scholarly journals UAV Dead Reckoning with and without using INS/GPS Integrated System in GPS denied Polar Regions

2019 ◽  
Vol 1 (2) ◽  
pp. 58-67
Author(s):  
Ali Kissai ◽  
Milton Smith
Keyword(s):  
Dead Reckoning ◽  
Integrated System ◽  
Polar Regions

A Kalman Filter Model for an Integrated Land Vehicle Navigation System

1995 ◽  
Vol 48 (2) ◽  
pp. 293-302 ◽  
Author(s):  
Allison N. Ramjattan ◽  
Paul A. Cross
Keyword(s):  
Dead Reckoning ◽  
Integrated System ◽  
Vehicle Navigation ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Filter Model ◽  
Land Vehicle ◽  
Land Vehicle Navigation ◽  
Vehicle Navigation System ◽  
Vehicle Position

Unlike in the case of airborne and offshore applications, GPS cannot be used continuously for land vehicle navigation due to the loss of satellite signals by obstructions from buildings, trees, etc. With the increasing trend in various sectors of the economy towards efficient fleet management, the challenges of providing a system capable of providing high-accuracy vehicle position and location anywhere, continuously, has led to renewed interest in the area of integrated navigation systems. In order to satisfy these conditions, an integrated system comprising GPS and gyro/odometer dead reckoning has been developed. This paper gives a description of the implemented system and shows some of the practical results that can be obtained using Kalman filtering algorithms.

Application of Kalman Filter Technology to Integrated INS/DR Navigation System for Land Vehicle

2013 ◽  
Vol 411-414 ◽  
pp. 912-916 ◽  
Author(s):  
Ying Chen ◽  
Xia Jiang Zhang ◽  
Yuan Yuan Xue ◽  
Zhen Kang ◽  
Ting Shang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Dead Reckoning ◽  
Position Error ◽  
Integrated System ◽  
Integrated Navigation ◽  
Integrated Navigation System ◽  
Attitude Error ◽  
Result Show ◽  
The Difference

Strap-down INS is composed of fiber gyroscope. Position error propagation equation and position update algorithm of dead reckoning is deduced in this paper. The Kalman filter is proposed for compensation error of integrated system. The difference of velocity between INS and DR is used as the input of Kalman filter, attitude error, velocity error, position error and scale factor error are to be estimated which compensate and rectify the errors of integrated navigation system. By carrying out experiment upon vehicular navigation system in use of Kalman filter, the errors of integrated navigation system are estimated accurately. Experiment result show that the method not only can effectively improve precision of the system, but also is simple and convenient, so it is more suitable for practical application.

A Route Direction-finder

1960 ◽  
Vol 13 (2) ◽  
pp. 191-195
Author(s):  
Colonel P. Gaudillère
Keyword(s):  
Autonomous Systems ◽  
Dead Reckoning ◽  
Great Circle ◽  
Magnetic Compass ◽  
Polar Regions ◽  
Automatic Navigation ◽  
Direction Finder ◽  
Continuous Waves ◽  
Route Direction ◽  
Paris Convention

The route direction-finder is a device giving an accurate directional reference. It uses two distant transmitters, A and B, radiating two continuous waves, the frequencies of which are different but very proximate. The paper was presented at the Paris convention on automatic navigation.Classical methods of navigation by dead reckoning have been considerably improved in recent years by the use of autonomous systems such as doppler and inertia which enable true speed to be measured. When using these systems, the principal cause of errors is the unreliability of the directional reference, which may be the meridian or any arc of a great circle, since it is with respect to this that the speed vector is obtained. The directional reference is given by the magnetic compass which often has an error of up to several degrees or is given by gyroscopic devices which can have considerable drift after several hours' operation. Errors in directional reference are especially marked in polar regions where magnetic or gyro compasses cannot be used.

scholarly journals A Real-Time BLE/PDR Integrated System by Using an Improved Robust Filter for Indoor Position

2021 ◽  
Vol 11 (17) ◽  
pp. 8170
Author(s):  
Shenglei Xu ◽  
Yunjia Wang ◽  
Meng Sun ◽  
Minghao Si ◽  
Hongji Cao
Keyword(s):  
Real Time ◽  
High Precision ◽  
Dead Reckoning ◽  
Integrated System ◽  
Gross Error ◽  
True Position ◽  
Time Position ◽  
Heading Angle ◽  
The Mean ◽  
Pedestrian Dead Reckoning

Indoor position technologies have attracted the attention of many researchers. To provide a real-time indoor position system with high precision and stability is necessary under many circumstances. In a real-time position scenario, gross errors of the Bluetooth low energy (BLE) fingerprint method are more easily occurring and the heading angle of the pedestrian will drift without acceleration and magnetic field compensation. A real-time BLE/pedestrian dead-reckoning (PDR) integrated system by using an improved robust filter has been proposed. In the PDR method, the improved Mahony complementary filter based on the pedestrian motion states is adopted to estimate the heading angle reducing the drift error. Then, an improved robust filter is utilized to detect and restrain the gross error of the BLE fingerprint method. The robust filter detected the gross error at different granularity by constructing a robust vector changing the observation covariance matrix of the extended Kalman filter (EKF) adaptively when the application is running. Several experiments are conducted in the true position scenario. The mean position accuracy obtained by the proposed method in the experiment is 0.844 m and RMSE is 0.74 m. Compared with the classic EKF, these two values are increased by 38% and 18%, respectively. The results show that the improved filter can avoid the gross error in the BLE method and provide high precision and scalability in indoor position service.

scholarly journals An integrated positioning system for the Toronto Transit System

2021 ◽  
Author(s):  
Mahmoud Salem I.S. Abd El-Gelil
Keyword(s):  
System Design ◽  
Dead Reckoning ◽  
Field Tests ◽  
Integrated System ◽  
Positioning System ◽  
Transit System ◽  
Hybrid Positioning ◽  
Bus Service ◽  
And Performance ◽  
Signpost System

In this thesis, a hybrid positioning system is developed, which combines GPS, Dead Reckoning (DR) and Signpost technologies for the purpose of improving the Toronto Transit System bus service. The DR system is used as the main positioning system, while GPS and Signpost systems are used as aiding systems to compensate for the DR errors. The integration is done in the position domain, which simplifies the system design. A centralized Kalman filter with five states is developed to combine all the available measurements. Field tests have been designed and conducted to assess the system design and performance under various environmental conditions. It is shown that the achieved positioning accuracy of the integrated DR/GPS/Signpost system is at the few metres level in unobstructed environments. In addition, despite the signal obstruction in the downtown area, the positioning solution of the integrated system is still sufficiently precise.

scholarly journals Research on the Integrated Navigation Technology of SINS with Couple Odometers for Land Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 546
Author(s):  
Jiaxin Gao ◽  
Kui Li ◽  
Jiyang Chen
Keyword(s):  
Navigation System ◽  
Dead Reckoning ◽  
Integrated System ◽  
Integrated Navigation ◽  
Fiber Optic Gyroscope ◽  
Velocity Difference ◽  
Positioning Accuracy ◽  
Integrated Navigation System ◽  
Positioning Errors ◽  
Over Time

Autonomous and accurate acquisition of the position and azimuth of the vehicle is critical to the combat effectiveness of land-fighting vehicles. The integrated navigation system, consisting of a strap-down inertial navigation system (SINS) and odometer (OD), is commonly applied in vehicles. In the SINS/OD integrated system, the odometer is installed around the vehicle’s wheel, while SINS is usually installed on the base of the vehicle. The distance along SINS and OD would cause a velocity difference when the vehicle maneuvers, which may lead to a significant influence on the integration positioning accuracy. Furthermore, SINS navigation errors, especially azimuth error, would diverge over time due to gyro drifts and accelerometer biases. The azimuth error would cause the divergence of dead-reckoning positioning errors with the distance that the vehicle drives. To solve these problems, an integrated positioning and orientation method based on the configuration of SINS and couple odometers was proposed in this paper. The proposed method designed a high precision integrated navigation algorithm, which compensated the lever arm effect to eliminate the velocity difference between SINS and odometers. At the same time, by using the measured information of couple odometers, azimuth reference was calculated and used as an external measurement to suppress SINS azimuth error’s divergence over time, thus could further improve the navigation precision of the integrated system, especially the orientation accuracy. The performance of the proposed method was verified by simulations. The results demonstrated that SINS/2ODs integrated system could achieve a positioning accuracy of 0.01% D (total mileage) and orientation accuracy of ±30″ by using SINS with 0.01°/h Fiber-Optic Gyroscope (FOGs) and 50 µg accelerometers.

scholarly journals An Extended Kalman Filter Algorithm for Integrating GPS and Low Cost Dead Reckoning System Data for Vehicle Performance and Emissions Monitoring

2003 ◽  
Vol 56 (2) ◽  
pp. 257-275 ◽  
Author(s):  
L. Zhao ◽  
W. Y. Ochieng ◽  
M. A. Quddus ◽  
R. B. Noland
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
Dead Reckoning ◽  
Integrated System ◽  
Vehicle Performance ◽  
Performance And Emissions ◽  
System Data ◽  
Kalman Filter Algorithm ◽  
Filter Algorithms

This paper describes the features of an extended Kalman filter algorithm designed to support the navigational function of a real-time vehicle performance and emissions monitoring system currently under development. The Kalman filter is used to process global positioning system (GPS) data enhanced with dead reckoning (DR) in an integrated mode, to provide continuous positioning in built-up areas. The dynamic model and filter algorithms are discussed in detail, followed by the findings based on computer simulations and a limited field trial carried out in the Greater London area. The results demonstrate that use of the extended Kalman filter algorithm enables the integrated system employing GPS and low cost DR devices to meet the required navigation performance of the device under development.

scholarly journals An integrated positioning system for the Toronto Transit System

2021 ◽  
Author(s):  
Mahmoud Salem I.S. Abd El-Gelil
Keyword(s):  
System Design ◽  
Dead Reckoning ◽  
Field Tests ◽  
Integrated System ◽  
Positioning System ◽  
Transit System ◽  
Hybrid Positioning ◽  
Bus Service ◽  
And Performance ◽  
Signpost System

In this thesis, a hybrid positioning system is developed, which combines GPS, Dead Reckoning (DR) and Signpost technologies for the purpose of improving the Toronto Transit System bus service. The DR system is used as the main positioning system, while GPS and Signpost systems are used as aiding systems to compensate for the DR errors. The integration is done in the position domain, which simplifies the system design. A centralized Kalman filter with five states is developed to combine all the available measurements. Field tests have been designed and conducted to assess the system design and performance under various environmental conditions. It is shown that the achieved positioning accuracy of the integrated DR/GPS/Signpost system is at the few metres level in unobstructed environments. In addition, despite the signal obstruction in the downtown area, the positioning solution of the integrated system is still sufficiently precise.

Ship Recognition by Integration of SAR and AIS

2012 ◽  
Vol 65 (2) ◽  
pp. 323-337 ◽  
Author(s):  
Sudhir Kumar Chaturvedi ◽  
Chan-Su Yang ◽  
Kazuo Ouchi ◽  
Palanisamy Shanmugam
Keyword(s):  
Dead Reckoning ◽  
Warning System ◽  
Integrated System ◽  
Tokyo Bay ◽  
Automatic Identification ◽  
Identification System ◽  
Sar Image ◽  
Ship Recognition ◽  
Matching Criteria ◽  
Integrated System Design

A novel design of an integrated system using Synthetic Aperture Radar (SAR) image and Automatic Identification System (AIS) data is proposed in this paper for the purpose of identifying ships at sea. TerraSAR-X® (SpotLight mode) images and AIS data collected over Incheon Port (Korea) and Tokyo Bay (Japan) were used on different dates. Four main steps for integration of SAR and AIS based ships can be identified, namely: ‘Time Matching’ to retrieve the respective Dead Reckoning (DR) position of the ships at SAR image acquisition times; ‘Position Matching’ based on a nearest neighbourhood re-sampling method with compensation of position shift; ‘Size Matching’ and ‘Speed Matching’. Under each of the matching criteria, the measurement error in each of the matching criteria was found to be less than 20% and the SAR extracted ship's hull boundaries were presented on a screen to display the system results. The results of this study will contribute to the design a Near-Real-Time (NRT) operational system for ship detection, identification, and classification by SARs in different data acquisition modes over various geographical locations at different acquisition times. This novel integrated system design will provide a most important preliminary step towards integration based on ships' hull monitoring in order to recognize ‘friend’ and ‘foe’ ship targets over a huge oceanic region and would be useful for coast guards as an early warning system.

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