Indoor object positioning using ultra wide band sensor

Today, indoor positioning systems are used in many areas, both civil and military and they become an important study field. Since global positioning systems cannot be used to locate objects indoors, different positioning systems are needed to solve indoor positioning problems. In this thesis, it is aimed to determine the performance limits of the EKF algorithm and to investigate the effects of different sensor geometries and sensor numbers on the estimation performance of the EKF algorithm in indoor object positioning problem using an ultra wideband sensor. Therefore, position estimation and estimation errors of the EKF algorithm were obtained by using different sensor geometries. When the results were examined, it was seen that the estimation errors have changed when sensor geometry was changed. Therefore, sensor geometry affects the estimation performance of the EKF algorithm. Consequently, sensor geometry should be designed optimally to obtain position estimation with low errors. Also, to examine the effects of the sensor numbers on position estimation performance of the EKF algorithm, estimation errors of the EKF algorithm were obtained by increasing the sensor numbers. It was concluded that when the number of sensors is increased, the decrease in the estimation error of the EKF algorithm depends on the sensor geometry. Key Words : Extended Kalman filter, UWB sensor, indoor positioning, sensor geometry