scholarly journals A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2551 ◽  
Author(s):  
Qifeng Lai ◽  
Hong Yuan ◽  
Dongyan Wei ◽  
Ningbo Wang ◽  
Zishen Li ◽  
...  
Keyword(s):  
Navigation System ◽  
Rapid Development ◽  
Satellite System ◽  
Urban Environments ◽  
Sensor Technology ◽  
Vehicle Navigation ◽  
Noise Compensation ◽  
Vehicle Navigation System ◽  
Tightly Coupled ◽  
Global Navigation Satellite

Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.

A Fault-Tolerant Tightly Coupled GNSS/INS/OVS Integration Vehicle Navigation System Based on an FDP Algorithm

2019 ◽  
Vol 68 (7) ◽  
pp. 6365-6378 ◽  
Author(s):  
Wei Jiang ◽  
Dan Liu ◽  
Baigen Cai ◽  
Chris Rizos ◽  
Jian Wang ◽  
...  
Keyword(s):  
Navigation System ◽  
Fault Tolerant ◽  
Vehicle Navigation ◽  
Vehicle Navigation System ◽  
Tightly Coupled

scholarly journals Implementation and Analysis of Tightly Coupled Global Navigation Satellite System Precise Point Positioning/Inertial Navigation System (GNSS PPP/INS) with Insufficient Satellites for Land Vehicle Navigation

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4305 ◽  
Author(s):  
Yue Liu ◽  
Fei Liu ◽  
Yang Gao ◽  
Lin Zhao
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Single Frequency ◽  
Vehicle Navigation ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Gps Satellites ◽  
Tightly Coupled ◽  
Gnss Measurements ◽  
Global Navigation Satellite

This paper implements and analyzes a tightly coupled single-frequency global navigation satellite system precise point positioning/inertial navigation system (GNSS PPP/INS) with insufficient satellites for land vehicle navigation using a low-cost GNSS receiver and a microelectromechanical system (MEMS)-based inertial measurement unit (IMU). For land vehicle navigation, it is inevitable to encounter the situation where insufficient satellites can be observed. Therefore, it is necessary to analyze the performance of tightly coupled integration in a GNSS-challenging environment. In addition, it is also of importance to investigate the least number of satellites adopted to improve the performance, compared with no satellites used. In this paper, tightly coupled integration using low-cost sensors with insufficient satellites was conducted, which provided a clear view of the improvement of the solution with insufficient satellites compared to no GNSS measurements at all. Specifically, in this paper single-frequency PPP was implemented to achieve the best performance, with one single-frequency receiver. The INS mechanization was conducted in a local-level frame (LLF). An extended Kalman filter was applied to fuse the two different types of measurements. To be more specific, in PPP processing, the atmosphere errors are corrected using a Saastamoinen model and the Center for Orbit Determination in Europe (CODE) global ionosphere map (GIM) product. The residuals of atmosphere errors are not estimated to accelerate the ambiguity convergence. For INS error mitigation, velocity constraints for land vehicle navigation are adopted to limit the quick drift of a MEMS-based IMU. Field tests with simulated partial and full GNSS outages were conducted to show the performance of tightly coupled GNSS PPP/INS with insufficient satellites: The results were classified as long-term (several minutes) and short-term (less than 1 min). The results showed that generally, with GNSS measurements applied, although the number of satellites was not enough, the solution still could be improved, especially with more than three satellites observed. With three GPS satellites used, the horizontal drift could be reduced to a few meters after several minutes. The 3D position error could be limited within 10 m in one minute when three GPS satellites were applied. In addition, a field test in an urban area where insufficient satellites were observed from time to time was also conducted to show the limited solution drift.

scholarly journals Fault Detection and Exclusion Method for a Deeply Integrated BDS/INS System

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1844
Author(s):  
Junren Sun ◽  
Zun Niu ◽  
Bocheng Zhu
Keyword(s):  
Fault Detection ◽  
Navigation System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Vector Tracking ◽  
Tightly Coupled ◽  
Tracking Loops ◽  
Deep Integration ◽  
Navigation Service ◽  
Global Navigation Satellite

The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture has better tracking and positioning performance. Information is shared among channels, and the assistant information from INS helps to reduce the dynamic stress of tracking loops. However, this vector tracking architecture may result in easy propagation of errors among tracking channels. To solve this problem, a Fault Detection and Exclusion (FDE) method for the deeply integrated BeiDou Navigation Satellite System (BDS)/INS navigation system is proposed in this paper. This method utilizes pre-filters’ outputs and integration filter’s estimations to form test statistics. These statistics can help to detect and exclude both step errors and Slowly Growing Errors (SGEs) correctly. The monitoring capability of the method was verified by a simulation which was based on a software receiver. The simulation results show that the proposed FDE method works effectively. Additionally, the method is convenient to be implemented in real-time applications because of its simplicity.

Simple GPS Automatic Navigation Design

2014 ◽  
Vol 1044-1045 ◽  
pp. 1545-1548
Author(s):  
Hao Wang ◽  
Dian Ren Chen
Keyword(s):  
Navigation System ◽  
Rapid Development ◽  
Vehicle Navigation ◽  
Gps Navigation ◽  
Hardware System ◽  
Automatic Navigation ◽  
Vehicle Navigation System ◽  
Quality Technology ◽  
Gps Products ◽  
Embedded Development

GPS vehicle navigation technology is the GPS technology emerges along with the rapid development of embedded technology, the auto industry, the market ofmore variety of products GPS navigation based on quality, technology gap, doesa variety of GPS products. This paper analyzes the development status ofdomestic and foreign vehicle navigation system at present, the GPS vehicle navigation system was discussed, to construct the hardware system based on embedded development board as the core, build of the vehicle navigation systembased on WinCE, using EVC and eSuperMap tool software, design of intelligent navigation system the electronic navigation maproute search.

scholarly journals Investigation of GIM-TEC disturbances before M ≥ 6.0 inland earthquakes during 2003–2017

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fuying Zhu ◽  
Yingchun Jiang
Keyword(s):  
Rapid Development ◽  
Science Research ◽  
Satellite System ◽  
Statistical Investigation ◽  
Electron Content ◽  
Total Electron ◽  
Spatial And Temporal Distributions ◽  
Before And After ◽  
Global Ionosphere Map ◽  
Global Navigation Satellite

Abstract With the rapid development of the Global Navigation Satellite System (GNSS) and its wide applications to atmospheric science research, the global ionosphere map (GIM) total electron content (TEC) data are extensively used as a potential tool to detect ionospheric disturbances related to seismic activity and they are frequently used to statistically study the relation between the ionosphere and earthquakes (EQs). Indeed, due to the distribution of ground based GPS receivers is very sparse or absent in large areas of ocean, the GIM-TEC data over oceans are results of interpolation between stations and extrapolation in both space and time, and therefore, they are not suitable for studying the marine EQs. In this paper, based on the GIM-TEC data, a statistical investigation of ionospheric TEC variations of 15 days before and after the 276 M ≥ 6.0 inland EQs is undertaken. After eliminating the interference of geomagnetic activities, the spatial and temporal distributions of the ionospheric TEC disturbances before and after the EQs are investigated and compared. There are no particularly distinct features in the time distribution of the ionospheric TEC disturbances before the inland EQs. However, there are some differences in the spatial distribution, and the biggest difference is precisely in the epicenter area. On the other hand, the occurrence rates of ionospheric TEC disturbances within 5 days before the EQs are overall higher than those after EQs, in addition both of them slightly increase with the earthquake magnitude. These results suggest that the anomalous variations of the GIM-TEC before the EQs might be related to the seismic activities.

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