ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	Optimization and Comparison of Two Data Fusion Algorithms for an Inertial Measurement Unit
Authors	:	S.A.Quadri, Othman Sidek
Keywords	:	Data fusion; algorithm ; inertial measurement unit; Kalman filter; functional programming
Issue Date	:	July 2013
Abstract	:	Data fusion is a multilevel and multifaceted process that deals with the combination of data and information from single and multiple sources to achieve enhanced accuracy and precision. Development of algorithm plays significant role in the performance of data fusion system. We present two algorithms to fuse the data obtained from an accelerometer and gyroscope in an inertial measurement unit (IMU). First, we employ well-known Kalman filter algorithm and then we propose a new algorithm, namely decentralized data fusion algorithm based on Factor analysis model. After comparing the performance of both the algorithms, we switch our study to optimize the code. Matlab profiler carries out comparison and analysis. The code is optimized to speed up the execution time.
Page(s)	:	73-80
ISSN	:	2319-7323
Source	:	Vol. 2, No.4