GNSS/INS Integration in Urban Areas
The Satellite based navigation systems are often integrated with inertial navigation
systems in order to provide greater accuracy and reliability in the position
and velocity parameters. For this purpose high quality inertial sensors are used
which can provide real-time navigation at centimeter level. Price, size and weight
of traditional INS has been a problem which has been solved successfully by the
use of Micro Electro Mechanical Sensors (MEMS). The problem with the MEMS
technology is the large error which grows rapidly and degrade the performance
of the navigation system. Different methods are used to calculate the error coefficients
(not implemented in this study work) which are further used in a kalman
filter in order to enhance the performance of the system. Thus a kalman filter
has been introduced to perform the data fusion algorithms. Kalman filtering is a
recursive technique used to optimize the state vector of the estimates and it efficiently
provides the navigation estimates of a dynamic system. All the navigation
data used in this thesis work has been provided by my supervisor, professor Jon
Glenn Gjevestad (UMB). A real-time system has been tested in the urban areas
for different scenarios. Kalman filter approach with loose integration has been implemented.
A comparison of the filtered solution with the reference positions has
been made by introducing a 2D horizontal position error in order to analyze the
position accuracy. In the end some recommendations on future work are courted.
Place, publisher, year, edition, pages
Institutt for elektronikk og telekommunikasjon , 2014. , 116 p.
IdentifiersURN: urn:nbn:no:ntnu:diva-24948Local ID: ntnudaim:10101OAI: oai:DiVA.org:ntnu-24948DiVA: diva2:726195
Gjevestad, Jon Glenn Omholt, Professor II