scholarly journals Robustly Adaptive EKF PDR/UWB Integrated Navigation Based on Additional Heading Constraint

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4390
Author(s):  
Debao Yuan ◽  
Jian Zhang ◽  
Jian Wang ◽  
Ximin Cui ◽  
Fei Liu ◽  
...  
Keyword(s):  
Dead Reckoning ◽  
Wide Band ◽  
Satellite System ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Integrated Navigation ◽  
Position Information ◽  
Positioning Systems ◽  
Global Navigation Satellite ◽  
Non Line Of Sight

At present, GNSS (Global Navigation Satellite System) positioning technology is widely used for outdoor positioning services because of its high-precision positioning characteristics. However, in indoor environments, effective position information cannot be provided, because of the signals being obscured. In order to improve the accuracy and continuity of indoor positioning systems, in this paper, we propose a PDR/UWB (Pedestrian Dead Reckoning and Ultra Wide Band) integrated navigation algorithm based on an adaptively robust EKF (Extended Kalman Filter) to address the problem of error accumulation in the PDR algorithm and gross errors in the location results of the UWB in non-line-of-sight scenarios. First, the basic principles of UWB and PDR location algorithms are given. Then, we propose a loose combination of the PDR and UWB algorithms by using the adaptively robust EKF. By using the robust factor to adjust the weight of the observation value to resist the influence of the gross error, and by adjusting the variance of the system adaptively according to the positioning scene, the algorithm can improve the robustness and heading factor of the PDR algorithm, which is constrained by indoor maps. Finally, the effectiveness of the algorithm is verified by the measured data. The experimental results showed that the algorithm can not only reduce the accumulation of PDR errors, but can also resist the influence of gross location errors under non-line-of-sight UWB scenarios.

Urban Fleet Monitoring with GPS and GLONASS

1998 ◽  
Vol 51 (3) ◽  
pp. 382-393 ◽  
Author(s):  
M. Tsakiri ◽  
M. Stewart ◽  
T. Forward ◽  
D. Sandison ◽  
J. Walker
Keyword(s):  
Global Positioning System ◽  
Public Transport ◽  
Urban Areas ◽  
Dead Reckoning ◽  
Satellite System ◽  
Basic Function ◽  
Positioning System ◽  
Positioning Systems ◽  
Global Positioning ◽  
Global Navigation Satellite

The increasing volume of traffic in urban areas has resulted in steady growth of the mean driving time on fixed routes. Longer driving times lead to significantly higher transportation costs, particularly for vehicle fleets, where efficiency in the distribution of their transport tasks is important in staying competitive in the market. For bus fleets, the optimal control and command of the vehicles is, as well as the economic requirements, a basic function of their general mission. The Global Positioning System (GPS) allows reliable and accurate positioning of public transport vehicles except within the physical limitations imposed by built-up city ‘urban canyons’. With a view to the next generation of satellite positioning systems for public transport fleet management, this paper highlights the limitations imposed on current GPS systems operating in the urban canyon. The capabilities of a future positioning system operating in this type of environment are discussed. It is suggested that such a system could comprise receivers capable of integrating the Global Positioning System (GPS) and the Russian equivalent, the Global Navigation Satellite System (GLONASS), and relatively cheap dead-reckoning sensors.

scholarly journals AIOSAT - Autonomous Indoor & Outdoor Safety Tracking System

2019 ◽  
Vol 26 (1) ◽  
pp. 21-32
Author(s):  
Iñigo Adin ◽  
Paul Zabalegui ◽  
Alejandro Perez ◽  
Jaione Arrizabalaga ◽  
Jon Goya ◽  
...  
Keyword(s):  
Rural Areas ◽  
Tracking System ◽  
Dead Reckoning ◽  
Wide Band ◽  
Satellite System ◽  
System Level ◽  
Horizon 2020 ◽  
Rescue Workers ◽  
Global Navigation Satellite ◽  
Map Data

Abstract Even though satellite-based positioning increases rescue workers’ safety and efficiency, signal availability, reliability, and accuracy are often poor during fire operations, due to terrain formation, natural and structural obstacles or even the conditions of the operation. In central Europe, the stakeholders report a strong necessity to complement the location for mixed indoor-outdoor and GNSS blocked scenarios. As such, location information often needs to be augmented. For that, European Global Navigation Satellite System Galileo could help by improving the availability of the satellites with different features. Moreover, a multi-sensored collaborative system could also take advantage of the rescue personnel who are already involved in firefighting and complement the input data for positioning. The Autonomous Indoor & Outdoor Safety Tracking System (AIOSAT) is a multinational project founded through the Horizon 2020 program, with seven partners from Spain, Netherlands and Belgium. It is reaching the first year of progress (out of 3) and the overarching objective of AIOSAT system is to advance beyond the state of the art in tracking rescue workers by creating a high availability and high integrity team positioning and tracking system. On the system level approach, this goal is achieved by fusing the GNSS, EDAS/EGNOS, pedestrian dead reckoning and ultra-wide band ranging information, possibly augmented with map data. The system should be able to work both inside buildings and rural areas, which are the test cases defined by the final users involved in the consortium and the advisory board panel of the project

A Hybrid Intelligent Algorithm DGP-MLP for GNSS/INS Integration during GNSS Outages

2018 ◽  
Vol 72 (2) ◽  
pp. 375-388 ◽  
Author(s):  
Yuexin Zhang ◽  
Lihui Wang
Keyword(s):  
Satellite System ◽  
Micro Electro Mechanical System ◽  
Real Field ◽  
Prediction Errors ◽  
Integrated Navigation ◽  
Intelligent Algorithm ◽  
Position Information ◽  
Hybrid Intelligent Algorithm ◽  
Global Navigation Satellite ◽  
Adaptively Adjusting

The performance of Global Navigation Satellite System (GNSS) and Micro-Electro-Mechanical System (MEMS)-based Inertial Navigation System (INS) integrated navigation is reduced during GNSS outages. To bridge the period during GNSS outages, a novel hybrid intelligent algorithm incorporating a Discrete Grey Predictor (DGP) and a Multilayer Perceptron (MLP) neural network (DGP-MLP) is proposed. The DGP-MLP is used to provide a pseudo-GNSS position to correct the INS errors during GNSS outages; the DGP uses the GNSS position information of the latest few moments to predict the position of future moments; in the process of DGP-MLP, the MLP is used to modify the prediction errors of DGP, and the MLP is improved by adding momentum terms and adaptively adjusting the learning rate and momentum factor. To evaluate the effectiveness of the proposed methodology, four GNSS outages in different cases over a real field test data were employed. The experimental results demonstrate that the proposed methodology can significantly improve positioning accuracy during GNSS outages.

Ubiquitous Positioning Technologies for Modern Intelligent Navigation Systems

2005 ◽  
Vol 59 (1) ◽  
pp. 91-103 ◽  
Author(s):  
Guenther Retscher ◽  
Allison Kealy
Keyword(s):  
Dead Reckoning ◽  
Satellite System ◽  
Indoor Environments ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
First Case ◽  
And Performance ◽  
Navigation Service ◽  
Global Navigation Satellite

Recently new location technologies have emerged that can be employed in modern advanced navigation systems. They can be employed to augment Global Navigation Satellite System (GNSS) positioning techniques and dead reckoning as they offer different levels of positioning accuracies and performance. An integration of other technologies is especially required in indoor and outdoor-to-indoor environments. The paper gives an overview of the newly developed ubiquitous positioning technologies and their integration in navigation systems. Furthermore two case studies are presented, i.e., the improvement of land vehicle safety using Augmented Reality (AR) technologies and pedestrian navigation services for the guidance of users to certain University offices. In the first case study the integration of map matching into a Kalman filter approach is performed (referred to as “Intelligent Vehicle Navigation”) and its principle is briefly described. This approach can also be adapted for the pedestrian navigation service described in the second case study.

scholarly journals TDMA Datalink Cooperative Navigation Algorithm Based on INS/JTIDS/BA

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Satellite System ◽  
Time Of Arrival ◽  
Military Operations ◽  
Position Information ◽  
Cooperative Navigation ◽  
Navigation Algorithm ◽  
Geometric Dilution Of Precision ◽  
Global Navigation Satellite

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.

scholarly journals Many Ways Lead to the Goal—Possibilities of Autonomous and Infrastructure-Based Indoor Positioning

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 397
Author(s):  
Hossein Shoushtari ◽  
Thomas Willemsen ◽  
Harald Sternberg
Keyword(s):  
Mobile Networks ◽  
Dead Reckoning ◽  
Simulated Data ◽  
Minimum Cost ◽  
Cost Effective ◽  
Satellite System ◽  
Position Estimation ◽  
Robust Solution ◽  
Position Data ◽  
Global Navigation Satellite

There are many ways to navigate in Global Navigation Satellite System-(GNSS) shaded areas. Reliable indoor pedestrian navigation has been a central aim of technology researchers in recent years; however, there still exist open challenges requiring re-examination and evaluation. In this paper, a novel dataset is used to evaluate common approaches for autonomous and infrastructure-based positioning methods. The autonomous variant is the most cost-effective realization; however, realizations using the real test data demonstrate that the use of only autonomous solutions cannot always provide a robust solution. Therefore, correction through the use of infrastructure-based position estimation based on smartphone technology is discussed. This approach invokes the minimum cost when using existing infrastructure, whereby Pedestrian Dead Reckoning (PDR) forms the basis of the autonomous position estimation. Realizations with Particle Filters (PF) and a topological approach are presented and discussed. Floor plans and routing graphs are used, in this case, to support PDR positioning. The results show that the positioning model loses stability after a given period of time. Fifth Generation (5G) mobile networks can enable this feature, as well as a massive number of use-cases, which would benefit from user position data. Therefore, a fusion concept of PDR and 5G is presented, the benefit of which is demonstrated using the simulated data. Subsequently, the first implementation of PDR with 5G positioning using PF is carried out.

scholarly journals Constrained Unscented Particle Filter for SINS/GNSS/ADS Integrated Airship Navigation in the Presence of Wind Field Disturbance

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 471 ◽  
Author(s):  
Zhaohui Gao ◽  
Dejun Mu ◽  
Yongmin Zhong ◽  
Chengfan Gu
Keyword(s):  
Wind Speed ◽  
Particle Filter ◽  
State Estimation ◽  
Wind Field ◽  
Satellite System ◽  
Integrated Navigation ◽  
Unscented Particle Filter ◽  
Field Disturbance ◽  
Global Navigation Satellite ◽  
Optimal State Estimation

Due to the disturbance of wind field, it is difficult to achieve precise airship positioning and navigation in the stratosphere. This paper presents a new constrained unscented particle filter (UPF) for SINS/GNSS/ADS (inertial navigation system/global navigation satellite system/atmosphere data system) integrated airship navigation. This approach constructs a wind speed model to describe the relationship between airship velocity and wind speed using the information output from ADS, and further establishes a mathematical model for SINS/GNSS/ADS integrated navigation. Based on these models, it also develops a constrained UPF to obtain system state estimation for SINS/GNSS/ADS integration. The proposed constrained UPF uses the wind speed model to constrain the UPF filtering process to effectively resist the influence of wind field on the navigation solution. Simulations and comparison analysis demonstrate that the proposed approach can achieve optimal state estimation for SINS/GNSS/ADS integrated airship navigation in the presence of wind field disturbance.

scholarly journals GNSS Multipath Detection Using Continuous Time-Series C/N0

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 4059
Author(s):  
Nobuaki Kubo ◽  
Kaito Kobayashi ◽  
Rei Furukawa
Keyword(s):  
Time Series ◽  
Continuous Time ◽  
Urban Areas ◽  
Satellite System ◽  
Line Of Sight ◽  
Static Tests ◽  
Gnss Receivers ◽  
Multipath Detection ◽  
Global Navigation Satellite ◽  
Multipath Errors

The reduction of multipath errors is a significant challenge in the Global Navigation Satellite System (GNSS), especially when receiving non-line-of-sight (NLOS) signals. However, selecting line-of-sight (LOS) satellites correctly is still a difficult task in dense urban areas, even with the latest GNSS receivers. This study demonstrates a new method of utilization of C/N0 of the GNSS to detect NLOS signals. The elevation-dependent threshold of the C/N0 setting may be effective in mitigating multipath errors. However, the C/N0 fluctuation affected by NLOS signals is quite large. If the C/N0 is over the threshold, the satellite is used for positioning even if it is still affected by the NLOS signal, which causes the positioning error to jump easily. To overcome this issue, we focused on the value of continuous time-series C/N0 for a certain period. If the C/N0 of the satellite was less than the determined threshold, the satellite was not used for positioning for a certain period, even if the C/N0 recovered over the threshold. Three static tests were conducted at challenging locations near high-rise buildings in Tokyo. The results proved that our method could substantially mitigate multipath errors in differential GNSS by appropriately removing the NLOS signals. Therefore, the performance of real-time kinematic GNSS was significantly improved.

scholarly journals A Loose-Coupled Fusion of Inertial and UWB Assisted by a Decision-Making Algorithm for Localization of Emergency Responders

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1463 ◽  
Author(s):  
André G. Ferreira ◽  
Duarte Fernandes ◽  
André P. Catarino ◽  
Ana M. Rocha ◽  
João L. Monteiro
Keyword(s):  
Decision Making ◽  
Indoor Localization ◽  
Dead Reckoning ◽  
Time Of Arrival ◽  
Robust Solution ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Emergency Responders ◽  
Pedestrian Dead Reckoning ◽  
Non Line Of Sight

Combining different technologies is gaining significant popularity among researchers and industry for the development of indoor positioning systems (IPSs). These hybrid IPSs emerge as a robust solution for indoor localization as the drawbacks of each technology can be mitigated or even eliminated by using complementary technologies. However, fusing position estimates from different technologies is still very challenging and, therefore, a hot research topic. In this work, we pose fusing the ultrawideband (UWB) position estimates with the estimates provided by a pedestrian dead reckoning (PDR) by using a Kalman filter. To improve the IPS accuracy, a decision-making algorithm was developed that aims to assess the usability of UWB measurements based on the identification of non-line-of-sight (NLOS) conditions. Three different data fusion algorithms are tested, based on three different time-of-arrival positioning algorithms, and experimental results show a localization accuracy of below 1.5 m for a 99th percentile.

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