Thesis Type: Postgraduate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics Engineering, Turkey
Approval Date: 2015
Student: MELİH DOĞAN
Co-Supervisor: ALİ ÖZGÜR YILMAZ, UMUT ORGUNERAbstract:
In this study, first, received signal strength (RSS) based indoor localization and tracking techniques including maximum likelihood estimation (MLE), Kalman Filter (KF), serial and parallel extended Kalman Filter (EKF) are investigated and their performances compared to each other via a simulation study. Later, sensor fusion with RSS and inertial measurement unit (IMU) for target tracking is discussed to improve accuracy of RSS-based tracking by using KF and EKF as fusion algorithms. Effects of channel parameters and IMU precision to tracking performance are analyzed. Derivations of Posterior Cramer-Rao Bounds for tracking are provided for ONLY RSS and RSS/IMU fusion scenarios with respect to different measurement variances. Finally, we establish a test-bed for RSS based localization and tracking by using Xbee S2 RF modules. ONLY RSS and RSS/IMU fusion scenarios are compared to each other experimentally. RSSI performance is also examined with respect to antenna orientation of Xbee S2 RF module.