Deeply coupled GPS/INS integration using adaptive prediction filter
Doctor of Philosophy in Computer Engineering
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2016
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72604 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.unimap-72604 |
|---|---|
| record_format |
dspace |
| spelling |
my.unimap-726042022-11-24T06:44:32Z Deeply coupled GPS/INS integration using adaptive prediction filter Younis H. Karim, Al-Jewari R. Badlishah, Ahmad, Prof. Dr. Inertial navigation systems Global Positioning System (GPS) Coordinate systems Inertial Navigation System (INS) Doctor of Philosophy in Computer Engineering Most applications using Global Positioning System (GPS) require constant, highly accurate navigation data with available satellite signals. GPS error sources can lead to reduction in accuracy of navigational information relevant to position, velocity, and attitude. For this reason, the integration of GPS and Inertial Navigation System (INS) produces a high-precision navigation system. In spite of considerable progress in recent years, it is still possible to improve the performance of this integration system. This thesis addressed Deeply Coupled GPS/INS Integration method based on using Adaptive Prediction Filter (APF) to increase accuracy and reliability of navigation data to mitigate effects of data collection errors. The main problem is outage or weakness of the GPS signal. There are several reasons for the outage of GPS signals, such as tunnels, high-rise buildings, urban canyons, heavy foliage, and high mountains. Reasons for weakness in a GPS signal include multipath signals, tropospheric effects, satellite orbit changes, etc. Represented in this thesis are the simulation and analysis of the INS system and its errors with detail components of X-axis, Y-axis, and Z-axis acceleration and velocity components, and INS performance in Euler angles (pitch, roll, and yaw) to find the attitude of a rigid body. Simulation and analysis of GPS with errors in latitude, longitude, and height and also represented here. Simulation trajectory for a vehicle on a banked figure-eight track has been proposed in this research. 2016 2021-10-22T02:55:24Z 2021-10-22T02:55:24Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72604 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering |
| institution |
Universiti Malaysia Perlis |
| building |
UniMAP Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Malaysia Perlis |
| content_source |
UniMAP Library Digital Repository |
| url_provider |
http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Inertial navigation systems Global Positioning System (GPS) Coordinate systems Inertial Navigation System (INS) |
| spellingShingle |
Inertial navigation systems Global Positioning System (GPS) Coordinate systems Inertial Navigation System (INS) Younis H. Karim, Al-Jewari Deeply coupled GPS/INS integration using adaptive prediction filter |
| description |
Doctor of Philosophy in Computer Engineering |
| author2 |
R. Badlishah, Ahmad, Prof. Dr. |
| author_facet |
R. Badlishah, Ahmad, Prof. Dr. Younis H. Karim, Al-Jewari |
| format |
Thesis |
| author |
Younis H. Karim, Al-Jewari |
| author_sort |
Younis H. Karim, Al-Jewari |
| title |
Deeply coupled GPS/INS integration using adaptive prediction filter |
| title_short |
Deeply coupled GPS/INS integration using adaptive prediction filter |
| title_full |
Deeply coupled GPS/INS integration using adaptive prediction filter |
| title_fullStr |
Deeply coupled GPS/INS integration using adaptive prediction filter |
| title_full_unstemmed |
Deeply coupled GPS/INS integration using adaptive prediction filter |
| title_sort |
deeply coupled gps/ins integration using adaptive prediction filter |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2016 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72604 |
| _version_ |
1753972980977762304 |
| score |
13.222552 |