Deeply coupled GPS/INS integration using adaptive prediction filter

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...

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Format:	Thesis
Language:	English
Subjects:	Inertial navigation systems Global Positioning System (GPS) Coordinate systems Inertial Navigation System (INS)
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/4/Younis%20H%20Karim.pdf
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id	my-unimap-72604
record_format	uketd_dc
spelling	my-unimap-726042022-11-24T06:44:32Z Deeply coupled GPS/INS integration using adaptive prediction filter R. Badlishah, Ahmad, Prof. Dr. 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. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72604 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/1/Page%201-24.pdf c1022338b0d2a7cf7db8afaf20082b90 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/2/Full%20text.pdf 38e20164b4d7c24fcdb559edd3777aef http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/4/Younis%20H%20Karim.pdf b23369450b97c83ff8405aee713a30e1 Universiti Malaysia Perlis (UniMAP) Inertial navigation systems Global Positioning System (GPS) Coordinate systems Inertial Navigation System (INS) School of Computer and Communication Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	R. Badlishah, Ahmad, Prof. Dr.
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) Deeply coupled GPS/INS integration using adaptive prediction filter
description	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.
format	Thesis
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
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Computer and Communication Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72604/4/Younis%20H%20Karim.pdf
_version_	1776104224656982016

Deeply coupled GPS/INS integration using adaptive prediction filter

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