Table of Content

20 May 2021, Volume 50 Issue 5

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Geodesy and Navigation

Virtual AP based indoor localization in area without linear constraints

XUE Weixing, LI Qingquan, ZHOU Baoding

2021, 50(5):  569-579.  doi:10.11947/j.AGCS.2021.20200450

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For narrow areas such as corridors, the positioning accuracy can be significantly improved by using behavioral landmarks and electronic indoor maps. However, in wide indoor areas without linear constraints,such as offices, shops and airport halls, the use of inertial sensors and indoor map cannot achieve a significant performance gain. Virtual access point (AP) is the "virtual position" of AP calculated by using the simplified formula of wireless signal attenuation with reference points.Based on this, a fingerprint point clustering algorithm based on virtual AP coordinates has been proposed in offline phase. An AP selection algorithm based on eight-diagram has been proposed to reduce the calculation amount of online positioning. Finally, experiments conducted in different office buildings demonstrated that the positioning accuracy of the proposed algorithms is considerably better than that of the traditional methods.

Precise absolute and relative orbit determination for distributed InSAR satellite system

SHAO Kai, ZHANG Houzhe, QIN Xianping, HUANG Zhiyong, YI Bin, GU Defeng

2021, 50(5):  580-588.  doi:10.11947/j.AGCS.2021.20200415

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Precise orbit and baseline determination of formation-flying low Earth orbiters are prerequisites for the success of distributed InSAR satellite system mission. GNSS-based reduced-dynamic absolute and relative orbit determination method is the main method to obtain high-precision orbit and baseline products. The absolute and relative orbit determination for TH-2 satellite system is researched using the space-borne GPS data. The results show that the signal tracking abilities and data qualities of the receivers equipped on satellite A and satellite B are almost the same. By modeling orbital maneuvers with constant empirical accelerations, the influences of orbital maneuvers on absolute and relative orbit determination for TH-2 satellite formation can be effectively eliminated. For single-satellite absolute orbit determination, the three-dimensional (3D) RMS of 6 h overlapping orbit differences is less than 1.2 cm. The RMS values of satellite laser ranging data validation residuals for satellite A and satellite B are 2.76 cm and 2.33 cm, respectively. For dual-satellite relative orbit determination, the 3D RMS of 6 h overlapping baseline differences is about 0.66 mm. Baseline comparison RMS with the products of Xi'an Research Institute of Surveying and Mapping are 0.73 mm, 1.11 mm, 0.51 mm and 1.43 mm in radial, tangential, normal and 3D direction, respectively.

Weighted least squares regularization iteration solution and precision estimation for ill-posed multiplicative error model

WANG Leyang, CHEN Tao, ZOU Chuanyi

2021, 50(5):  589-599.  doi:10.11947/j.AGCS.2021.20200126

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Aiming at the ill-posed problem of multiplicative error model, this paper introduces the Tikhonov regularization method to derive the weighted least squares regularization solution. Considering the complex nonlinear relationship between parameter estimations and the observations when using weighted least squares regularization method to solve the ill-posed multiplicative error model, the scaled unscented transformation (SUT) method is used to calculate the mean value and mean square error matrix of the nonlinear function by weighted without derivation for precision estimation of ill-posed multiplicative error model. The simulated and actual examples results show that the weighted least squares regularization iterative solution proposed in this paper can effectively weaken the ill-posed model, and the precision estimation method based on SUT method can obtain more reasonable precision information than the existing methods, and has strong applicability.

Photogrammetry and Remote Sensing

Monitoring and analysis of subsidence along Lian-Yan railway using multi-temporal Sentinel-1A InSAR

HE Xiufeng, GAO Zhuang, XIAO Ruya, LUO Haibin, FENG Can

2021, 50(5):  600-611.  doi:10.11947/j.AGCS.2021.20200226

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Multi-temporal interferometry synthetic aperture radar (MT-InSAR) has the capability to monitor deformation with millimeter precision over wide areas. It has been widely applied for the monitoring of land subsidence. In recent years, much attention was paid on monitoring of the subsidence along large-scale man-made linear features represented by high speed railway(HSR) with MT-InSAR. This paper conducts a tentative test for applying C-band SAR data to the deformation monitoring of HSR subgrade, phase stability analysis and improved StaMPS technology were jointly used to increase the point density and stability of deformation parameter solution. In this paper, a total of 47 Sentinel-1A images spanning 21 months were processed for MT-InSAR analysis along Lian-Yan HSR, and the accuracy of linear deformation velocity and time-series deformation were evaluated respectively by the data of continuous BDS (BeiDou navigation satellite system) monitoring station. The results demonstrate that C-band Sentinel-1A data is capable of achieving millimeter accuracy in linear deformation velocity and time-series deformation, the mean root mean square error (RMSE) value of time-series displacement differences between the InSAR and the BDS is 3.8 mm, agreed well with BDS monitoring data, and the overall performance of Lian-Yan HSR is stable.

Remote sensing image retrieval with ant colony optimization and a weighted image-to-class distance

YE Famao, MENG Xianglong, DONG Meng, Nie Yunju, GE Yun, CHEN Xiaoyong

2021, 50(5):  612-620.  doi:10.11947/j.AGCS.2021.20200357

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Remote sensing image retrieval (RSIR) aims to find relevant images of a query image from a remote sensing image retrieval dataset. But the similarity between a query image and a retrieval image is generally used and the relationship among images on the retrieval dataset is neglected during the retrieval process. To deal with the problem, this paper presents a new retrieval method based on ant colony optimization (ACO) for RSIR. First, our method uses the pheromone to represent the similarity between images on the retrieval dataset; then the pheromone matrix is updated by ACO. Finally, the pheromone of images is used to improve the performance of RSIR. Meanwhile, an improved weighted image-to-class distance is used to measure the similarity between two images for further improving the retrieval performance. Extensive experiments are conducted on two publicly available remote sensing image databases, UCMD and PatternNet. Compared with the state-of-the-art methods, the proposed method can achieve better retrieval results.

Roof segmentation from airborne LiDAR by combining region growing with random sample consensus

ZHAO Chuan, GUO Haitao, LU Jun, YU Donghang, LIN Yuzhun, JIANG Huaigang

2021, 50(5):  621-633.  doi:10.11947/j.AGCS.2021.20200270

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Roofs of a building have the characteristics of greatly different size, complex shape and uncertain number, and airborne LiDAR point cloud has the characteristics of uneven density, irregular distribution and without any semantic information, which make many existing airborne LiDAR roof segmentation methods ineffective and their applicability and precision still need to be improved. Thus, an airborne LiDAR roof segmentation method combining region growing with random sample consensus is proposed in the paper. Firstly, the robust normal estimation is introduced to calculate point cloud normal, a proposed iterative region growing strategy and random sample consensus are applied to extract many reliable roof patches. Then, an iterative process is performed to merge these roof patches based on their parameters and the idea of inlier selection of random sample consensus(RANSAC), and roof parameters are refined by the process. Finally, the orthogonal distance of points which are not segmented by the previous steps to each roof is calculated, and points are assigned to the corresponding roof with the minimum orthogonal distance and less than the threshold, and the roof segmentation results are refined by voting in the local neighborhood. Multiple representative building point clouds and a group of regional building point clouds are used in the experiment. The results show that the proposed method can effectively segment roofs of buildings with different complexity, and can also effectively segment roofs with small area, the average segmentation correctness is 95.56% and 97.93% by using a roof and a single point as the basic evaluation unit. The results can provide reliable information for applications such as three-dimensional building model reconstruction and point cloud reduction.

Time-series co-registration for Sentinel-1 TOPS SAR Data

MA Zhangfeng, JIANG Mi, DING Qixuan

2021, 50(5):  634-640.  doi:10.11947/j.AGCS.2021.20200082

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TOPS mode is the default imaging mode of Sentinel-1 satellites, which requires an overall azimuth co-registration accuracy of 0.001 pixels to ensure that the interferometric phase difference of consecutive bursts is less than 3°. Although the ESD technique is an effective method to correct the azimuth residual shift, the accuracy will decrease due to the abrupt loss of coherence. To solve this issue, this paper presents a method to improve the accuracy of TOPS co-registration by maximizing time-series coherence. The method focuses on selecting interferometric pairs with optimal coherence and simultaneously preserve the temporal network loops by Bellman-Ford algorithm. The improvement of network can reduce the error propagation caused by low coherence during the least-squares adjustment, and therefore improve the performance of ESD estimation. Based on synthetic data and real data covering the Weihe plain, we evaluate the performance of proposed method against the state-of-the-art techniques. The results demonstrate the effectiveness of the proposed method.

Affine invariant feature matching of oblique images based on multi-branch network

ZHANG Chuanhui, YAO Guobiao, ZHANG Li, AI Haibin, MAN Xiaocheng, Huang Pengfei

2021, 50(5):  641-651.  doi:10.11947/j.AGCS.2021.20200506

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The available wide-baseline image matching algorithms have been prone to failure or only producing few matches, due to the complex affine deformation and perspective distortion. On this basis, we proposed a novel affine invariant feature matching algorithm for oblique stereo images based on multivariate network. In our method, we applied the Hessian algorithm to extract initial feature regions, then we constructed triplet network (TN) model, and obtained affine invariant feature regions through deep learning. To improve the matching performance of similar features, we proposed multilateral constraint loss function to train multi-branch descriptor network (MDN) model, and then generated deep learning descriptors with higher discrimination for image features. Afterwards, the conjugate features were produced by the matching metric of nearest/next distance ratio (NNDR), and eliminated possible mismatch points through random sampling consistency (RANSAC) algorithm. Finally, experiments on oblique stereo images acquired by unmanned aerial vehicle verified the effectiveness of the proposed approach.

Scene classification of high-resolution remote sensing imagery based on deep transfer deformable convolutional neural networks

SHI Huihui, XU Yannan, TENG Wenxiu, WANG Ni

2021, 50(5):  652-663.  doi:10.11947/j.AGCS.2021.20200190

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In recent years, scene classification of high-resolution remote sensing images based on deep convolutional neural networks has become the focus of attention. Because of the existing deep convolution neural network is not robust to the geometric deformation of remote sensing scene image, we proposed a novel scene classification method for high-resolution remote sensing image, based on the deep transfer deformable convolutional neural networks (DTDCNN). Specifically, the depth features of remote sensing image are extracted by using the trained depth model on the large-scale natural scene dataset (ImageNet), then, the deformable convolution layer is introduced to learn the depth features which are robust to the geometric deformation of remote sensing scene.The results show that:the accuracy of DTDCNN on AID, UC-Merced and NWPU-RESISC45 datasets is improved by 4.25%, 1.9% and 4.83% after adding the deformable convolution, respectively. By the adaptive adjustment of the receptive field for different objects in the scene, DTDCNN enhances the ability of spatial sampling position, and, effectively improves the accuracy of remote sensing scene classification.

Cartography and Geoinformation

Semantic-assisted CityGML model consistency checking method

WANG Yongjun, CHEN Qingyan, YANG Yujiao, CHEN Xueye, SUN Jian

2021, 50(5):  664-674.  doi:10.11947/j.AGCS.2021.20190474

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The inconsistency of model geometry, topology and semantics of CityGML data caused by the modeling method, model optimization and data conversion are widespread, which affects its further application. A rule set for CityGML building models was proposed and constructed in this paper which takes semantic constraints into account. Relevant algorithms for automatic detection and restoring of CityGML LOD2/LOD3/LOD4 multi-level-of-detail building model data are designed. Open data downloaded from OGC website was used to verify the rules and algorithms. Experimental results demonstrate that the constructed consistency rule set was complete and self-consistent, and proposed corresponding algorithms can detect most of the topology inconsistencies in CityGML building model data, and can automatically repair some of the topological and geometric errors.

An anisotropic IDW interpolation method with multiple parameters cooperative optimization

YAN Jinbiao, WU Bo, HE Qinghua

2021, 50(5):  675-684.  doi:10.11947/j.AGCS.2021.20200148

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The inverse distance weighting (IDW) is one of widely accepted methods employed for predicting an unknown spatial value using known values observed at a set of sample locations. Many factors including spatial proximity, sample size and distance decay affect the estimation of the method simultaneously. However, most of IDW-based methods do not consider the effect of spatial anisotropy. In addition, most of these methods cannot predict accurate interpolating values because they only involve a sole factor for optimization. To obtain accurate missing values and high-resolution spatial surface model, the paper proposes a novel multiple parameters synchronization optimization IDW algorithm which involves anisotropy. The proposed method simultaneously optimizes the parameters of anisotropy, neighbor size and distance decay to improve the accuracy of IDW interpolation by particle swarm optimization (PSO). Moreover, scaling and direction factor are introduced to capture the varying of distance in different direction,and a new fitness function is schemed via cross validation technique. Two different resolution datum are selected to validate the effectiveness of proposed method, and the experimental results demonstrate that our method significantly outperform the typical IDW method. Comparisons with the recently developed IDW-based method, i.e. CIDW(classical IDW), FIDW(four quadrant IDW), AIDW(adaptive-IDW) and KAIDW(K-nearest neighbor adaptive IDW), OK(ordinary Kriging), as well as AnisOK(anisotropic Ordinary Kriging) are also implemented, and the experiments show that our algorithm can achieve the best interpolation results in terms of reliable and accuracy.

A global grid model for the vertical correction of zenith wet delay based on the sliding window algorithm

HUANG Liangke, ZHU Ge, PENG Hua, CHEN Hua, LIU Lilong, JIANG Weiping

2021, 50(5):  685-694.  doi:10.11947/j.AGCS.2021.20200515

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Tropospheric delay is an important error source in Global Navigation Satellite System (GNSS) positioning. Some shortages still exist in current global zenith wet delay (ZWD) vertical stratification models, such as only single gridded data as well as monthly profiles is used for modeling. To address those of drawbacks, a new approach, the sliding window algorithm, is proposed to develop the ZWD vertical stratification model. In this work, the ZWD vertical stratification model that considering seasonal variations of ZWD height scale factor is developed, named as GZWD-H model. The ZWD layered profiles from 321 radiosonde sites in 2017 are treated as reference values, to evaluate the performance of GZWD-H model in layered vertical interpolation and its application in spatial interpolation for GGOS (global geodetic observing system) atmosphere gridded ZWD. Besides, the performance of GZWD-H model is compared to the GPT2w model. The results show that GZWD-H model shows the best performance in the ZWD layered vertical interpolation against the ZWD layered profiles from globally distributed radiosonde sites. In terms of RMS, the GZWD-H model has improved by 4% and 7% compared to the GPT2w-1 and GPT2w-5 models, respectively. Compared to GPT2w-1 and GPT2w-5 models, GZWD-H model has improved by 17% and 35% in spatial interpolation for GGOS Atmosphere gridded ZWD against surface ZWD calculated from radiosonde profiles over globe, respectively. In terms of model parameters, GZWD-H model has been significantly reduced and optimized against GPT2w-1 model, thus, the applicability of this model could be enhanced in GNSS atmospheric sounding and GNSS precise position.

Marine Survey

High-precision and quick algorithm for multibeam sounding coordinates considering the propagation surface

BI Zijun, ZHAO Jianhu, ZHENG Gen, LIU Meiqin

2021, 50(5):  695-705.  doi:10.11947/j.AGCS.2021.20200486

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In order to solve the problem that the traditional algorithm for multibeam sounding coordinates ignores the significant impact of the difference in the position of the receiving and transmitting transducer on the deep-water sounding, and the new algorithm takes into account the difference in receiving and transmitting but low efficiency, this paper proposes a high-precision and quick algorithm for multibeam sounding coordinates that considers the propagation surface. First, based on the principle of multibeam measurement and sound ray propagation, a beam propagation surface model is proposed. Second, the beams in the sector are divided into interpolation nodes and points to be interpolated. For the former, a method based on iterative search and interpolation is proposed to avoid the establishment of a complete propagation surface. For the latter, using the interpolated node parameters, a method based on polynomial interpolation is proposed to obtain the single-way time, depression angle and azimuth angle of sound ray. Finally, all beam footprints are calculated. Experiments in shallow and medium-deep water areas show that the accuracy of the cross-line inspection method using this paper method is similar to that of Caris, and is better than the traditional algorithm. Compared with the results of Caris, the depth deviations of the same beam footprint in this paper are 0.35‰ depth and 0.11‰ depth, respectively, and the efficiency in this paper has increased by 8% and 35%, respectively.

Summary of PhD Thesis

Research on monitoring of terrestrial water storage change and its load deformation combining with GNSS and GRACE data processing

LI Wanqiu

2021, 50(5):  706-706.  doi:10.11947/j.AGCS.2021.20200213

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Prediction of atmospheric reentry of space objects based on TLE data

LIU Jinghong

2021, 50(5):  707-707.  doi:10.11947/j.AGCS.2021.20200219

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Seafloor topography estimation from gravity gradients

YANG Junjun

2021, 50(5):  708-708.  doi:10.11947/j.AGCS.2021.20200221

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Study on a method for delineation of wetland hydrology boundary using multi-sources remote sensing data

FU Bolin

2021, 50(5):  709-709.  doi:10.11947/j.AGCS.2021.20200224

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Research on the theory and method of global ionospheric modeling for BDS

ZHU Yongxing

2021, 50(5):  710-710.  doi:10.11947/j.AGCS.2021.20200631

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