2013 Vol. 38, No. 9
With the development of space-borne GPS technologies and IGS precise orbit and clock products,precise orbit determination(POD) of Low Earth Orbiters(LEOs) based on PPP technology has become a hot issue.At present,an accuracy of 3～5 cm in Radial(R),Along-track(T),Cross-track(N) components can be achieved with conventional PPP.However,the results are less precise or reliable than the double-differenced fixed solution due to the ambiguity-float solution in traditional PPP.In order to further improve the precision and reliability of POD with PPP,daily observations from all IGS tracking stations through day 2 to 7 in 2012 were used to estimate the wide and narrow-lane fractional cycle bias(FCB) of all satellites for PPP integer ambiguity resolution.The POD of the two GRACE satellites were respectively compared with GFZ’s post precise orbit and K-band measurements for the analysis of the inner and external conformities.As compared to GFZ,the daily orbital accuracy of the ambiguity-fixed solution in this work is about 2～3 cm in R direction,better than 2 cm in T direction and better than 2 cm in N direction for GRACE-A,an improvement of 19%,30% and 50% respectively when compared with that of the float solution.The POD precision for GRACE-B are 2-3 cm,2 cm and 1-2 cm in R,N,T directions for the fixed solution,respectively.The accuracy improvement in the fixed solution for GARCE-B is nearly equivalent with that for GRACE-A.For K-band cases,the mean STD error of KBR residual is about 16.4 mm for the fixed solution,and 22.6 mm for the float solution.These results show that PPP with ambiguity-fixed can greatly improve POD precision of LEO satellites and provide more reliable orbital service.
This paper first proposes a method for the BeiDou orientation using single epoch single frequency ambiguity resolution with fixed baseline length and single epoch dual frequency ambiguity resolution based on LAMBDA algorithm.According to the results of multiple tests on BeiDou and GPS short baseline data,the BeiDou’s ambiguity resolution success rate and the precision of orientation are found to be in common with the GPS’s.
The characteristics of GPS Common View(GPS CV) and GPS Carrier Phase time transfer(GPS CP) methods are introduced,and a new continuous time and frequency transfer algorithm based on GPS single Different Carrier Phase observations is proposed.The new algorithm uses an ionosphere-free combination of single but different observations from the same satellite and the processing steps are also consistent with simple traditional GPS CP.But,the Bayesian estimation of prior information is proposed to smooth the day-boundaries of time transfer results.Simulation results,which compared to that of GPS CP method,show that the proposed new algorithm improves the precision and frequency stability of the time and frequency transfer results remarkably.
Based on code,carrier phase and their combination so called GRAPHIC observation,three types of observation model for Single-Frequency Precise Point Positioning(SF-PPP) were presented,named as :"C-G model" making use of Code and GRAPHIC observation,"G-P model" making use of GRAPHIC and Phase observation and "C-P model" making use of Code and Phase observation.We considered two approaches to eliminate ionospheric effect : first,to remove the ionospheric delay with ionospheric map data from the International GNSS Service(IGS) which is the most accurate ionospheric model;second,to estimate the ionospheric path delay parameter together with receiver position,clock offset and so on.SFPPP experiments were carried out with static GPS data collected at 15 stations of IGS through day 75 to 90 in 2011 and airborne GPS data collected on September 5th 2008.It’s shown that different models and ionospheric elimination approaches lead to different positioning accuracy.Among all the three models and two approaches,G-P model and C-P model with estimation of ionospheric path delay,produce the best result for both static and kinematic positioning.Just saying the first ionospheric elimination approach,C-G model enjoy the best result.Our work indicates that,by adopt suitable observation and ionospheric elimination approach,an accuracy of a few centimeters for static positioning and several delimiters for kinematic positioning is achievable with SFPPP.
The Chang’E-2 spacecraft was sent to the Lissajous orbit around the L2 of the Sun-Earth for an extended mission in June,2011.During that mission,the maximum distance between the satellite and the Earth was about 1 700 000 km.With an increase in the Earth-Satellite distance,the noise level in three-way ranging increases significantly on the one hand,and the constraint of flight dynamic decreases rapidly on the other hand.Moreover,the geometry for POD deteriorates,therefore the calculation for orbit determination also gets correspondingly more difficult during the process.These factors present challenges to the tracking system.In this paper,the POD for the Chang’E-2 extended mission is described in detail,and the accuracy is assessed using several methods.The results show that the degree of accuracy is better than 1km in the escape phase,and as the distance increases,the required arc-length for POD increases correspondingly.In the late phase of a transfer orbit,orbit determination calculation executed with 20 consecutive days’ data and and orbital comparison using overlaps and prediction analysis,show that the orbital error as a root mean square is at the level of 2 km.
The towing operation mode results in dislocation and distortion of SSS images,as well as creating difficulties for image mosaicing by coordinates,and target recognition and determination.Therefore,this paper proposes an image segmented mosaic method based on corresponding features on the seabed.Through preprocessing of side scan sonar image,segmented matching by mutual features,and image fusion in the public coverage area based on wavelet transformation,this method can correctly fuse adjacent SSS images,going a,long way toward solving the problem of dislocation and distortion found in the traditional methods for image mosaic.A test verifies the effectiveness of the proposed method.
The spherical harmonics transform is a method to improve the calculation speed of the earth’s gravity disturbsance on orbiting satellites.Based on the particularity of the trajectory for pole transformation,the Clenshaw sun method is introduced to calculate the gravity disturbance on the new coordinates.Then,a comparative analysis focuses on the calculation speed and physical space needs using three methods;the traditional,pole transform,and improved pole transform methods.A simulation using the three methods is used to calculate the gravity disturbance on one period of the orbit.Test results show that the improved pole transformation of spherical harmonic functions is 100 times the calculation speed of the traditional pole transformation method.Furthermore,the data storage capacity required by the new method is only three percent of the traditional method.
Angular resolution is the dominant factor for determining the extraction ability of a point cloud target.An angular resolution model is derived from average modulation transfer function(AMTF).The AMTF model is affected by sampling interval AMTFS、spot size AMTFb and quantization AMTFq.An accuracy assessment formula for sampling intervals and spot size was derived through an analysis of the error factor of sampling interval and spot size.The Linearization of AMTF model was based on the relationship among AMTF model、the sampling interval and spot size;The standard deviation of the cut-off frequency is derived according to the error propagation law;and an accuracy evaluation for angular resolution is achieved according to the relationship between cut-off frequency and angular resolution.
An improved numerical simulation method of Doppler Spectrum of sea echo for ground-based microwave wave radar is presented based on a study of scattering mechanism of microwave with ocean surface and some research results by W.J.Plant et al.According to the theories of Bragg scattering,composite surface,linear wave,and the expressions for NRCS of different polarization types,the characteristics of Doppler spectrum is displayed in shape,amplitude and time domain,and Doppler spectra of different ocean conditions are compared and qualitatively analyzed.Accordingly,it can be concluded that the simulation results reflect actual ocean environment and accord with objective law,which provides significant theoretical model for oceanographic observation by microwave wave radar and information extraction of sea state,especially parameters of wind,wave and current.
In this paper,we propose methods that combine with high time resolution MODIS images,high spatial resolution ETM+ images and classification data information based on the theory of down scaling in order to use multi-source remote sensing data effectively for fine remote sensing applications.Linear mixed model disaggregate mixed pixels in coarse resolution images.Therefore,when exploiting information within mixed pixels,each component fractional cover is derived from high spatial resolution classification maps.A model between the pixel reflection and class reflection simulates images with high spatial resolution and high time resolution characteristics.The calculated results of the correlation coefficient between the simulated image and the real image,the correlation coefficient between NDVI image produced by the simulate image and NDVI image produced by the real image showed a very high correspondence between them,validating the approach.
Considering the large amount of computation & low accuracy of extracted point-like features are the two main disadvantages of traditional point-to-point based registration methods which is designed for LiDAR point cloud,and the accuracy of registration results is seriously decreased by the linearization procedure of traditional 7-parameter based transformation approaches,a new registration approach is designed to overcome above disadvantages,which selects linear features as registration primitives,and uses quaternion to represent rotation matrix.Similarity measure of the linear-feature-constrained 3D transformation procedure is presented,and the formulation of registration procedure is exactly deduced.Besides,the detailed procedure of how to calculate rotation,translation & scale is also presented.Experiments show that the presented approach is efficient & effective.More importantly,by using quaternion to represent rotation matrix,the new presented approach avoids the decrease of accuracy,meanwhile,due to the characteristic of quaternion,it also needs few calculation resources compared to traditional registration methods.
A new automatic urban area extraction method from high-resolution remote-sensing imagery that exploits the unique local features of urban area is presented in this paper.The proposed algorithm contains the following steps: First,it obtains the filtering response images with Gabor filters grouped at various central frequencies and orientations;Secondly,we use the Ostu’s method to implement threshold segmentation,and then realize the logical and operation in the various orientations of every central frequency;Thirdly,we determine the optimal central frequency with the Gabor features distribution information;Finally,with the information above,we extract the urban area by forming the spatial voting matrix with the Gaussian function.Experimental results show that the approach is able to detect the urban areas in the high-resolution remote-sensing imagery.The results of a performance evaluation also support the high precision of this approach.
The extraction of impervious surfaces from satellite imagery has been a hot topic in the remote sensing field over the past decade.Nevertheless,whether the impervious surface information extracted from different sensor images is comparable is still unknown.This paper implemented a complementary study based on a comparison of the retrieved impervious surface information from Landsat ETM+ and EO-1 ALI sensor data.Impervious surface features were derived from a date-coincident image pair of the two sensors by using linear spectral mixture analysis(LSMA).The accuracy of retrieved impervious surface information of the two sensors was assessed and compared.The results show that the ALI image has higher accuracy than ETM+,as suggested by its higher overall accuracy and Kappa coefficient and lower root mean square error and systematic error(in absolute value).The differences in spectral resolution and radiometric resolution between the two sensors are believed to be the main factors causing these differences when retrieving impervious surfaces.An increase in spectral information in ALI sensor can be of help when distinguishing differences between land cover types,while the enhancement in radiometric resolution in the ALI sensor can make the sensor more sensitivite when detecting ground surface features.
Addressing the automatic recognition problem of a bridge above water in aerial images,an automatic recognition algorithm for a bridge above water in aerial image based on regional features is proposed.Firstly,aerial image binarization is executed based on the gradient mean square variance.The image noises are then removed based on pixel density.Next,the connective regions are labeled according to the pixels in binary image with a six neighborhood connection rule to obtain the water regional feature.Finally,the bridge is extracted.Experiments show this algorithm is effective for automatic recognition of a bridge above water in low-contrast aerial images taken at low altitudes.
The paper discusses a new pan-concept-level generation method based onthe cloud model.A new method of remote sensing image classification based on a improved pan-concept-level generation method is proposed.Classification experiments are used to compare the proposed method with traditional methods.Comparative experiments validate the proposed method.
Image matching is one of the most important and challenging areas in computer vision and remote sensing.Especially for the wide base line images with large distortions,the accuracy and reliability of the matching is a bottleneck in the auto-disposition given the large volume of images.Based on an analysis of the latest refining methods,the Reverse Positioning Refining Algorithm in Matching(REPRAM) composed of REPRAM Excluding and the REPRAM Including parts is proposed.The theory and properties are discussed in relation to the refining ability for excluding more bads and including more rights,where the mutual impact is separated.Thus,there is no need for extrinsic and intrinsic parameters of the camera or control points.Although the original reliability of the rough couples is about 30 percent,the algorithm works robustly with a high degree of reliability above 99.5 percents under the ranging error threshold for several kinds of remote sensing images as well as for close shot pictures.
A new algorithm based on a multiplicative weighted Voronoi diagram(MWVD) was proposed in this paper.The idea of the algorithm is to: select appropriate factors for describing the statistical,thematic,topological and metric information,and integrate the factors in the process of point feature generalization to ensure different types of information may be transmitted correctly,and the generalization of point clusters is done by repetitively constructing MWVDs.
To solve the problem of 3D real-time visual design for roads,a method based on road template was realized based on lateral and lengthwise structures and the geographic environment of the road.Combining real-time interactive data and the template,the method dynamically creates a 3D road model adapted to the terrain and complying with road engineering and technical standards mutually.An application built on the Gaea Explorer,a 3D-GIS platform demonstrates the feasibility of the proposed method.
Spatial,temporal and attributive characters are the three basic characters of spatial entities.Temporal attributes change over time.Research and Modeling on temporal attributes’ temporal semantics are important in spatiotemporal data modeling field.In this paper,in the form of algebraic relation,an attributive function is proposed,based on which,the temporal semantics of independent variable,domain of definition,function’s relation and function’s value are analyzed,and the algebraic descriptions,definitions and classifications of them are presented.At last,a classification with 20 types of temporal attributes are motivated which is able to offer advanced support for data modeling on temporal attributes,research on operation and query language,and presentation techniques in temporal geographical information system(TGIS).
The classical TOPSIS methods have their limitations when they are applied to spatial information.First,they lack methods for an ideal solution for decision-making attributes in spatial information.Second,they do not provide the utility degree for decision-making attributes.To solve these two problems,TOPSIS is extended by introducing interval analysis,and hence the E-TOPSIS-based algorithm for delivery decision-making is proposed.Experiments indicate that the E-TOPSIS-based algorithm is quite competent with intelligent spatial information delivery decision-making.
Aiming at the serious water pollution accidents happened in China,combined with pre-established 1D system dynamics water quality models and integration of GIS with system dynamics(SD),a realspace system of spatial-temporal simulation and dynamic regulation of water quality in water pollution accidents is developed;The Songhua River water pollution accident which happened on November,2005 was taken as example to make validation of simulation results and visual dynamic regulation.Dynamic simulation and trend forecast of pollutants transport and transformation is made in spatial and temporal dimension.The simulation,forecast of water quality and model regulation based on different emergency response strategies in water pollution accident is realized.
This paper puts forward a geometry matching method for transportation road network data based on projection.Characteristic points can be extracted from lines by projection and segmentation,so complex matching of road networks is converted into a characteristic point matching problem.An incremental matching strategy was designed,that narrows the range of matching and improves matching efficiency.A proper matching threshold can not only reduce leakage match and mismatch but also improves matching accuracy.Experimental results show that this method can obtain ahigher correct matching rate that meets application requirements.
The analysis of multi-scale land-use change and the driving force factors behind it has become an important direction for research In this study,a wavelet analysis tool was applied to analyze the multi-scale correlation between land-use change and economic factors based on characteristic scale analysis.The results showed that,in the study area,the scale of 64m was regarded as the characteristic scale and optimal to identify land-use heterogeneity.Wavelet variance revealed local information but failed to describe the general spatial pattern of land-use at a finer scale,and shapely raised for combination of information along with the upscaling.The results indicated that correlation between land-use change and economic factors was scale-dependent: the correlation coefficient values were smaller at a finer scale and reached the extreme at the characteristic scale.However,at a coarser scale,the correlation coefficient values of most economic factors became flat.This analysis suggests that economic factors effecting land-use change are macro constraints,and at the same time,shows the effectiveness of characteristic scale analysis.The coefficients among different factors are also different,under high-frequency wavelet coefficients there was strong positive correlation between population and land-use change at each scale,but a weak negative correlation in Per Capita income of rural households,suggesting that population was the most influential factor in land-use change.This study shows that wavelet analysis is a powerful tool for multi-scale correlation analysis,and can effectively reveal the multi-scale spatial patterns in land-use change.
Scenario simulation of land-use and land-cover change is gaining importance in global change research and for sustainable use of land resources.Most of the existing research has focused on simulating and identifying the possible land use allocation in the future.How to represent historic land use change under different scenarios is an issue for assessing the relative effect of implemented policies.An innovative counterfactual simulation model was proposed for assessing the effects of China’s farmland protection policies on food security and urban sprawl.The CLUE-s model and GM(1,1) approach were combined to forecast land use changes and simulate their spatial locations in a study area.Jiayu County was taken as an example to test the validity of the proposed model.The results showed that farmland protection policies played an effective role in reducing the rate of cultivated land loss,restricting the expansion of disorderly construction and optimizing the spatial distribution of land-use allocations in Jiayu County.
A normalized foreground computing approach based on the camera perspective effect is presented.A two-dimensional probability density for the binary foreground is calculated through classic joint probability distribution theory,and then the two-dimension joint entropy is calculated.Finally,a novel model based on normalized foreground and two-dimension joint entropy for detecting pedestrian gathering is proposed.Experimental results show that this model can quickly and effectively detect a pedestrian gathering event in a surveillance scene.
In order to improve the concurrent access performance with large-scale vector data in WebGIS,a content grid load balancing algorithm is proposed.The server processing capability,service contents,and request time are taken into account.A proposed method to divide large-scale vector data into a content grid,the algorithm of content automatic identification,analysis,aggregation and feedback in the server cluster concurrent environment is discussed.This algorithm implements all servers in the cluster to complete visualization tasks submitted by clients at the same time and realizes task-oriented load balancing.For the extraction and display of large-scale and high-intensity vector data,the algorithm balances the servers’ load efficiently and responds to requests in minimal time.As compared to t traditional load balancing algorithms,the algorithm proposed in this paper has the best performance.The larger the scale,the more obvious is the load balancing effect.