Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/3069
Title: Multi Sensor Data Fusion for Land Vehicle Navigation
Authors: Singha, Arindam
Supervisor: Ghosh, Smarajit
Karar, Vinod
Keywords: Multi Sensor;Land Vehicle Navigation;Data Fusion;Kalman Filter
Issue Date: 26-Aug-2014
Abstract: Navigation is a tool, which has gained popularity for land vehicles in recent years. However, achieving navigation with high accuracy is still a desire to be accomplished. In pursuit of achieving this goal in a low cost budget multi-sensor data fusion has been seen as a promising solution. The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The estimation accuracy of a lowcost inertial navigation system (INS) is limited by the accuracy of the used sensors and the imperfect mathematical modelling of the error sources. By fusing the INS data with GPS data, the errors can be bounded and the accuracy increases considerably. For fusion of data and minimization of error a Kalman filter based approach has been developed in this work. The work puts forward a cost benefit solution for achieving accurate navigation through sensor fusion.
Description: M.E. THESIS
URI: http://hdl.handle.net/10266/3069
Appears in Collections:Masters Theses@EIED

Files in This Item:
File Description SizeFormat 
3069.pdf1.48 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.