scholarly journals A Robust GNSS/PDR Integration Scheme with GRU-Based Zero-Velocity Detection for Mass-Pedestrians

2022 ◽  
Vol 14 (2) ◽  
pp. 300
Author(s):  
Dongpeng Xie ◽  
Jinguang Jiang ◽  
Jiaji Wu ◽  
Peihui Yan ◽  
Yanan Tang ◽  
...  
Keyword(s):  
Low Cost ◽  
Single Point ◽  
Dead Reckoning ◽  
Satellite System ◽  
Integration Scheme ◽  
Fusion Algorithm ◽  
Zero Velocity ◽  
Single Antenna ◽  
Other Information ◽  
Global Navigation Satellite

Aiming at the problem of high-precision positioning of mass-pedestrians with low-cost sensors, a robust single-antenna Global Navigation Satellite System (GNSS)/Pedestrian Dead Reckoning (PDR) integration scheme is proposed with Gate Recurrent Unit (GRU)-based zero-velocity detector. Based on the foot-mounted pedestrian navigation system, the error state extended Kalman filter (EKF) framework is used to fuse GNSS position, zero-velocity state, barometer elevation, and other information. The main algorithms include improved carrier phase smoothing pseudo-range GNSS single-point positioning, GRU-based zero-velocity detection, and adaptive fusion algorithm of GNSS and PDR. Finally, the scheme was tested. The root mean square error (RMSE) of the horizontal error in the open and complex environments is lower than 1 m and 1.5 m respectively. In the indoor elevation experiment where the elevation difference of upstairs and downstairs exceeds 25 m, the elevation error is lower than 1 m. This result can provide technical reference for the accurate and continuous acquisition of public pedestrian location information.

scholarly journals The Design a TDCP-Smoothed GNSS/Odometer Integration Scheme with Vehicular-Motion Constraint and Robust Regression

2020 ◽  
Vol 12 (16) ◽  
pp. 2550
Author(s):  
Kai-Wei Chiang ◽  
Yu-Hua Li ◽  
Li-Ta Hsu ◽  
Feng-Yu Chu
Keyword(s):  
State Estimation ◽  
Navigation System ◽  
Robust Regression ◽  
Single Point ◽  
Dead Reckoning ◽  
Satellite System ◽  
Least Square ◽  
Integration Scheme ◽  
Intelligent Transport System ◽  
Global Navigation Satellite

Global navigation satellite system (GNSS) is widely regarded as the primary positioning solution for intelligent transport system (ITS) applications. However, its performance could degrade, due to signal outages and faulty-signal contamination, including multipath and non-line-of-sight reception. Considering the limitation of the performance and computation loads in mass-produced automotive products, this research investigates the methods for enhancing GNSS-based solutions without significantly increasing the cost for vehicular navigation system. In this study, the measurement technique of the odometer in modern vehicle designs is selected to integrate the GNSS information, without using an inertial navigation system. Three techniques are implemented to improve positioning accuracy; (a) Time-differenced carrier phase (TDCP) based filter: A state-augmented extended Kalman filter is designed to incorporate TDCP measurements for maximizing the effectiveness of phase-smoothing; (b) odometer-aided constraints: The aiding measurement from odometer utilizing forward speed with the lateral constraint enhances the state estimation; the information based on vehicular motion, comprising the zero-velocity constraint, fault detection and exclusion, and dead reckoning, maintains the stability of the positioning solution; (c) robust regression: A weighted-least-square based robust regression as a measurement-quality assessment is applied to adjust the weightings of the measurements adaptively. Experimental results in a GNSS-challenging environment indicate that, based on the single-point-positioning mode with an automotive-grade receiver, the combination of the proposed methods presented a root-mean-square error of 2.51 m, 3.63 m, 1.63 m, and 1.95 m for the horizontal, vertical, forward, and lateral directions, with improvements of 35.1%, 49.6%, 45.3%, and 21.1%, respectively. The statistical analysis exhibits 97.3% state estimation result in the horizontal direction for the percentage of epochs that had errors of less than 5 m, presenting that after the intervention of proposed methods, the positioning performance can fulfill the requirements for road level applications.

scholarly journals Walker: Continuous and Precise Navigation by Fusing GNSS and MEMS in Smartphone Chipsets for Pedestrians

2019 ◽  
Vol 11 (2) ◽  
pp. 139 ◽  
Author(s):  
Feng Zhu ◽  
Xianlu Tao ◽  
Wanke Liu ◽  
Xiang Shi ◽  
Fuhong Wang ◽  
...  
Keyword(s):  
Carrier Phase ◽  
Signal To Noise Ratio ◽  
Single Point ◽  
Dead Reckoning ◽  
Smartphone Application ◽  
Satellite System ◽  
Portable Devices ◽  
Navigation Solution ◽  
Global Navigation Satellite ◽  
Gnss Observations

The continual miniaturization of mass-market sensors built in mobile intelligent terminals has inspired the development of accurate and continuous navigation solution for portable devices. With the release of Global Navigation Satellite System (GNSS) observations from the Android Nougat system, smartphones can provide pseudorange, Doppler, and carrier phase observations of GNSS. However, it is still a challenge to achieve the seamless positioning of consumer applications, especially in environments where GNSS signals suffer from a low signal-to-noise ratio and severe multipath. This paper introduces a dedicated android smartphone application called Walker that integrates the GNSS navigation solution and MEMS (micro-electromechanical systems) sensors to enable continuous and precise pedestrian navigation. Firstly, we introduce the generation of GNSS and MEMS observations, in addition to the architecture of Walker application. Then the core algorithm in Walker is given, including the time-differenced carrier phase improved GNSS single-point positioning and the integration of GNSS and Pedestrian Dead Reckoning (PDR). Finally, the Walker application is tested and the observations of GNSS and MEMS are assessed. The static experiment shows that, with GNSS observations, the RMS (root mean square) values of east, north, and up positioning error are 0.49 m, 0.37 m, and 1.01 m, respectively. Furthermore, the kinematic experiment verifies that the proposed method is capable of obtaining accuracy within 1–3 m for smooth and continuous navigation.

scholarly journals Constrained ESKF for UAV Positioning in Indoor Corridor Environment Based on IMU and WiFi

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 391
Author(s):  
Zhonghan Li ◽  
Yongbo Zhang
Keyword(s):  
Data Fusion ◽  
Autonomous Navigation ◽  
Low Cost ◽  
Optimization Method ◽  
Satellite System ◽  
Fusion Algorithm ◽  
K Nearest Neighbors ◽  
Positioning Accuracy ◽  
Spatial Features ◽  
Global Navigation Satellite

The indoor autonomous navigation of unmanned aerial vehicles (UAVs) is the current research hotspot. Unlike the outdoor broad environment, the indoor environment is unknown and complicated. Global Navigation Satellite System (GNSS) signals are easily blocked and reflected because of complex indoor spatial features, which make it impossible to achieve positioning and navigation indoors relying on GNSS. This article proposes a set of indoor corridor environment positioning methods based on the integration of WiFi and IMU. The zone partition-based Weighted K Nearest Neighbors (WKNN) algorithm is used to achieve higher WiFi-based positioning accuracy. On the basis of the Error-State Kalman Filter (ESKF) algorithm, WiFi-based and IMU-based methods are fused together and realize higher positioning accuracy. The probability-based optimization method is used for further accuracy improvement. After data fusion, the positioning accuracy increased by 51.09% compared to the IMU-based algorithm and by 66.16% compared to the WiFi-based algorithm. After optimization, the positioning accuracy increased by 20.9% compared to the ESKF-based data fusion algorithm. All of the above results prove that methods based on WiFi and IMU (low-cost sensors) are very capable of obtaining high indoor positioning accuracy.

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 Design of a Multiband Global Navigation Satellite System Radio Frequency Interference Monitoring Front-End with Synchronized Secondary Sensors

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2594
Author(s):  
Aiden Morrison ◽  
Nadezda Sokolova ◽  
James Curran
Keyword(s):  
Radio Frequency ◽  
Global Navigation Satellite System ◽  
Low Cost ◽  
Satellite System ◽  
Radio Frequency Interference ◽  
Navigation Satellite ◽  
Inertial Measurement ◽  
Front End ◽  
Global Navigation ◽  
Global Navigation Satellite

This paper investigates the challenges of developing a multi-frequency radio frequency interference (RFI) monitoring and characterization system that is optimized for ease of deployment and operation as well as low per unit cost. To achieve this, we explore the design and development of a multiband global navigation satellite system (GNSS) front-end which is intrinsically capable of synchronizing side channel information from non-RF sensors, such as inertial measurement units and integrated power meters, to allow the simultaneous production of substantial amounts of sampled spectrum while also allowing low-cost, real-time monitoring and logging of detected RFI events. While the inertial measurement unit and barometer are not used in the RFI investigation discussed, the design features that provide for their precise synchronization with the RF sample stream are presented as design elements worth consideration. The designed system, referred to as Four Independent Tuners with Data-packing (FITWD), was utilized in a data collection campaign over multiple European and Scandinavian countries in support of the determination of the relative occurrence rates of L1/E1 and L5/E5a interference events and intensities where it proved itself a successful alternative to larger and more expensive commercial solutions. The dual conclusions reached were that it was possible to develop a compact low-cost, multi-channel radio frequency (RF) front-end that implicitly supported external data source synchronization, and that such monitoring systems or similar capabilities integrated within receivers are likely to be needed in the future due to the increasing occurrence rates of GNSS RFI events.

scholarly journals High-rate altimetry in SNR-based GNSS-R: Proof-of-concept of a synthetic vertical array

2021 ◽  
Author(s):  
Mauricio Kenji Yamawaki ◽  
Felipe Geremia-Nievinski ◽  
João Francisco Monico
Keyword(s):  
Sea Level ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
High Rate ◽  
Proof Of Concept ◽  
Radio Waves ◽  
Vertical Array ◽  
Remote Sensing Technique ◽  
Single Antenna ◽  
Global Navigation Satellite

Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a promising remote sensing technique for coastal sea level monitoring. The GNSS-R based on signal-to-noise ratio (SNR) observations employs a single antenna and a conventional receiver. It performs best for low elevation satellites, where direct and reflected radio waves are very similar in polarization and direction of arrival. One of the disadvantages of SNR-based GNSS-R for sea level altimetry is its low temporal resolution, which is of the order of one hour for each independent satellite pass. Here we present a proof-of-concept based on a synthetic vertical array. It exploits the mechanical movement of a single antenna at high rate (about 1 Hz). SNR observations can then be fit to a known modulation, of the order of the antenna sweeping rate. We demonstrate that centimetric altimetry precision can be achieved in a 5-minute session. [©2021 IEEE]

scholarly journals Kinematic PPP Using Mixed GPS/Glonass Single-Frequency Observations

2019 ◽  
Vol 54 (3) ◽  
pp. 97-112
Author(s):  
Mostafa Hamed ◽  
Ashraf Abdallah ◽  
Ashraf Farah
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Single Frequency ◽  
Future Research ◽  
Frequency Data ◽  
Dual Frequency ◽  
Trajectory Data ◽  
Average Improvement ◽  
Kinematic Ppp ◽  
Global Navigation Satellite

Abstract Nowadays, Precise Point Positioning (PPP) is a very popular technique for Global Navigation Satellite System (GNSS) positioning. The advantage of PPP is its low cost as well as no distance limitation when compared with the differential technique. Single-frequency receivers have the advantage of cost effectiveness when compared with the expensive dual-frequency receivers, but the ionosphere error makes a difficulty to be completely mitigated. This research aims to assess the effect of using observations from both GPS and GLONASS constellations in comparison with GPS only for kinematic purposes using single-frequency observations. Six days of the year 2018 with single-frequency data for the Ethiopian IGS station named “ADIS” were processed epoch by epoch for 24 hours once with GPS-only observations and another with GPS/GLONASS observations. In addition to “ADIS” station, a kinematic track in the New Aswan City, Aswan, Egypt, has been observed using Leica GS15, geodetic type, dual-frequency, GPS/GLONASS GNSS receiver and single-frequency data have been processed. Net_Diff software was used for processing all the data. The results have been compared with a reference solution. Adding GLONASS satellites significantly improved the satellite number and Position Dilution Of Precision (PDOP) value and accordingly improved the accuracy of positioning. In the case of “ADIS” data, the 3D Root Mean Square Error (RMSE) ranged between 0.273 and 0.816 m for GPS only and improved to a range from 0.256 to 0.550 m for GPS/GLONASS for the 6 processed days. An average improvement ratio of 24%, 29%, 30%, and 29% in the east, north, height, and 3D position components, respectively, was achieved. For the kinematic trajectory, the 3D position RMSE improved from 0.733 m for GPS only to 0.638 m for GPS/GLONASS. The improvement ratios were 7%, 5%, 28%, and 13% in the east, north, height, and 3D position components, respectively, for the kinematic trajectory data. This opens the way to add observations from the other two constellations (Galileo and BeiDou) for more accuracy in future research.

Ocean Navigation Method Based on Multi-System and Multi-Source Data Fusion

2020 ◽  
pp. 1-16
Author(s):  
Xiang Wang ◽  
Jingxian Liu ◽  
Zhao Liu
Keyword(s):  
Data Fusion ◽  
Satellite System ◽  
Single Frequency ◽  
Fusion Algorithm ◽  
Ship Maneuvering ◽  
Source Data ◽  
Huge Impact ◽  
Potential Risks ◽  
Global Navigation Satellite ◽  
Navigation Method

Ship navigation requires accurate positioning, navigation and timing (PNT) data. PNT data from a single source has uncertainties and potential risks. Wrong PNT data has a huge impact on ship maneuvering, and at the same time, it may cause huge losses to national assets and national security. This chapter proposes a data fusion algorithm based on single-frequency global navigation satellite system (GNSS) and inertial navigation system (INS) to obtain PNT data, which can improve the availability, accuracy, reliability, continuity, and robustness. The experimental results show that the data fusion method combining median filtering and Kalman filtering can improve the system's ability to acquire PNT data. When blocking GNSS acquisition of PNT data, relying on INS, you can still obtain PNT data, which can make up for the ability to obtain PNT data from GNSS.

scholarly journals Terrain changes from images acquired on opportunistic flights by SfM photogrammetry

2017 ◽  
Vol 11 (2) ◽  
pp. 827-840 ◽  
Author(s):  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb ◽  
Bernd Etzelmüller ◽  
Jack Kohler
Keyword(s):  
Low Cost ◽  
Rapid Change ◽  
Satellite System ◽  
Light Transport ◽  
Area Of Interest ◽  
Accuracy And Precision ◽  
Global Navigation Satellite ◽  
The Cost ◽  
Gnss Data

Abstract. Acquiring data to analyse change in topography is often a costly endeavour requiring either extensive, potentially risky, fieldwork and/or expensive equipment or commercial data. Bringing the cost down while keeping the precision and accuracy has been a focus in geoscience in recent years. Structure from motion (SfM) photogrammetric techniques are emerging as powerful tools for surveying, with modern algorithm and large computing power allowing for the production of accurate and detailed data from low-cost, informal surveys. The high spatial and temporal resolution permits the monitoring of geomorphological features undergoing relatively rapid change, such as glaciers, moraines, or landslides. We present a method that takes advantage of light-transport flights conducting other missions to opportunistically collect imagery for geomorphological analysis. We test and validate an approach in which we attach a consumer-grade camera and a simple code-based Global Navigation Satellite System (GNSS) receiver to a helicopter to collect data when the flight path covers an area of interest. Our method is based and builds upon Welty et al. (2013), showing the ability to link GNSS data to images without a complex physical or electronic link, even with imprecise camera clocks and irregular time lapses. As a proof of concept, we conducted two test surveys, in September 2014 and 2015, over the glacier Midtre Lovénbreen and its forefield, in northwestern Svalbard. We were able to derive elevation change estimates comparable to in situ mass balance stake measurements. The accuracy and precision of our DEMs allow detection and analysis of a number of processes in the proglacial area, including the presence of thermokarst and the evolution of water channels.

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