such as sea surface fragmentation waves, floating algae, fish groups, and submarine secondary echoes). To reduce the noise generated by these interferences, a joint-filtering algorithm taking into account the surface, volume, bottom (SVB) is proposed. For water surface noise, the point cloud on the sea surface is separated by building the opposing cloth simulation filter model. Then, the water body outlier is removed by establishing a SOR (statistical outlier removal) filter. Finally, the noise smoothing is performed by building a moving trend surface model for small-scale underwater noise near the terrain body. The ALB data collected in the Jiaozhou Bay area of Qingdao using RIEGL VQ-840-G UAV on-board LiDAR bathymetric system are used to verify the performance of the proposed SVB filtering algorithm. The experimental results show that the overall accuracy and Kappa coefficient of the SVB joint-filtering algorithm can reach 97.45% and 0.947, respectively. It has high efficiency while ensuring the accuracy rate. Compared to the existing algorithms, the proposed filtering algorithm can better solve the problem of ALB point cloud filtering, and can provide an effective solution for ALB bathymetric data point cloud filtering.

Attention-guided feature fusion and joint learning for remote sensing image scene classification

YU Donghang, XU Qing, ZHAO Chuan, GUO Haitao, LU Jun, LIN Yuzhun, LIU Xiangyun

2023, 52(4):  624-637.  doi:10.11947/j.AGCS.2023.20210659

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Aiming at the difficulties of high-precision remote sensing image classification caused by scale variations, inter-class similarity and intra-class difference, a method with attention-guided feature fusion and joint learning is proposed for remote sensing image scene classification to make full use of multi-scale features extracted from the images. First, the deep convolutional neural network is used to extract three levels of feature maps from the images. Then, the residual attention mechanism is designed to enhance the semantic information and suppress the noise information of the feature maps. Finally, global average pooling is used to obtain the global information of the feature maps and to construct the feature vectors. Then the three levels of feature vectors are fused by connection.The three levels of feature vectors and the fusion result are classified in independent fully connected layers, respectively.During the training process, the joint loss is calculated to optimize the model's parameters. And multi-classifier decision-level fusion is adopted to improve the robustness of prediction. Experimental results on the UC Merced, AID and NWPU-RESISC45 datasets show that the proposed method can significantly improve the discrimination on similar scenes and scenes with intra-class difference. And compared with the similar method using multi-scale features, the overall accuracies are improved by 0.84%, 4.04% and 4.43%, respectively.

Dual decoupling semantic segmentation model for high-resolution remote sensing images

LIU Shuai, LI Xiaoying, YU Meng, XING Guanglong

2023, 52(4):  638-647.  doi:10.11947/j.AGCS.2023.20210455

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Semantic segmentation is one of the core contents of high spatial resolution remote sensing images analysis and understanding. The existing semantic segmentation network based on deep learning will lead to the loss of high-frequency information and inaccurate edge segmentation of remote sensing images. Aiming at this problem,this study designs a dual decoupling semantic segmentation network model to improve the semantic segmentation performance of high-resolution remote sensing images. The extracted two-level feature maps are decoupled into edge features with high-frequency characteristics and body features with low-frequency characteristics,and the decoupled edge and body feature maps are fused. Furthermore,a loss function considering edge and body is proposed to optimize the ground feature elements.Experiments on ISPRS Vaihingen and ISPRS Potsdam 2D high spatial resolution remote sensing image datasets. Compared with the results of the existing remote sensing images semantic segmentation network model,the dual decoupling semantic segmentation network model can effectively improve the segmentation accuracy of ground feature elements.

Super-resolution reconstruction method for remote sensing images considering global features and texture features

HU Anna, LIU Rui, WU Liang, ZHANG Jin, XU Yongyang, CHEN Siqiong

2023, 52(4):  648-659.  doi:10.11947/j.AGCS.2023.20210571

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Due to the performance limitation of remote sensing equipment, the quality of the remote sensing image is affected, and the low-resolution remote sensing image limits the accuracy of remote sensing interpretation applications. Insufficient global information and texture details of reconstructed remote sensing images are still in super-resolution reconstruction research. Therefore, this study proposes a super-resolution reconstruction method for remote sensing images considering global features and texture features. The method utilizes the feature learning ability of the generative adversarial network to optimize the model in two aspects: global information enhancement and texture information enhancement. On the one hand, the global feature enhancement part is used to solve the problem that the current super-resolution reconstruction model does not pay attention to the global remote sensing information of low-resolution remote sensing images. The self-attention module is introduced to the generation network, which is used to obtain the global object attention map, and the remote object information in remote sensing image is used as a reference in the reconstruction process. On the other hand, the texture enhancement part is used to solve the problem of insufficient texture information of the reconstructed remote sensing image. Texture loss is introduced to the optimized generated network that the texture information of ground objects can be improved. In addition, weight normalization is adopted to replace batch normalization to avoid false shadows in the reconstruction result. The experimental results show that the proposed super-resolution algorithm can not only enhance the features of the ground object, but also recovery the texture details for ground objects, and the SSIM, FSIM, and PSNR values of the reconstructed super-resolution image quality evaluation index are 0.756, 0.595 and 26.005, respectively.

Study on elastic skeleton storage coefficient in Beijing-Tianjin-Hebei region combining satellite and ground data

ZHANG Yupeng, ZHANG Yonghong, WU Hongan, LIU Qinghao, WEI Jujie, KANG Yonghui

2023, 52(4):  660-669.  doi:10.11947/j.AGCS.2023.20210454

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Due to over-exploitation of groundwater, the soil structure in the Beijing-Tianjin-Hebei Plain has been severely damaged.This study was taken to understand the health status of the current soil structure and give suggestion to the location that suitable for obtaining groundwater in the Beijing-Tianjin-Hebei area. First of all, based on GRACE-FO data and MCTSB-InSAR technology, the groundwater change sequence and subsidence change sequence of the Beijing-Tianjin-Hebei region from 2017 to 2019 are extracted respectively. Then, the neighborhood averaging method was used to achieve the same spatial resolution of the two data,and the elastic skeleton water storage coefficient maps of the Beijing-Tianjin-Hebei region in 2017, 2018 and 2019 were obtained for the first time. Finally, combined with the topography, soil types, rainfall and temperature conditions in each year in the Beijing-Tianjin-Hebei region, a comparative analysis of the spatial and temporal dimensions of the elastic skeleton water storage coefficient map is carried out. The study found that the average soil structure in the Beijing-Tianjin-Hebei region is gradually getting better, but the soil structure in the southeast of the region continues to deteriorate; the soil structure in the northwest of the Beijing-Tianjin-Hebei region is more suitable for exploiting groundwater than the southeast region.

Cartography and Geoinformation

Geography-aware representation learning for trajectory similarity computation

WU Chenhao, XIANG Longgang, ZHANG Yeting, WU Huayi

2023, 52(4):  670-678.  doi:10.11947/j.AGCS.2023.20220026

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Quantifying the similarity between two trajectories is a fundamental research that underlies many trajectory-based applications. Conventional methods suffer from inefficiency and noise sensitivity, making it difficult to achieve large-scale deployments. Current researches start to explore the emerging deep representation learning method, which maps high-dimensional trajectory data to a low-dimensional vector space for efficiently performing similarity measurement by computing the distance between trajectory representations. This paper pioneers the idea of Transformer, and proposes a geography-aware deep representation learning model for trajectory similarity computation: First, the two-dimensional coordinate point is converted into a one-dimensional sequence using Geohash algorithm, which can preserve the spatial correlations of the trajectory point during the embedding. Second, a deep trajectory representation learning model is constructed based on the Transformer framework, and a masked point strategy is employed to ensure that the model can acquire robust vector representations from low-frequency, noisy data. Final, a geography-aware loss function is devised to penalize the model and narrow the representation of spatially similar trajectories via a distance factor. Experiments show that the proposed method outperforms the state-of-the-art model in the similarity measurement and is at least one order of magnitude faster than the traditional models in terms of computational efficiency.

An indoor fisher discriminant model for indoor POI salience evaluation

LI Huarong, ZHENG Jiaxin, LI Tiantong

2023, 52(4):  679-688.  doi:10.11947/j.AGCS.2023.20210547

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In the rapid development of the social economy, the structure of large buildings is more and more complex, and people are easily lost in it, so the indoor location service becomes increasingly significant. Landmarks are the basic elements of the indoor space that can help people recognize the indoor orientation and location. However, many existing methods of indoor landmark selection ignore the unique features of indoor POIs and are guided by the outdoor criteria, resulting in a mismatch between the selected landmarks and users' cognition. The paper adopts the fisher discriminant analysis (FDA) for the above problem to process test data from the experiment of exploring factors affecting indoor POIs salience, including quantifying semantic information, building model, model self-judgment and cross-validation. And the model of indoor POI salience evaluation is confirmed to select indoor landmarks. The results indicated that the established model significantly affects discriminating and classifying indoor POI's salience, and the selected landmarks can be consistent with the user's cognitive results.

Summary of PhD Thesis

Effect of evolving tides on nuisance flooding along the US coastline

LI Sida

2023, 52(4):  689-689.  doi:10.11947/j.AGCS.2023.20210476

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Research on BDS satellite-based augmentation system decimeter-level positioning and multi-GNSS real-time single-frequency precise point positioning

WANG Ahao

2023, 52(4):  690-690.  doi:10.11947/j.AGCS.2023.20210477

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Monitoring global coastline changes over 1987—2016 using Landsat data

XU Nan

2023, 52(4):  691-691.  doi:10.11947/j.AGCS.2023.20210481

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Research on high precision fusion method of heterogeneous data in mobile mapping system

YU Jiayong

2023, 52(4):  692-692.  doi:10.11947/j.AGCS.2023.20210482

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Study on indoor positioning method based on smartphone multi-sensor considering pedestrian activity

ZHANG Shuai

2023, 52(4):  693-693.  doi:10.11947/j.AGCS.2023.20210483

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Research on characteristic identification methods of bridge dynamic monitoring data

WANG Xinpeng

2023, 52(4):  694-694.  doi:10.11947/j.AGCS.2023.20210493

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Study on cloud and snow discrimination in the highlighted and complex underlying surface

WU Tingting

2023, 52(4):  695-695.  doi:10.11947/j.AGCS.2023.20210519

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Modeling and predicting key tropospheric parameters in China

LI Junyu

2023, 52(4):  696-696.  doi:10.11947/j.AGCS.2023.20210521

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