Teena Abbas Ali; Ahmed Mudheher Hasan
Volume 20, Issue 4 , October 2020, , Page 58-70
Abstract
Autonomous vehicle navigation has witnessed a huge revolutionary revision regarding development in Micro-Electro Mechanical System (MEMS) technology. Most recently, Strapdown Inertial Navigation System (SDINS) has successfully been integrated with Global Positioning System (GPS). However, different grades ...
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Autonomous vehicle navigation has witnessed a huge revolutionary revision regarding development in Micro-Electro Mechanical System (MEMS) technology. Most recently, Strapdown Inertial Navigation System (SDINS) has successfully been integrated with Global Positioning System (GPS). However, different grades of MEMS inertial sensors are available and choosing the convenient grade is quite important. Noises in inertial sensor are mostly treated through de-noising the additive errors to improve the precision of SDINS output. Unfortunately, integration in SDINS mechanization causes a growing in SDINS error output which considered the main challenge in integrating MEMS inertial sensors with GPS. This paper aims to promote the long-term performance of the MEMS-SDINS/GPS integrated system. A new integrated structure is proposed to model the nonlinearities that exist in SDINS dynamics in addition to the error uncertainty in the inertial sensors’ measurements. A robust Nonlinear AutoRegressive models with eXogenous inputs (NARX) based algorithm are designed for data fusion in the proposed GPS/INS integrated system. Validation for the proposed integrated system has been carried out using different field tests data in order to assess the accuracy of the system during GPS denied environment. The results obtained demonstrate that the proposed NARX model is applicative and satisfactory which shows a desired prediction performance.
Farah F. Alkhalid; Bashra Kadhim Oleiwi
Volume 19, Issue 1 , January 2019, , Page 82-87
Abstract
This study focuses on the design of an autonomous wheelchair basedsmart driving features for disabled persons. The movement directions andposition tracking of the wheelchair are controlled and localized by pre-definedvoice commands and global positioning system (GPS), respectively. Arduinomicrocontroller ...
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This study focuses on the design of an autonomous wheelchair basedsmart driving features for disabled persons. The movement directions andposition tracking of the wheelchair are controlled and localized by pre-definedvoice commands and global positioning system (GPS), respectively. Arduinomicrocontroller based on speaker dependent voice recognition module andtracking system based on quad-board SIM808 has been used to help thewheelchair navigation. The experimental tests of the proposed system have beendone and given satisfactory results in controlling the wheelchair and making acall on demand. Hence the proposed system is a simple, easy to use and lowcosthardware for designing.
Ali F. Lutfy; Ahmed M. Hassan; Salam A. Ismaeel
Volume 9, Issue 1 , December 2009, , Page 116-130
Abstract
Abstract:
Global Positioning System (GPS) and Strap down Inertial Navigation System (SDINS) can be Integrated Together To Provide A Reliable Navigation System. In This Paper, A Technique For Error Estimation In A GPS/INS System Based On A Low-Cost Inertial Measurement Unit (IMU) Is Offered. This Technique ...
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Abstract:
Global Positioning System (GPS) and Strap down Inertial Navigation System (SDINS) can be Integrated Together To Provide A Reliable Navigation System. In This Paper, A Technique For Error Estimation In A GPS/INS System Based On A Low-Cost Inertial Measurement Unit (IMU) Is Offered. This Technique Is Composed Of Wavelet Transform (WT) And Adaptive Fuzzy System (AFS). The Wavelet Decomposition Is Used To De-Noise The Position And Velocity Components Of The GPS And INS Outputs. An AFS Is Introduced In This Paper To Estimate The Position And Velocity Errors In The Integrated System In Order To Provide Accurate Navigation Information About The Moving Vehicle.
Several Data Sets Are Processed In This Paper, Where The Simulation Results Are Based On Matlab7 Programming Language. Six AFS Networks Are Used To Process The Position And Velocity Components. The Average Error Value Per Sample Was 0.0142, 0.0443, And 0.0108 M For Position In X, Y, And Z Axes Respectively And 0.0077, 0.0223, And 0.0269 M/S For Velocity In North, East, And Down Directions Respectively
Mr. AHMED MUDHER HASSAN
Volume 8, Issue 1 , December 2008, , Page 67-78
Abstract
Abstract:
The integration of global positioning system (GPS) and Inertial Navigation System (INS) are continuously gaining interests in many positioning and navigation applications. Both systems have their unique features and shortcomings. Their integration offers systems that overcome each of their ...
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Abstract:
The integration of global positioning system (GPS) and Inertial Navigation System (INS) are continuously gaining interests in many positioning and navigation applications. Both systems have their unique features and shortcomings. Their integration offers systems that overcome each of their drawbacks and maximize each of their benefits. An INS/GPS integration method based on Artificial Neural Networks (ANNs) to fuse INS measurements and GPS measurements has been suggested. It is also provide high performance INS/GPS integration with accurate prediction for position
And velocity components during GPS signal absence. Thus the integration of the two systems presents a number of advantages and overcomes each systems inadequacy. An ANN was adopted in this paper using position and velocity update architectures and utilizing the window based weight updating strategy to updates the navigation knowledge in the strategy using two data test IMU systems.
Ali Farouq; Mr. Ahmed M. Hassan; Salam A. Ismaeel
Volume 7, Issue 2 , December 2007, , Page 21-34
Abstract
Abstract:
Over time, inertial navigators drift from their preset alignments. Or, the initial alignment may have been corrupted by vehicle motion, with imperfect transfer of alignment and velocities to the navigator. Also, there may not have been enough time to perfect alignment. In such case, navigators ...
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Abstract:
Over time, inertial navigators drift from their preset alignments. Or, the initial alignment may have been corrupted by vehicle motion, with imperfect transfer of alignment and velocities to the navigator. Also, there may not have been enough time to perfect alignment. In such case, navigators can be benefit from aiding such as GPS.
So that, the combination of GPS and INS has become increasingly common in the past few years, because the characteristics of GPS and INS are complementary.
The integration between the GPS and INS leads to accurate navigation solution by overcoming each of their respective shortcomings. And to make this integration possible the difference between the GPS and INS systems in sampling rate must be solved before any integration can be work properly.
