Intelligent Urban Positioning: Integration of Shadow Matching with 3D-Mapping-Aided GNSS Ranging

In dense urban areas, conventional Global Navigation Satellite Systems (GNSS) positioning can exhibit errors of tens of metres due to the obstruction and reflection of the signals by the surrounding buildings. By using Three-Dimensional (3D) mapping of the buildings, the accuracy can be significantly improved. This paper demonstrates the first integration of GNSS shadow matching with 3D-mapping-aided GNSS ranging. The integration is performed in the position domain, whereby separate ranging and shadow matching position solutions are computed, then combined using direction-dependent weighting. Two weighting strategies are compared, one based on the computation of ranging-based and shadow matching position error covariance matrices, and a deterministic approach based on the street azimuth. Using experimental data collected from a u-blox GNSS receiver, it is shown that both integrated position solutions are significantly more accurate than either shadow matching or 3D-mapping-aided ranging on their own. The overall Root Mean Square (RMS) horizontal accuracy obtained using covariance-based weighting was 6·1 m, a factor of four improvement on the 25·9 m obtained using conventional GNSS positioning. Results are also presented using smartphone data, where shadow matching is integrated with conventional GNSS positioning.

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Adjustment of an Integrated Geodetic Network Composed of GNSS Vectors and Classical Terrestrial Linear Pseudo-Observations

Applied Sciences ◽

10.3390/app11104352 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4352

Author(s):

Tadeusz Gargula

Keyword(s):

Three Dimensional ◽

Geodetic Network ◽

Global Navigation Satellite Systems ◽

Adjustment Process ◽

Dimensional System ◽

Integrated Network ◽

Satellite Systems ◽

Linear Distance ◽

Easy Integration ◽

Global Navigation Satellite

The paper proposes a new method for adjusting classical terrestrial observations (total station) together with satellite (GNSS-Global Navigation Satellite Systems) vectors. All the observations are adjusted in a single common three-dimensional system of reference. The proposed method does not require the observations to be projected onto an ellipsoid or converted between reference systems. The adjustment process follows the transformation of a classical geodetic network (distances and horizontal and vertical angles) into a spatial linear (distance) network. This step facilitates easy integration with GNSS vectors when results are numerically processed. The paper offers detailed formulas for calculating pseudo-observations (spatial distances) from input terrestrial observations (horizontal and vertical angles, horizontal distances, height of instrument and height of target). The next stage was to set observation equations and transform them into a linear form (functional adjustment model of geodetic observations). A method was provided as well for determining the mean errors of the pseudo-observations, necessary to assess the accuracy of the values following the adjustment (point coordinates). The proposed algorithm was verified in practice whereby an integrated network made up of a GNSS vector network and a classical linear-angular network was adjusted.

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Filtering Link Outliers in Vehicle Trajectories by Spatial Reasoning

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10050333 ◽

2021 ◽

Vol 10 (5) ◽

pp. 333

Author(s):

Junli Liu ◽

Miaomiao Pan ◽

Xianfeng Song ◽

Jing Wang ◽

Kemin Zhu ◽

...

Keyword(s):

Urban Areas ◽

Spatial Reasoning ◽

Sampling Interval ◽

Global Navigation Satellite Systems ◽

Quality Analysis ◽

Ancillary Data ◽

Satellite Systems ◽

Positioning Errors ◽

Vehicle Trajectories ◽

Global Navigation Satellite

Vehicle trajectories derived from Global Navigation Satellite Systems (GNSS) are used in various traffic applications based on trajectory quality analysis for the development of successful traffic models. A trajectory consists of points and links that are connected, where both the points and links are subject to positioning errors in the GNSS. Existing trajectory filters focus on point outliers, but neglect link outliers on tracks caused by a long sampling interval. In this study, four categories of link outliers are defined, i.e., radial, drift, clustered, and shortcut; current available algorithms are applied to filter apparent point outliers for the first three categories, and a novel filtering approach is proposed for link outliers of the fourth category in urban areas using spatial reasoning rules without ancillary data. The proposed approach first measures specific geometric properties of links from trajectory databases and then evaluates the similarities of geometric measures among the links, following a set of spatial reasoning rules to determine link outliers. We tested this approach using taxi trajectory datasets for Beijing with a built-in sampling interval of 50 to 65 s. The results show that clustered links (27.14%) account for the majority of link outliers, followed by shortcut (6.53%), radial (3.91%), and drift (0.62%) outliers.

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Integrity and Collaboration in Dynamic Sensor Networks

Sensors ◽

10.3390/s18072400 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2400 ◽

Cited By ~ 7

Author(s):

Steffen Schön ◽

Claus Brenner ◽

Hamza Alkhatib ◽

Max Coenen ◽

Hani Dbouk ◽

...

Keyword(s):

Sensor Networks ◽

Urban Areas ◽

Research Training ◽

Training Group ◽

Autonomous Driving ◽

Global Navigation Satellite Systems ◽

Satellite Systems ◽

Global Navigation Satellite ◽

Map Data ◽

Dynamic Sensor Networks

Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.

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Robust Statistics for GNSS Positioning under Harsh Conditions: A Useful Tool?

Sensors ◽

10.3390/s19245402 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5402 ◽

Cited By ~ 6

Author(s):

Daniel Medina ◽

Haoqing Li ◽

Jordi Vilà-Valls ◽

Pau Closas

Keyword(s):

Robust Regression ◽

Robust Statistics ◽

Single Point ◽

Global Navigation Satellite Systems ◽

Noise Model ◽

Satellite Systems ◽

Gnss Positioning ◽

Global Navigation Satellite ◽

Harsh Conditions ◽

Real World Problems

Navigation problems are generally solved applying least-squares (LS) adjustments. Techniques based on LS can be shown to perform optimally when the system noise is Gaussian distributed and the parametric model is accurately known. Unfortunately, real world problems usually contain unexpectedly large errors, so-called outliers, that violate the noise model assumption, leading to a spoiled solution estimation. In this work, the framework of robust statistics is explored to provide robust solutions to the global navigation satellite systems (GNSS) single point positioning (SPP) problem. Considering that GNSS observables may be contaminated by erroneous measurements, we survey the most popular approaches for robust regression (M-, S-, and MM-estimators) and how they can be adapted into a general methodology for robust GNSS positioning. We provide both theoretical insights and validation over experimental datasets, which serves in discussing the robust methods in detail.

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Robust Estimators in Geodetic Networks Based on a New Metaheuristic: Independent Vortices Search

Sensors ◽

10.3390/s19204535 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4535 ◽

Cited By ~ 1

Author(s):

Ismael Érique Koch ◽

Ivandro Klein ◽

Luiz Gonzaga ◽

Marcelo Tomio Matsuoka ◽

Vinicius Francisco Rofatto ◽

...

Keyword(s):

Large Scale ◽

Three Dimensional ◽

Search Space ◽

Global Navigation Satellite Systems ◽

Robust Estimator ◽

Satellite Systems ◽

Original Algorithm ◽

Geodetic Networks ◽

Global Navigation Satellite ◽

Better Than

Geodetic networks provide accurate three-dimensional control points for mapping activities, geoinformation, and infrastructure works. Accurate computation and adjustment are necessary, as all data collection is vulnerable to outliers. Applying a Least Squares (LS) process can lead to inaccuracy over many points in such conditions. Robust Estimator (RE) methods are less sensitive to outliers and provide an alternative to conventional LS. To solve the RE functions, we propose a new metaheuristic (MH), based on the Vortex Search (IVS) algorithm, along with a novel search space definition scheme. Numerous scenarios for a Global Navigation Satellite Systems (GNSS)-based network are generated to compare and analyze the behavior of several known REs. A classic iterative RE and an LS process are also tested for comparison. We analyze the median and trim position of several estimators, in order to verify their impact on the estimates. The tests show that IVS performs better than the original algorithm; therefore, we adopted it in all subsequent RE computations. Regarding network adjustments, outcomes in the parameter estimation show that REs achieve better results in large-scale outliers’ scenarios. For detection, both LS and REs identify most outliers in schemes with large outliers.

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Theoretical Upper Bound and Lower Bound for Integer Aperture Estimation Fail-Rate and Practical Implications

Journal of Navigation ◽

10.1017/s0373463312000513 ◽

2012 ◽

Vol 66 (3) ◽

pp. 321-333 ◽

Cited By ~ 4

Author(s):

Tao Li ◽

Jinling Wang

Keyword(s):

Lower Bound ◽

Upper Bound ◽

Global Navigation Satellite Systems ◽

Integer Ambiguity ◽

Satellite Systems ◽

Gnss Positioning ◽

Integer Aperture Estimation ◽

Ambiguity Validation ◽

Global Navigation Satellite ◽

Practical Implications

Integer ambiguity validation is pivotal in precise positioning with Global Navigation Satellite Systems (GNSS). Recent research has shown traditionally used ambiguity validation methods can be classified as members of the Integer Aperture (IA) estimators, and by the virtue of the IA estimation, a user controllable IA fail-rate is preferred. However, an appropriately chosen fail-rate is essential for ambiguity validation. In this paper, the upper bound and the lower bound for the IA fail-rate, which are extremely useful even at the designing stage of a GNSS positioning system, have been analysed, and numerical results imply that a meaningful IA fail-rate should be within this range.

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Precise Point Positioning using Multi-Constellation GNSS Observations for Kinematic Applications

Journal of Applied Geodesy ◽

10.1515/jag-2014-0021 ◽

2015 ◽

Vol 9 (1) ◽

Cited By ~ 12

Author(s):

Mahmoud Abd Rabbou ◽

Ahmed El-Rabbany

Keyword(s):

Urban Areas ◽

Precise Point Positioning ◽

Global Navigation Satellite Systems ◽

Test Scenario ◽

Satellite Systems ◽

Satellite Geometry ◽

Point Positioning ◽

Kinematic Ppp ◽

Gnss Measurements ◽

Global Navigation Satellite

AbstractTraditional precise point positioning (PPP) is commonly based on un-differenced ionosphere-free linear combination of Global Positioning System (GPS) observations. Unfortunately, for kinematic applications, GPS often experiences poor satellite visibility or weak satellite geometry in urban areas. To overcome this limitation, we developed a PPP model, which combines the observations of three global navigation satellite systems (GNSS), namely GPS, GLONASS and Galileo. Both un-differenced and between-satellite single-difference (BSSD) ionosphere-free linear combinations of pseudorange and carrier phase GNSS measurements are processed. The performance of the combined GNSS PPP solution is compared with the GPS-only PPP solution using a real test scenario in downtown Kingston, Ontario. Inter-system biases between GPS and the other two systems are also studied and obtained as a byproduct of the PPP solution. It is shown that the addition of GLONASS observations improves the kinematic PPP solution accuracy in comparison with that of GPS-only solution. However, the contribution of adding Galileo observations is not significant due to the limited number of Galileo satellites launched up to date. In addition, BSSD solution is found to be superior to that of traditional un-differenced model.

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FULLY AUTOMATIC FEATURE-BASED REGISTRATION OF MOBILE MAPPING AND AERIAL NADIR IMAGES FOR ENABLING THE ADJUSTMENT OF MOBILE PLATFORM LOCATIONS IN GNSS-DENIED URBAN ENVIRONMENTS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-w1-317-2017 ◽

2017 ◽

Vol XLII-1/W1 ◽

pp. 317-323 ◽

Cited By ~ 2

Author(s):

P. Jende ◽

F. Nex ◽

M. Gerke ◽

G. Vosselman

Keyword(s):

Urban Areas ◽

Urban Environments ◽

Global Navigation Satellite Systems ◽

Aerial Images ◽

Mobile Mapping ◽

High Resolution Data ◽

Satellite Systems ◽

Correct Orientation ◽

Fully Automatic ◽

Global Navigation Satellite

Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM’s georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform’s localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95&thinsp;%.

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A Computation Effective Range-Based 3D Mapping Aided GNSS with NLOS Correction Method

Journal of Navigation ◽

10.1017/s037346332000003x ◽

2020 ◽

Vol 73 (6) ◽

pp. 1202-1222 ◽

Cited By ~ 2

Author(s):

Hoi-Fung Ng ◽

Guohao Zhang ◽

Li-Ta Hsu

Keyword(s):

Ray Tracing ◽

Urban Areas ◽

Low Cost ◽

Three Dimensional ◽

Correction Method ◽

Satellite System ◽

Urban Environments ◽

3D Mapping ◽

Gnss Positioning ◽

Positioning Method

Global navigation satellite system (GNSS) positioning in dense urban areas remains a challenge due to the signal reflection by buildings, namely multipath and non-line-of-sight (NLOS) reception. These effects degrade the performance of low-cost GNSS receivers such as in those smartphones. An effective three-dimensional (3D) mapping aided GNSS positioning method is proposed to correct the NLOS error. Instead of applying ray-tracing simulation, the signal reflection points are detected based on a skyplot with the surrounding building boundaries. The measurements of the direct and reflected signals can thus be simulated and further used to determine the user's position based on the measurement likelihood between real measurements. Verified with real experiments, the proposed algorithm is able to reduce the computational load greatly while maintaining a positioning accuracy within 10 metres of error in dense urban environments, compared with the conventional method of ray-tracing based NLOS corrected positioning.

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Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment

Robotics ◽

10.3390/robotics9030066 ◽

2020 ◽

Vol 9 (3) ◽

pp. 66

Author(s):

Oguz Kagan Isik ◽

Juhyeon Hong ◽

Ivan Petrunin ◽

Antonios Tsourdos

Keyword(s):

Urban Environment ◽

Urban Areas ◽

Environmental Parameters ◽

Urban Environments ◽

Rate Of Change ◽

Global Navigation Satellite Systems ◽

Integrity Monitoring ◽

Satellite Systems ◽

Joint Consideration ◽

Global Navigation Satellite

The increasing use of Unmanned Aerial Vehicles (UAVs) in safety-critical missions in both civilian and military areas demands accurate and reliable navigation, where one of the key sources of navigation information is presented by Global Navigation Satellite Systems (GNSS). In challenging conditions, for example, in urban areas, the accuracy of GNSS-based navigation may degrade significantly due to user-satellite geometry and obscuration issues without being noticed by the user. Therefore, considering the essentially dynamic rate of change in this type of environment, integrity monitoring is of critical importance for understanding the level of trust we have in positioning and timing data. In this paper, the dilution of precision (DOP) coefficients under nominal and challenging conditions were investigated for the purpose of integrity monitoring in urban environments. By analyzing positioning information in a simulated urban environment using a software-based GNSS receiver, the integrity monitoring approach based on joint consideration of GNSS observables and environmental parameters has been proposed. It was shown that DOP coefficients, when considered together with a number of visible satellites and cut-off elevations specific to the urban environment carry valuable integrity information that is difficult to get using existing integrity monitoring approaches. This has allowed generating indirect integrity measures based on cut-off elevation and satellite visibility that can be used for UAV path planning and guidance in urban environments.

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