Decentralized Data Fusion Algorithm Using Factor Analysis Model

Abstract

Multi-sensor data fusion provides significant advantages over single source data to achieve an improved accuracy and better precision. Decentralized data fusion approach is one in which features are extracted and processed individually and finally fused to obtain global estimates. The paper presents decentralized data fusion algorithm using factor analysis model. Factor analysis is a statistical method used to study the effect and interdependence of various factors within a system. The proposed algorithm fuses accelerometer and gyroscope data in an inertial measurement unit (IMU). Simulations are carried out on Matlab platform to illustrate the algorithm.