A Hybrid System for World-wide Navigation

1970 ◽  
Vol 23 (1) ◽  
pp. 26-44 ◽  
Author(s):  
F. S. Stringer
Keyword(s):  
Navigation System ◽  
Short Range ◽  
World Wide ◽  
Dead Reckoning ◽  
Satellite System ◽  
System Study ◽  
Sources Of Information ◽  
Multiple Sensors ◽  
Omega System ◽  
System Operating

In 1963, in addition to examining the characteristics of the Omega system, we were also very concerned with a comprehensive navigation system study which was designed to examine all aspects of a world-wide navigation system operating in a B.O.A.C. type environment. This concerned a study of dead reckoning as well as externally referenced sources of information. You have the choice of an all dead reckoning system probably employing multiple sensors of the same type, triple IN is typical, or you could have a mixture of externally referenced and self-contained, in other words dead reckoning sensors. Occasional reference could be made to short-range aids or even a satellite system if available to increase the integrity of the position-fixing information. The inertial and computer aspects have been examined by the Avionics Department at R.A.E. whereas the radio sensors, which are externally referenced, and the relevant software have been the responsibility of the Radio Department.

scholarly journals Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; GNSS/IMU Case Study

2018 ◽  
Author(s):  
Siavash Hosseinyalamdary
Keyword(s):  
Kalman Filter ◽  
Satellite System ◽  
Measurement Unit ◽  
Sources Of Information ◽  
Error Sources ◽  
Multiple Sensors ◽  
Efficient Integration ◽  
Global Navigation Satellite ◽  
Gnss Observations

The Bayes filters, such as Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of the unknowns. Efficient integration of multiple sensors requires deep knowledge of their error sources and it is not trivial for complicated sensors, such as Inertial Measurement Unit (IMU). Therefore, IMU error modelling and efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we develop deep Kalman filter to model and remove IMU errors and consequently, improve the accuracy of IMU positioning. In other words, we add modelling step to the prediction and update steps of Kalman filter and the IMU error model is learned during integration. Therefore, our deep Kalman filter outperforms Kalman filter and reaches higher accuracy.

scholarly journals Indoor and Outdoor Low-Cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System

2020 ◽  
Vol 12 (19) ◽  
pp. 3271
Author(s):  
Ningbo Li ◽  
Lianwu Guan ◽  
Yanbin Gao ◽  
Shitong Du ◽  
Menghao Wu ◽  
...  
Keyword(s):  
Navigation System ◽  
Low Cost ◽  
Dead Reckoning ◽  
Satellite System ◽  
Outdoor Environment ◽  
Mode Switching ◽  
Integrated Navigation ◽  
Switching Algorithm ◽  
Navigation Algorithm ◽  
Indoor And Outdoor

Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.

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 Lane Detection Aided Online Dead Reckoning for GNSS Denied Environments

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6805
Author(s):  
Jinhwan Jeon ◽  
Yoonjin Hwang ◽  
Yongseop Jeong ◽  
Sangdon Park ◽  
In So Kweon ◽  
...  
Keyword(s):  
Navigation System ◽  
Autonomous Vehicles ◽  
Computing Time ◽  
Dead Reckoning ◽  
Satellite System ◽  
Lane Detection ◽  
Urban Streets ◽  
Detection Model ◽  
Linearization Errors ◽  
Global Navigation Satellite

With the emerging interest of autonomous vehicles (AV), the performance and reliability of the land vehicle navigation are also becoming important. Generally, the navigation system for passenger car has been heavily relied on the existing Global Navigation Satellite System (GNSS) in recent decades. However, there are many cases in real world driving where the satellite signals are challenged; for example, urban streets with buildings, tunnels, or even underpasses. In this paper, we propose a novel method for simultaneous vehicle dead reckoning, based on the lane detection model in GNSS-denied situations. The proposed method fuses the Inertial Navigation System (INS) with learning-based lane detection model to estimate the global position of vehicle, and effectively bounds the error drift compared to standalone INS. The integration of INS and lane model is accomplished by UKF to minimize linearization errors and computing time. The proposed method is evaluated through the real-vehicle experiments on highway driving, and the comparative discussions for other dead-reckoning algorithms with the same system configuration are presented.

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.

Studies of the integrated navigation system correction in the absence of a satellite signal

2021 ◽  
Author(s):  
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Operation Mode ◽  
Satellite System ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Correction Signal ◽  
Satellite Signal ◽  
Navigation Information

The schemes of navigation systems correction are considered. The operation mode of the aircraft during navigation is analyzed. An adaptive modification of the linear Kalman filter is used to correct the navigation information. An algorithm for predicting a correction signal based on a neural network in the event of a loss of a SNS correction signal is formed. Experimental results show the effectiveness of the algorithm. Keywords aircraft; inertial navigation system; satellite system; Kalman filter; neural networks; genetic algorithm

scholarly journals Multi-Radio Integrated Navigation System M&S Software Design for GNSS Backup under Navigation Warfare

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 188 ◽  
Author(s):  
Heyone Kim ◽  
Junhak Lee ◽  
Sang Heon Oh ◽  
Hyoungmin So ◽  
Dong-Hwan Hwang
Keyword(s):  
Software Design ◽  
Navigation System ◽  
Design Method ◽  
Satellite System ◽  
Navigation Satellite ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Very High Frequency ◽  
Integrated Navigation System ◽  
Function Modules

To avoid degradation of navigation performance in the navigation warfare environment, the multi-radio integrated navigation system can be used, in which all available radio navigation systems are integrated to back up Global Navigation Satellite System (GNSS) when the GNSS is not available. Before real-time multi-radio integrated navigation systems are deployed, time and cost can be saved when the modeling and simulation (M&S) software is used in the performance evaluation. When the multi-radio integrated navigation system M&S is comprised of independent function modules, it is easy to modify and/or to replace the function modules. In this paper, the M&S software design method was proposed for multi-radio integrated navigation systems as a GNSS backup under the navigation warfare. The M&S software in the proposed design method consists of a message broker and function modules. All the messages were transferred through the message broker in order to be exchanged between the function modules. The function modules in the M&S software were independently operated due to the message broker. A message broker-based M&S software was designed for a multi-radio integrated navigation system. In order to show the feasibility of the proposed design method, the M&S software was implemented for Global Positioning System (GPS), Korean Navigation Satellite System (KNSS), enhanced Long range navigation (eLoran), Loran-C, and Distance Measuring Equipment/Very high-frequency Omnidirectional Radio range (DME/VOR). The usefulness of the proposed design method was shown by checking the accuracy and availability of the GPS only navigation and the multi-radio integrated navigation system under the attack of jamming to GPS.

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