earticle

영어

Multisensor data fusion aims to overcome the limitations of individual sensors and produce accurate, robust and reliable estimates based on multisensory information. Data fusion algorithm plays significant role in achieving reasonable performance. In this paper, we present an algorithm that is employed to fuse data obtained from accelerometer and gyroscope in an inertial measurement unit (IMU). The proposed algorithm is developed based on decentralized data fusion notion that facilitates to study effect of noise parameter associated with individual sensors. Feature extraction and processing is accomplished using factor analysis model. Factor analysis is a statistical method used to study the effect and interdependence of various factors within a system. The performance of the algorithm is illustrated via computer simulations and compared with well-known Kalman filter algorithm.