GPS/BDS RTK Positioning Based on Equivalence Principle Using Multiple Reference Stations

Reliable real-time kinematic (RTK) is crucially important for emerging global navigation satellite systems (GNSSs) applications, such as drones and unmanned vehicles. The performance of conventional single baseline RTK (SBRTK) with one reference station degrades greatly in dense, urban environments, due to signal blockage and multipath error. The increasing use of multiple reference stations for kinematic positioning can improve RTK positioning accuracy and availability in urban areas. This paper proposes a new algorithm for multi-baseline RTK (MBRTK) positioning based on the equivalence principle. The advantages of the solution are to keep observation independent and increase the redundancy to estimate the unknown parameters. The equivalent double-differenced (DD) observation equations for multiple reference stations are firstly developed through the equivalent transform. A modified Kalman filter with parameter constraints is proposed, as well as a partial ambiguity resolution (PAR) strategy is developed to determine an ambiguity subset. Finally, the static and kinematic experiments are carried out to validate the proposed algorithm. The results demonstrate that, compared with single global positioning system (GPS) and Beidou navigation system (BDS) RTK positioning, the GPS/BDS positioning for MBRTK can enhance the positioning accuracy with improvement by approximately (45%, 35%, and 27%) and (12%, 6%, and 19%) in the North (N), East (E), and Up (U) components, as well as the availability with improvement by about 33% and 10%, respectively. Moreover, the MBRTK model with two and three reference receivers can significantly increase the redundancy and provide smaller ambiguity dilution of precision (ADOP) values. Compared with the scheme-one and scheme-two for SBRTK, the MBRTK with multiple reference receivers have a positioning accuracy improvement by about (9%, 0%, and 6%) and (9%, 16%, and 16%) in N, E, and U components, as well as the availability improvement by approximately 10%. Therefore, compared with the conventional SBRTK, the MBRTK can enhance the strength of the kinematic positioning model as well as improve the positioning accuracy and availability.

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Implementation and Performance of a Deeply-Coupled GNSS Receiver with Low-Cost MEMS Inertial Sensors for Vehicle Urban Navigation

Sensors ◽

10.3390/s20123397 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3397 ◽

Cited By ~ 1

Author(s):

Xin Feng ◽

Tisheng Zhang ◽

Tao Lin ◽

Hailiang Tang ◽

Xiaoji Niu

Keyword(s):

Urban Areas ◽

Weight Control ◽

Low Cost ◽

Field Tests ◽

Urban Environments ◽

Global Navigation Satellite Systems ◽

Measurement Unit ◽

Positioning Accuracy ◽

Gnss Receiver ◽

Tracking Loops

In urban environments, Global Navigation Satellite Systems (GNSS) signals are frequently attenuated, blocked or reflected, which degrades the positioning accuracy of GNSS receivers significantly. To improve the performance of GNSS receiver for vehicle urban navigation, a GNSS/INS deeply-coupled software defined receiver (GIDCSR) with a low cost micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) ICM-20602 is presented, in which both GPS and BDS constellations are supported. Two key technologies, that is, adaptive open-close tracking loops and INS aided pseudo-range weight control algorithm, are applied in the GIDCSR to enhance the signal tracking continuity and positioning accuracy in urban areas. To assess the performance of the proposed deep couple solution, vehicle field tests were carried out in GNSS-challenged urban environments. With the adaptive open-close tracking loops, the deep couple output carrier phase in the open sky, and improved pseudo-range accuracy before and after GNSS signal blocked. Applying the INS aided pseudo-range weight control, the pseudo-range gross errors of the deep couple decreased caused by multipath. A popular GNSS/INS tightly-coupled vehicle navigation kit from u-blox company, M8U, was tested side by side as benchmark. The test results indicate that in the GNSS-challenged urban areas, the pseudo-range quality of GIDCSR is at least 25% better than that of M8U, and GIDCSR’s horizontal positioning results are at least 69% more accurate than M8U’s.

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A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning

Remote Sensing ◽

10.3390/rs13112117 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2117

Author(s):

Qi Cheng ◽

Ping Chen ◽

Rui Sun ◽

Junhui Wang ◽

Yi Mao ◽

...

Keyword(s):

Fault Detection ◽

Real Time ◽

Urban Areas ◽

Least Square ◽

Global Navigation Satellite Systems ◽

Positioning Accuracy ◽

Detection Scheme ◽

Multiple Faults ◽

Ground Vehicle ◽

Vehicle Positioning

The performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS in some environments, such as in urban areas, are often affected by non-line-of-sight (NLOS) signals and multipath effects. It is therefore essential to develop an effective fault detection scheme that can be applied to GNSS observations so as to ensure that the vehicle positioning can be calculated with a high accuracy. In this paper, we propose an online dataset based faulty GNSS measurement detection and exclusion algorithm for vehicle positioning that takes account of the NLOS/multipath affected scenarios. The proposed algorithm enables a real-time online dataset based fault detection and exclusion scheme, which makes it possible to detect multiple faults in different satellites simultaneously and accurately, thereby allowing real-time quality control of GNSS measurements in dynamic urban positioning applications. The algorithm was tested with simulated/artificial step errors in various scenarios in the measured pseudoranges from a dataset acquired from a UAV in an open area. Furthermore, a real-world test was also conducted with a ground-vehicle driving in a dense urban environment to validate the practical efficiency of the proposed algorithm. The UAV based simulation exhibits a fault detection rate of 100% for both single and multi-satellite fault scenarios, with the horizontal positioning accuracy improved to about 1 metre from tens of metres after fault detection and exclusion. The ground vehicle-based real test shows an overall improvement of 26.1% in 3D positioning accuracy in an urban area compared to the traditional least square method.

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Road Tests of the Positioning Accuracy of INS/GNSS Systems Based on MEMS Technology for Navigating Railway Vehicles

Energies ◽

10.3390/en13174463 ◽

2020 ◽

Vol 13 (17) ◽

pp. 4463 ◽

Cited By ~ 3

Author(s):

Mariusz Specht ◽

Cezary Specht ◽

Paweł Dąbrowski ◽

Krzysztof Czaplewski ◽

Leszek Smolarek ◽

...

Keyword(s):

Urban Areas ◽

Land Development ◽

Global Navigation Satellite Systems ◽

Rolling Stock ◽

Navigation Systems ◽

Positioning Accuracy ◽

Positioning Systems ◽

Satellite Systems ◽

Wide Range ◽

Mems Technology

Thanks to the support of Inertial Navigation Systems (INS), Global Navigation Satellite Systems (GNSS) provide a navigation positioning solution that, in the absence of satellite signals (in tunnels, forest and urban areas), allows the continuous positioning of a moving object (air, land and sea). Passenger and freight trains must, for safety reasons, comply with several formal navigation requirements, particularly those that concern the minimum acceptable accuracy for determining their position. Depending on the type of task performed by the train (positioning a vehicle on a route, stopping at a turnout, stopping at a platform, monitoring the movement of rolling stock, etc.), the train must have positioning systems that can determine its position with sufficient accuracy (1–10 m, p = 0.95) to perform the tasks in question. A wide range of INS/GNSS equipment is currently available, ranging from very costly to simple solutions based on Micro-Electro-Mechanical Systems (MEMS), which, in addition to an inertial unit, use one or two GNSS receivers. The paper presents an assessment of the accuracy of both types of solutions by testing them simultaneously in dynamic measurements. The research, due to the costs and logistics complexity, was made using a passenger car. The surveys were carried out in a complex way, because the measurement route was travelled three times at four different speeds: 40 km/h, 80 km/h, 100 km/h and 120 km/h on seven representative test sections with diverse land development. In order to determine the positioning accuracy of INS devices, two precise GNSS geodetic receivers (2 cm accuracy, p = 0.95) were used as a reference positioning system. The measurements demonstrated that only INS/GNSS systems based on two receivers can meet the requirements of most railway applications related to rail navigation, and since a solution with a single GNSS receiver has a much lower positioning accuracy, it is not suitable for many railway applications. It is noted that considerable differences between the standards defining the navigation requirements for railway applications. For example, INS/GNSS systems based on two receivers meet the vast majority of the expectations specified in the Report on Rail User Needs and Requirements. However, according to the Federal Radionavigation Plan (FRP), it cannot be used in any railway application.

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Evaluation of Quad-Constellation GNSS Precise Point Positioning in Egypt

Artificial Satellites ◽

10.1515/arsa-2017-0002 ◽

2017 ◽

Vol 52 (1) ◽

pp. 9-18

Author(s):

Emad El Manaily ◽

Mahmoud Abd Rabbou ◽

Adel El-Shazly ◽

Moustafa Baraka

Keyword(s):

Urban Areas ◽

Precise Point Positioning ◽

Low Cost ◽

Single Point ◽

Convergence Time ◽

Reference Station ◽

Single Frequency ◽

Major Drawback ◽

Positioning Accuracy ◽

Point Positioning

Abstract Commonly, relative GPS positioning technique is used in Egypt for precise positioning applications. However, the requirement of a reference station is usually problematic for some applications as it limits the operational range of the system and increases the system cost and complexity On the other hand; the single point positioning is traditionally used for low accuracy applications such as land vehicle navigation with positioning accuracy up to 10 meters in some scenarios which caused navigation problems especially in downtown areas. Recently, high positioning accuracy can be obtained through Precise Point Positioning (PPP) technique in which only once GNSS receiver is used. However, the major drawback of PPP is the long convergence time to reach to the surveying grade accuracy compared to the existing relative techniques. Moreover, the PPP accuracy is significantly degraded due to shortage in satellite availability in urban areas. To overcome these limitations, the quad constellation GNSS systems namely; GPS.GLONASS, Galileo and BeiDou can be combined to increase the satellite availability and enhance the satellite geometry which in turn reduces the convergence time. In Egypt, at the moment, the signals of both Galileo and BeiDou could be logged with limited number of satellites up to four and six satellites for both Systems respectively. In this paper, we investigated the performance of the Quad-GNSS positioning in both dual- and single-frequency ionosphere free PPP modes for both high accurate and low cost navigation application, respectively. The performance of the developed PPP models will be investigated through GNSS data sets collected at three Egyptian cities namely, Cairo, Alexandria and Aswan.

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Feasibility Analysis of LTE-Based UAS Navigation in Deep Urban Areas and DSRC Augmentation

Sensors ◽

10.3390/s19194192 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4192 ◽

Cited By ~ 1

Author(s):

Euiho Kim ◽

Yujin Shin

Keyword(s):

Urban Areas ◽

Autonomous Navigation ◽

Base Station ◽

Unmanned Aircraft ◽

Global Navigation Satellite Systems ◽

Urban Canyon ◽

Positioning Accuracy ◽

Cooperative Positioning ◽

Lte Network ◽

Better Than

The current autonomous navigation of unmanned aircraft systems (UAS) heavily depends on Global Navigation Satellite Systems (GNSS). However, in challenging environments, such as deep urban areas, GNSS signals can be easily interrupted, so that UAS may lose navigation capability at any instant. For urban positioning and navigation, Long Term Evolution (LTE) has been considered a promising signal of opportunity due to its dense network in urban areas, and there has recently been great advancement in LTE positioning technology. However, the current LTE positioning accuracy is found to be insufficient for safe UAS navigation in deep urban areas. This paper evaluates the positioning performance of the current network of LTE base stations in a selected deep urban area and investigates the effectiveness of LTE augmentations using dedicated short range communication (DSRC) transceivers through the optimization of the ground LTE/DSRC network and cooperative positioning among UAS. The analysis results based on simulation using an urban canyon model and signal line of sight propagations show that the addition of four or five DSRC transceivers to the existing LTE base station network could provide better than 4–6 m horizontal positioning accuracy (95%) in the selected urban canyon at a position of 150 ft above the ground, while a dense LTE network alone may result in a 15–20 m horizontal positioning error. Additionally, the simulation results of cooperative positioning with inter-UAS ranging measurements in the DSRC augmented LTE network were shown to provide horizontal positioning accuracy better than 1 m in most flight space, assuming negligible time-synchronization errors in inter-UAS ranging measurements.

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Shadow Matching: A New GNSS Positioning Technique for Urban Canyons

Journal of Navigation ◽

10.1017/s0373463311000087 ◽

2011 ◽

Vol 64 (3) ◽

pp. 417-430 ◽

Cited By ~ 134

Author(s):

Paul D. Groves

Keyword(s):

Urban Areas ◽

Tall Buildings ◽

Global Navigation Satellite Systems ◽

Positioning System ◽

Positioning Accuracy ◽

Satellite Systems ◽

Building Models ◽

Satellite Visibility ◽

Global Navigation Satellite ◽

Cross Track

The Global Positioning System (GPS) is unreliable in dense urban areas, known as urban canyons, which have tall buildings or narrow streets. This is because the buildings block the signals from many of the satellites. Combining GPS with other Global Navigation Satellite Systems (GNSS) significantly increases the availability of direct line-of-sight signals. Modelling is used to demonstrate that, although this will enable accurate positioning along the direction of the street, the positioning accuracy in the cross-street direction will be poor because the unobstructed satellite signals travel along the street, rather than across it. A novel solution to this problem is to use 3D building models to improve cross-track positioning accuracy in urban canyons by predicting which satellites are visible from different locations and comparing this with the measured satellite visibility to determine position. Modelling is used to show that this shadow matching technique has the potential to achieve metre-order cross-street positioning in urban canyons. The issues to be addressed in developing a robust and practical shadow matching positioning system are then discussed and solutions proposed.

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Empirical Stochastic Model of Multi-GNSS Measurements

Sensors ◽

10.3390/s21134566 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4566

Author(s):

Dominik Prochniewicz ◽

Kinga Wezka ◽

Joanna Kozuchowska

Keyword(s):

Stochastic Model ◽

Density Ratio ◽

Functional Model ◽

Optimal Solution ◽

Global Navigation Satellite Systems ◽

Unknown Parameters ◽

Short Baseline ◽

Stochastic Parameters ◽

Dependent Model ◽

The Impact

The stochastic model, together with the functional model, form the mathematical model of observation that enables the estimation of the unknown parameters. In Global Navigation Satellite Systems (GNSS), the stochastic model is an especially important element as it affects not only the accuracy of the positioning model solution, but also the reliability of the carrier-phase ambiguity resolution (AR). In this paper, we study in detail the stochastic modeling problem for Multi-GNSS positioning models, for which the standard approach used so far was to adopt stochastic parameters from the Global Positioning System (GPS). The aim of this work is to develop an individual, empirical stochastic model for each signal and each satellite block for GPS, GLONASS, Galileo and BeiDou systems. The realistic stochastic model is created in the form of a fully populated variance-covariance (VC) matrix that takes into account, in addition to the Carrier-to-Noise density Ratio (C/N0)-dependent variance function, also the cross- and time-correlations between the observations. The weekly measurements from a zero-length and very short baseline are utilized to derive stochastic parameters. The impact on the AR and solution accuracy is analyzed for different positioning scenarios using the modified Kalman Filter. Comparing the positioning results obtained for the created model with respect to the results for the standard elevation-dependent model allows to conclude that the individual empirical stochastic model increases the accuracy of positioning solution and the efficiency of AR. The optimal solution is achieved for four-system Multi-GNSS solution using fully populated empirical model individual for satellite blocks, which provides a 2% increase in the effectiveness of the AR (up to 100%), an increase in the number of solutions with errors below 5 mm by 37% and a reduction in the maximum error by 6 mm compared to the Multi-GNSS solution using the elevation-dependent model with neglected measurements correlations.

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Characterization of Carrier Phase-Based Positioning in Real-World Jamming Conditions

Remote Sensing ◽

10.3390/rs13142680 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2680

Author(s):

Søren Skaarup Larsen ◽

Anna B. O. Jensen ◽

Daniel H. Olesen

Keyword(s):

Real World ◽

Carrier Phase ◽

Reference Station ◽

Baseline Length ◽

Dual Frequency ◽

Positioning Accuracy ◽

The Impact ◽

Single Versus ◽

Selection Of

GNSS signals arriving at receivers at the surface of the Earth are weak and easily susceptible to interference and jamming. In this paper, the impact of jamming on the reference station in carrier phase-based relative baseline solutions is examined. Several scenarios are investigated in order to assess the robustness of carrier phase-based positioning towards jamming. Among others, these scenarios include a varying baseline length, the use of single- versus dual-frequency observations, and the inclusion of the Galileo and GLONASS constellations to a GPS only solution. The investigations are based on observations recorded at physical reference stations in the Danish TAPAS network during actual jamming incidents, in order to realistically evaluate the impact of real-world jamming on carrier phase-based positioning accuracy. The analyses performed show that, while there are benefits of using observations from several frequencies and constellations in positioning solutions, special care must be taken in solution processing. The selection of which GNSS constellations and observations to include, as well as when they are included, is essential, as blindly adding more jamming-affected observations may lead to worse positioning accuracy.

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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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