Acta Geodaetica et Cartographica Sinica

Effect of External Disturbing Gravity Field on Spacecraft Guidance and Surveying Line Layout for Marine Gravity Survey

HUANG Motao, LIU Min, OUYANG Yongzhong, DENG Kailiang, ZHAI Guojun, LU Xiuping, WU Taiqi

2016, 45(11): 1261-1269. doi:10.11947/j.AGCS.2016.20160175

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Centred on the support requirement of flying track control for a long range spacecraft, a detail research is made on the computation of external disturbing gravity field, the survey accuracy of gravity anomaly on the earth' surface and the program of surveying line layout for marine gravity survey. Firstly, the solution expression of navigation error for a long range spacecraft is analyzed and modified, and the influence of the earth's gravity field on flying track of spacecraft is evaluated. Then with a given limited quota of biased error of spacecraft drop point, the accuracy requirement for calculating the external disturbing gravity field is discussed and researched. Secondly, the data truncation error and the propagated data error are studied and estimated, and the quotas of survey resolution and computation accuracy for gravity anomaly on the earth' surface are determined. Finally, based on the above quotas, a corresponding program of surveying line layout for marine gravity survey is proposed. A numerical test has been made to prove the reasonableness and validity of the suggested program.

Satellite Shadow Modeling and Algorithm of Satellite Shadow Parameters for GNSS

DU Lan, ZHOU Peiyuan, FANG Shanchuan, LIU Zejun, GUO Rui

2016, 45(11): 1270-1277. doi:10.11947/j.AGCS.2016.20160063

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The satellite shadow parameters can be numerically calculated with high accuracy from the positions of the sun, the earth and the specific satellite. Unfortunately, it is difficult for the numerical calculation to give a general profile of the variations and distributions of these parameters for some certain types of orbital spacecraft. A satellite shadow model was presented based on the spatial view at the altitude of the satellite and the correlative geometry amongst the sun, the earth and the satellite. Firstly, the size and location of the satellite shadow were determined by the semi-major axis of the satellite orbit and the annual motion of the apparent sun, respectively. Secondly, the computing formulae of the satellite shadow parameters were derived, together with the correction formulae for the long-term prediction of the parameters due to oblateness perturbation, etc. Examinations on the three types of orbits for the BeiDou navigation constellation show that the proposed satellite shadow model and its shadow parameters computing formulae can provide a prompt profile of the eclipse parameters for the medium-high altitude circular orbit satellites.

Centimeter Precise Orbit Determination for SWARM Satellite via Reduced-dynamic Method

ZHANG Bingbing, NIE Linjuan, WU Tangting, FENG Jiandi, QIU Yaodong

2016, 45(11): 1278-1284. doi:10.11947/j.AGCS.2016.20160284

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Combining dual-frequency satellite-borne GPS observations with reduced dynamic models, and introducing proper pseudo-stochastic pulse parameters into the satellite's motion equation, SWARM satellite precise orbit determination is implemented. The orbit accuracy is assessed using three methods, which include analysis satellite-borne GPS phase observation residuals, orbit overlaps and external orbit comparisons. The results indicate that the SWARM satellite-borne GPS phase observation residual RMS is in the range of 7 to 10 mm, radial, along-track and cross-track orbit overlap difference RMS of 6 hours are about 1 cm, three directions have no significant systematic errors, comparisons with orbits computed by European Space Agency (ESA), Radial orbit difference RMS is in the range of 2 to 5 cm, along-track orbit difference RMS is in the range of 2 to 5 cm, cross-track orbit difference RMS is in the range of 2 to 4 cm, 3D orbit difference RMS is in the range of 4 to 7 cm, SWARM-B orbit accuracy is better than SWARM-A and SWARM-C. This evaluations indicate that SWARM satellite precise orbit determination is practicable by using reduced-dynamic method and orbit determining strategy in the article, the orbit solution is well and stable, the orbit accuracy reaches centimeter level.

A Time Transfer Algorithm of Precise Point Positioning with Additional Atomic Clock Physical Model

YU Heli, HAO Jinming, LIU Weiping, TIAN Yingguo, DENG Ke

2016, 45(11): 1285-1292. doi:10.11947/j.AGCS.2016.20160217

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In the traditional time transfer algorithms of precise point positioning, the receiver clock offset is estimated epoch by epoch as independent white noise and the short-term correlation between the epoch of the atomic clock offset is ignored. In order to solve this problem, a time transfer algorithm of precise point positioning with additional atomic clock physical model is proposed. The receiver clock parameters are expanded in the traditional model of precise point positioning by using Kalman filter to model the clock errors of high stability atomic clock, and the method of determining the covariance matrices of process noise and the initial state vector of the Kalman filter is presented. Experimental results show that the proposed algorithm can effectively avoid the convergence process of the traditional precise point positioning algorithm, and the result of the algorithm is more consistent with the physical properties of the atomic clock, this algorithm can significantly improve the accuracy and stability of the time transfer results, the accuracy of time transfer results of single station can be increased on average by 58%, and the accuracy of time synchronization between stations can be improved on average by 51%.

Soil Moisture Retrieval Utilizing GNSS Interference Signal Amplitude

HAN Mutian, ZHANG Bo, YANG Dongkai, HONG Xuebao, YANG Lei, SONG Shuhui

2016, 45(11): 1293-1300. doi:10.11947/j.AGCS.2016.20160145

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A soil moisture retrieval model was developed using GNSS interference signal amplitude, according to the interference phenomenon and GNSS receiver SNR estimation method. Antenna gain, soil permittivity and noise effect was considered in this model. The AMPD algorithm was used to extract the interference peaks and valleys from noisy normalized interference power which were then used to retrieve soil permittivity and moisture, and a simulation was performed to verify its feasibility. Results showed that the soil moisture retrieval performance using interference valleys was better compared to that using peaks, the relatively stable retrieval elevation angle range is 5°~25°, and the retrieved value was more accurate when moisture is larger than 0.06 cm³/cm³,with the standard deviation around 0.01 cm³/cm³.

Study on Improvement of Multibeam Backscatter Angular Response Model

YAN Jun, ZHANG Hongmei, ZHAO Jianhu, MENG Junxia

2016, 45(11): 1301-1307. doi:10.11947/j.AGCS.2016.20160169

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Because multibeam backscatter data is greatly affected by the AR (angular response) and the AR correction models are not perfect in the complex seabed, the multibeam image quality is seriously reduced. This paper puts forward an improved AR model and a correction method. Firstly, we average continual pings to obtain the AR curve; Secondly, we give out the extraction method of AR parameters; Thirdly, we use the parameters to establish the improved AR model of different sections of one ping; Finally, we use the model to weaken the AR effect in multibeam backscatter images. The validities of the method have been verified by the experiments of the field multibeam acoustic backscatter.

Filtering of Point Clouds Using Fusion of Three Types of Primitives Including Points, Objects and Key Points

LIN Xiangguo, ZHANG Jixian, NING Xiaogang, DUAN Minyan, ZANG Yi

2016, 45(11): 1308-1317. doi:10.11947/j.AGCS.2016.20160372

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Primitive, being the basic processing unit, is one of the key factors to determine the accuracy and efficiency of point cloud filtering. Triangular irregular network (TIN) progressive densification (TPD) and object-based TIN progressive densification (OTPD) are two existing filtering methods, but single primitive is employed by them. A multiple-primitives-based TIN progressive densification (MPTPD) filtering method is proposed. It is composed of three key stages, including point cloud segmentation, extraction of key points of objects, the key-points-based judging of the objects. Specifically, point, object and the key points are the primitive of the above three stages respectively. Four testing datasets, including two airborne LiDAR and two photogrammetric point clouds, are used to verify the overall performances of the above three filtering methods. Experimental results suggest that the proposed MPTPD has the best overall performance. In the viewpoint of accuracy, MPTPD and OTPD have the similar accuracy. Moreover, compared with the TPD, MPTPD is able to reduce omission errors and total errors by 22.07% and 8.44% respectively. In the viewpoint of efficiency, under most of the cases, TPD is the highest, MPTPD is the second, and OTPD is the slowest. Moreover, the total time cost of MPTPD is only 57.93% of the one of OTPD.

SRTM-aided Stereo Image Block Adjustment without Ground Control Points

ZHOU Ping, TANG Xinming, CAO Ning, WANG Xia, LI Guoyuan, ZHANG Heng

2016, 45(11): 1318-1327. doi:10.11947/j.AGCS.2016.20160219

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With regard to the feature that the vertical precision of SRTM(shuttle radar topography mission)data in the flat terrain area is much higher than its nominal precision, it is proposed that a stereo block adjustment algorithm without ground control by adopting SRTM data as elevation constraint. In order to improve overall vertical accuracy of the image, by constructing a wide local area network and setting intensive connecting points, SRTM is set as the initial vertical value of connecting points. In the process of adjustment calculation, ground height of connecting points distributing in the flat terrain area is made sure to rigorously approach to vertical accuracy of SRTM. Through the experiment employing ZY-3 triple linear array stereo satellite images cover across all of Hubei province, the verification results prove that the method is effective. The height root mean square errors(RMSEs)of ZY-3 stereo images is improved from 7.2 m to 2.0 m without ground control, and the RMSEs of flat areas and mountain areas improved to 1.44 m and 3.0 m respectively, which fulfills the elevation accuracy requirement of national 1:25 000 scale mapping applications.

A Low-Sampling-Rate Trajectory Matching Algorithm in Combination of History Trajectory and Reinforcement Learning

SUN Wenbin, XIONG Ting

2016, 45(11): 1328-1334. doi:10.11947/j.AGCS.2016.20160046

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In order to improve the accuracy of low frequency (sampling interval greater than 1 minute) trajectory data matching algorithm, this paper proposed a novel matching algorithm termed HMDP-Q (History Markov Decision Processes Q-learning). The new algorithm is based on reinforced learning on historic trajectory. First, we extract historic trajectory data according to incremental matching algorithm as historical reference, and filter the trajectory dataset through the historic reference, the shortest trajectory and the reachability. Then we model the map matching process as the Markov decision process, and build up reward function using deflected distance between trajectory points and historic trajectories. The largest reward value of the Markov decision process was calculated by using the reinforced learning algorithm, which is the optimal matching result of trajectory and road. Finally we calibrate the algorithm by utilizing city's floating cars data to experiment. The results show that this algorithm can improve the accuracy between trajectory data and road. The matching accuracy is 89.2% within 1 minute low-frequency sampling interval, and the matching accuracy is 61.4% when the sampling frequency is 16 minutes. Compared with IVVM (Interactive Voting-based Map Matching), HMDP-Q has a higher matching accuracy and computing efficiency. Especially, when the sampling frequency is 16 minutes, HMDP-Q improves the matching accuracy by 26%.

A Multi-scale Method for Mining Significant Spatial Co-location Patterns

HE Zhanjun, LIU Qiliang, DENG Min, CAI Jiannan

2016, 45(11): 1335-1341. doi:10.11947/j.AGCS.2016.20150371

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Spatial co-location patterns discovery aims to detect spatial features whose instances are frequently located in geographic proximity. Such patterns can reveal unknown regularity in geographic phenomena and they are helpful for decision-making. However, due to the little prior knowledge, it is difficult to specify thresholds for neighbor distance and prevalence index.As a result, the outcomes of most algorithms always include insignificant or even erroneous patterns. A pattern-reconstruction-based approach was proposed to discover only significant co-location patterns. Firstly, we introduce a new definition of MNND, which can identify the lower and upper bounds of neighbor distance threshold. Then, a null model was constructed based on the pattern reconstruction. On basis of that, selection of prevalence threshold is replaced by hypothesis testing. Finally, significant colocation patterns were mined at multiple distances and the results were evaluated by the notion of lifetime. The experimental results show that our approach could avoid the subjectivity in determining those thresholds, thereby improving the correctness and robustness.

M-Quadtree Index: A Spatial Index Method for Cloud Storage Environment Based on Modified Quadtree Coding Approach

FU Zhongliang, HU Yulong, WENG Baofeng, PENG Rui

2016, 45(11): 1342-1351. doi:10.11947/j.AGCS.2016.20150408

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Currently, the cloud storage platform based on key-value model can only support simple keyword queries but cannot support multidimensional spatial queries. To solve the problem, this paper puts forward a new method of distributed spatial index-M-Quadtree index. In the process of index building, a space partitioning method based on improved quadtree was proposed. This partitioning method specifies the minimum amount of data in the leaf area. By recombining the quad leaves, it solves the problem of storage imbalance among sub regions, and meets the parallel requirements of the MapReduce. This paper describes some algorithms about M-Quadtree index building,querying and updating under the MapReduce framework. In the experiments, we implement the M-Quadtree index on Hadoop platform to test the effect of key parameter on the efficiency of index, and also test the efficiency of index building, querying and updating under different scale of data. Comparing with existing distributed spatial index, experiments show that the M-Quadtree index performs better on data load balancing, algorithm parallelism and the efficiency of spatial querying.

The Syntax Model of Mobile Maps Generation

TIAN Jiangpeng, YOU Xiong, JIA Fenli, XIA Qing

2016, 45(11): 1352-1360. doi:10.11947/j.AGCS.2016.20150544

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Using the method of formal language (FL), the syntax model of mobile map generation is studied. The syntax model is located in the level of logical calculus of map generation based on the analysis of its process. Combined the hierarchical and recursive characteristics of map representation, the simplest form of syntax structure is abstracted as carto-lexicons and syntax-rules. The classification system of carto-lexicons is established as well as the model of the spatial relation predicate system, and the map operation rules and rules of different levels of syntactic units are discussed. The compilation process and key techniques of the syntax model are discussed, and the feasibility of the model is verified through mobile maps generation experiment. The essence of the model is a kind of formal language grammar, which uses finite rules and lexicons to generate maps automatically, as well as a kind of high-level cartography interface of human-computer interactive.

Public DEM-assisted Positioning Method for Chinese Satellite Imagery without Ground Control Points

CHEN Xiaowei, ZHANG Baoming, ZHANG Tonggang, GUO Haitao, CEN Minyi

2016, 45(11): 1361-1370. doi:10.11947/j.AGCS.2016.20160317

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With the purpose of revolving the problem of photogrammetry without ground control points (GCPs) (referred to non-controlled positioning), a public DEM-assisted positioning method for Chinese satellite imagery without GCPs was proposed in the context of global mapping. To give full play to the characteristics of globally consistent, stable and high precision of public DEM, these data were regarded as reference data and matched with the DEM extracted from satellite imagery. Least Z-difference (LZD) method using least trimmed square (LTS) estimator was applied to match, and deformation between DEM is automatically detected and eliminated by analysis of the distribution of Z-difference. The correction parameters in object space which determined by DEM matching were applied to correct the direct positioning results. Multi-groups of comparative experiments for Mapping Satellite-1 and ZY-3 Satellite imagery were designed. Experimental results show that the proposed method is practical and feasible and has good robustness to gross error and deformation between surfaces, which can make full use of the advantages of the reference DEM. The positioning accuracy greatly depends on but not limited to the accuracy of public DEM and hardly affected by its resolution. Assisted by SRTM DEM, single imagery can realize high positioning accuracy without GCPs, which can meet the mapping standard of 1:50,000 scale. This method also provides a new and effective means for positioning accuracy inspection of satellite imagery.

A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation

LIU Chuang, QIAN Haizhong, WANG Xiao, HE Haiwei, CHEN Jingnan

2016, 45(11): 1371-1383. doi:10.11947/j.AGCS.2016.20160062

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Existing road network matching methods mostly use the characteristics of the road's own nodes and arcs to carry on the matching process, while less attention is focused on the importance of the road neighborhood elements in the road network matching, thus affecting further improvement of the matching efficiency and accuracy. In response to these problems, a linkage matching method for road network considering the similarity of upper and lower spatial relation is proposed. The linkage matching imitates the human thinking process of searching for target objects by the signal features and spatial correlation when reading maps, regarding matching as a reasoning process of goal feature searching and information association transmitting. Firstly, classify the complex road network by using Stroke technology. Secondly, establish the road network linkage matching model based on road skeleton relation tree. Finally, select the high-level road in the classifying results of the source data as the reference road to start matching, calculate the road between the upper and lower levels of the spatial relationship similarity, and through a step-by-step iteration, make the matching information transmit in the road network linkage matching model thus to obtain the final matching results. Experiment shows that the mentioned algorithm can narrow the search range of the data to be matched, effectively improving the match efficiency and accuracy, especially applicable to the data with large non systematic geometric location deviation.

Research on the Airborne Vector Gravimetry Based on Data from SINS and GNSS

WANG Zheng

2016, 45(11): 1384-1384. doi:10.11947/j.AGCS.2016.20160321

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