
Jianguo WangYork University · Department of Earth and Space Science and Engineering (Faculty of Science and Engineering)
Jianguo Wang
Bachelor & Master in Surveying Engineering, Dr.-Ing. of Engineering Sciences
Editor-In-Chief of Journal of Global Positioning Systems
https://www.cpgps.org/portal.php?mod=topic&topicid=15
About
61
Publications
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Introduction
Multisensor Integrated Kinematic Positioning and Navigation (outdoor/indoor)-GNSS receivers/IMUs/Cameras/LiDAR/Indoor beacons; Comprehensive Error Analysis in Discrete Kalman filter, direct-Georeferencing Technology
Additional affiliations
September 1999 - June 2006
Applanix Corp - A Trimble company
Position
- Researcher
December 1998 - August 1999
Geomodeling
Position
- Developer
October 1991 - September 1992
Education
September 1993 - February 1997
September 1984 - July 1987
Wuhan Technical University of Surveying & Mapping
Field of study
- Surveying Engineering
February 1978 - February 1982
Wuhan Technical University of Surveying & Mapping
Field of study
- Surveying Engineering
Publications
Publications (61)
This research proposes a novel modeling method for integrating IMU arrays into multi-sensor kinematic positioning/navigation systems. This method characterizes sensor errors (biases/scale factor errors) for each IMU in an IMU array, leveraging the novel Generic Multisensor Integration Strategy (GMIS) and the framework for comprehensive error analys...
This study aims to exploit multisource remotely sensed data to improve land cover classification of an area dominated by extensive wetlands with surface cover complexity strongly shaped by permafrost, fine-scale geomorphological and topographic characteristics. Accurate and precise mapping tools are critically needed to track change in wetland ecos...
Improving the accuracy of Terrestrial Mobile LiDAR (TML) data has been a challenge in Engineering Surveys. This research aims at how to innovatively enhance the accuracy of TML solutions through post-processing toward meeting high accuracy specifications in Engineering Surveys. Three techniques are described and implemented. Firstly, the linear fea...
This research aims at further completing our novel Generic Multisensor Integration Strategy (GMIS) with the systematic development of three alternate attitude models, i.e., roll-pitch-heading (RPH), direction cosine matrix (DCM), and quaternion. The
GMIS’ potential for a true sensor level data fusion is leveraged to its full extent here by facilita...
This manuscript establishes a generic framework for comprehensive error analysis in discrete Kalman filtering with constraints, which systematically provides a complete set of algorithmic formulas along with demonstrating an alternative process of theoretical analytics of discrete Kalman filter. This constructive work aims extensively to standardiz...
Designed to be a standard textbook for undergraduates studying surveying engineering, geomatics engineering or geospatial engineering and technology, the textbook also serves a reference for scientific and engineering professionals such as surveyors, engineers, scientists and technicians in the relevant disciplines.
Phase Unwrapping for Synthetic Aperture RADAR Interferometry (InSAR) remains a challenge due to the speckle noise and temporal decorrelation present in many interferograms. This paper proposes a Polynomial-Based Region-Growing Phase Unwrapping (PBRGPU) approach that builds from the Region-Growing Phase Unwrapping (RGPU) approach developed by Xu and...
This manuscript attempts to systematically outline the theoretical concepts and practical implementation of comprehensive error analysis in Kalman filtering. They are four essential aspects: model formulation vs. the error sources, the redundancy contribution for the predicted state vector, process noise vector and measurement vector, posteriori qu...
In this study, multispectral Light Detection and Ranging (LiDAR) data were utilized to improve delineation of individual tree crowns (ITC) as an important step in individual tree analysis. A framework to integrate spectral and height information for ITC delineation was proposed, and the multi-scale algorithm for treetop detection developed in one o...
With the advance of deep learning networks, their applications in the assessment of pavement conditions are gaining more attention. A convolutional neural network (CNN) is the most commonly used network in image classification. In terms of pavement assessment, most existing CNNs are designed to only distinguish between cracks and non-cracks. Few ne...
本书是《误差理论与测量平差基础》的英译本,根据信息化测绘背景下测量基础处理课程改革中的教学研究和教学实践,结合近年来在误差理论和测量数据处理方法的最新研究成果,在第二版的基础上进行总体架构完备并完善内容。
http://www.wdp.com.cn/book/toBookInfoDetailPage.action?id=9620&flag=1
Since the introduction of the Asian Emerald Ash Borer beetle (EAB, Agrilus planipennis) to Southern Ontario in 2002, all species of ash trees (Fraxinus) in the province are currently at risk. Due to the aggressive nature of this beetle, early detection is critical in its eradication and can be facilitated by species distribution modelling. That sai...
Conventionally, the Kalman filter on the basis of integration mechanization, such as GPS-aided inertial integrated navigation system, has been commonly built up using error states and error measurements. In order to accurately reflect the evolution of the real state for a moving vehicle, we adopted an unconventional KF that directly estimated navig...
The Athenians Project deals with the digitization of the epigraphical (writings on stone, pottery and metals), prosopographical (biographical data on the residents of ancient Athens) and topographical (locations on maps of Athens and Attica) information. The project is primarily admired by classicists around the world for its relational database of...
Although the Kalman filter (KF) is widely used in practice, its estimated results are optimal only when the system model is linear and the noise characteristics of the system are already exactly known. However, it is extremely difficult to satisfy such requirement since the uncertainty caused by the inertial instrument and the external environment,...
In this study, full-waveform LiDAR data were exploited to detect weak returns backscattered by the bare terrain underneath vegetation canopies and thus improve the generation of a digital terrain model (DTM). Building on the methods of progressive generation of triangulation irregular network (TIN) model reported in the literature, we proposed an i...
Although Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS) integrated navigation system has been widely used in modern kinematic positioning and navigation due to its numerous advantages, the GNSS signal is easily disturbed or blocked by the surroundings, which will reduce the system accuracy significantly. S...
Improving a priori stochastic models of the process and measurement noise vectors in Kalman Filer (KF) has always been a challenge. As one preferable technique to address this challenge, the variance component estimation (VCE) applied on the Kalman Filter’s process and measurement noise covariance matrix (Q & R) has been proved in plenty of applica...
This paper presents a novel two-step camera calibration method in a GPS/INS/Stereo Camera multi-sensor kinematic positioning and navigation system. A camera auto-calibration is first performed to obtain for lens distortion parameters, up-to-scale baseline length and the relative orientation between the stereo cameras. Then, the system calibration i...
Unlike Mobile Airborne LiDAR (MAL), it has become common for Mobile Terrestrial LiDAR (MTL) sys tems to consist of two or more LiDAR sensors. It is a challenging task for a user to simultaneously verify and calibrate their lever arms and boresight angles with respect to the IMU using the kinematic data. This paper presents a novel method for determ...
In large-area LiDAR mapping projects, surveyors might collect data at different times and with different sensors, creating loosely connected laser point clouds with varying point densities, accuracies, and overlaps. Current LiDAR calibration methodologies refine each point cloud and evaluate the accuracy of each point cloud individually. In the cas...
The conventional integration mechanism in GNSS (Global Navigation Satellite Systems) aided inertial integrated positioning and navigation system is mainly based on the continuous outputs of the navigation mechanization, the associated error models for navigation parameters, the biases of the inertial measurement units (IMU), and the error measureme...
Conventionally, all of the sensors, except the IMUs, function as aiding sensors in the multisensor integrated kinematic positioning and navigation. In this way, the IMU measurements are only used in free inertial navigation calculation, not through measurement update in Kalman filter (KF) between two adjacent aiding measurement epochs. This paper s...
This paper presents a novel stereo image-based image aided inertial navigation algorithm for reducing position and orientation drifts during GNSS outages or in a poor GNSS environment. Usually, the image aided navigation based on the visual odometry uses the tracked features only from a pair of the consecutive image frames. The proposed method inte...
The errors of inertial sensors affect the navigation accuracy of the strapdown inertial navigation system (SINS) and are accumulated over time in nature. In order to continuously maintain the high navigation accuracy of vehicles for a long time period, an initial alignment and self-calibration is necessary after the SINS starts. Additionally, the o...
Structural Equation Modeling (SEM) is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions. It can be considered as an extended statistical hypotheses testing with pre-defined structural model. However, when the SEM is applied as an exploratory technique in da...
This paper proposes an innovative way to simultaneously estimate the variance matrix R of the measurement vector and the variance matrix Q of the process noise vector based on the variance-covariance component estimation by taking the advantages of the measurement residuals and the process noise residuals (Wang, 1997, 2009; Wang et al, 2009) and th...
The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an...
An image-aided inertial navigation implies that the errors of an inertial navigator are estimated via the Kalman filter using the aiding
measurements derived from images. The standard Kalman filter runs under the assumption that the process noise vector and
measurement noise vector are white, i.e. independent and normally distributed with zero mean...
The understanding of the effects of error on Mobile Terrestrial LiDAR (MTL) point clouds has not increased with their popularity. In this study, comprehensive error analyses based on error propagation theory and global sensitivity study were carried out to quantitatively describe the effects of various error sources in a MTL system on the point clo...
A critical step in object-oriented geospatial analysis (OBIA) is image segmentation. Segments determined from a lower-spatial resolution image can be used as the context to analyse a corresponding image at a higher-spatial resolution. Due to inherent differences in perceptions of a scene at different spatial resolutions and co-registration, segment...
Over the past decade, network RTK technology has become popular as an efficient method of precise, real-time positioning. Its relatively low-cost and single receiver ease-of-use has allowed it to mostly replace static relative GPS and single baseline RTK in urban areas where such networks are economically viable (e.g., cadastral and construction su...
The integrated navigation system with strapdown inertial navigation system (SINS), Beidou (BD) receiver and Doppler velocity log (DVL) can be used in marine applications owing to the fact that the redundant and complementary information from different sensors can markedly improve the system accuracy. However, the existence of multisensor asynchrony...
Despite its popularity, the development of an embedded real-time multisensor kinematic positioning and navigation system discourages many researchers and developers due to its complicated hardware environment setup and time consuming device driver development. To address these issues, this paper proposed a multisensor kinematic positioning and navi...
In this study, full waveform LiDAR data were exploited to improve the generation of a large-scale digital elevation model (DEM). Building on the methods of progressive generation of triangulation irregular network (TIN) model reported in the literature, we proposed an integrated approach. In this method, echo detection, terrain identification, and...
Automated calibration of LIDAR systems has been an active field of research and development over the last years. Traditional calibration approaches rely on manual extraction of geometric features in the laser data and require time-intensive input of a trained operator. Recently, new methodologies evolved using automatic extraction of linear feature...
Terrestrial LiDAR provides many disciplines with an effective and efficient means of producing realistic three-dimensional models of real world objects. With the advent of mobile terrestrial LiDAR, this ability has been expanded to include the rapid collection of three-dimensional models of large urban scenes. For all its usefulness, it does have d...
It has become a trend to replace the traditional single baseline RTK approach by using network RTK services, whilst there is still lack of authoritative guidelines and specifications with this most recent development of GNSS positioning. For this purpose, the Ministry of Transportation of Ontario (MTO), Canada is interested in the performance, as w...
There are different ways to construct adaptive Kalman filtering (AKF) algorithms. This paper proposes an
innovative way to simultaneously estimate the variance matrix R of the measurement vector and the variance
matrix Q of the process noise vector based on the variance-covariance component estimation by taking the
advantages of the measurement res...
This paper focuses on realization of the variance and covariance component estimation in static relative
GPS positioning for the double-differenced measurements in sequential least squares. The algorithm presented is based on the algorithm from [Ou, 1989] through the incorporation into the sequential least-squares (Wang et al, 2009; etc.). It is pr...
In this study, a new algorithm was developed to effectively use multi-angular hyperspectral remote sensing data in the retrieval of vegetation parameters based on a coupled leaf and canopy reflectance model. Since the observations acquired at different viewing angles tend to have different noise levels, the posterior variance factors of the observa...
This manuscript centers on the reliability theory and its applications in Kalman filtering. Especially, it delivers a distinct derivation of the redundancy contribution -the key element of reliability theory for the Kalman filter algorithm that has not been comprehensively discussed in literature at present. A distinction is made between the system...
This paper adapts Helmert's simplified variance component estimation (VCE) algorithm for static and kinematic GPS single point positioning (SPP). First, the VCE algorithm for a static GPS SPP is formulated. Second, the concept of redundancy contribution of observations is developed in Kalman filtering so that the VCE algorithm is further delivered...
The Geomatics Engineering program at York University, established in 2001, is one of four, four-year undergraduate geomatics engineering programs in Canada. The program was established to provide novel engineering studies and to address the increasing need for geomatics engineering education in Ontario. In this paper, we share the experiences gaine...
Dam deformation analysis is one of the most essential components in dam safety monitoring and management. Dynamic models of dam deformation analysis generally include both parametric and non-parametric models. In China, a large amount of research effort in data analysis has been directed toward the evelopment of new non-parametric models such as St...
One of the key requirements for Kalman filtering is to characterize various error sources, essentially for the quality assurance and quality control of a system. This characterization can be evaluated by applying the principle of multivariate statistics to the system innovations and the measurement residuals. This manuscript will systematically exa...
Main problem in data analysis is a construction of mathematical models relating environmental variables and patterns of deformation. In case of the dam environmental variables are temperature, water level in a reservoir, etc. The most commonly used method of data analysis is statistical modelling of the data. The partial least-squares regression (P...
In this work the quality control of the Kalman filter is extended. At first the equations to compute the redundancy contributions of the observations in the Kalman filter are derived from the concept of reliability. By use of these redundancy contributions, the reliability and the accuracy of a kinematic survey system could be studied. Further, the...
Der Entwicklungsstand moderner Positionierungstechniken mit GPS, INS und weiteren Verfahren ermöglicht es heute, eine fahrzeuggebundene kinematische Vermessung von Landverkehrswegen mit hoher Genauigkeit durchzuführen. Dazu ist aber die Entwicklung geeigneter Auswertemethoden erforderlich.
Vor diesem Hintergrund befaßt sich die vorliegende Arbeit...
Der Entwicklungsstand moderner Positionierungstechniken mit GPS, INS und weiteren Verfahren ermöglicht es heute, eine fahrzeuggebundene kinematische Vermessung von Landverkehrswegen mit hoher Genauigkeit durchzuführen. Dazu ist aber die Entwicklung geeigneter Auswertemethoden erforderlich.
Vor diesem Hintergrund befaßt sich die vorliegende Arbeit...
In this paper, the consistence between PCA method and distorting method of mathematical model in the study of survey networks is researched. As a practical example, the simulating experiments of an accelerator ring-shaped network are made. The results show that both methods are consistent under some conditions. It is not only reveals the reason for...
This paper sets forth the theory which is used for analysing the effects of observed elements in network, and gives four indexes corresponding with it. The relation between the effects of observed elements and the configuration of network is discussed, also the relation between the effects and accuracy matching of observed elements. Meanwhile, the...
Dam deformation analysis is an important part of da m safety monitoring. Generally dynamic models of dam deformation analysis include: parametric models and non-parametric models. In China, large amount of research activiti es in data analysis is in developing new non-parametric models such as stepwise regression ( SR), partial least-squares (PLS)...