scholarly journals Sensor Fusion for Position Estimation in Networked Systems

10.5772/9966 ◽  
2010 ◽  
Author(s):  
Luca Carlone ◽  
Giuseppe Calafiore ◽  
Mingzhu Wei
Keyword(s):  
Sensor Fusion ◽  
Position Estimation ◽  
Networked Systems

scholarly journals Extended Kalman Filter (EKF) Design for Vehicle Position Tracking Using Reliability Function of Radar and Lidar

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4126 ◽  
Author(s):  
Taeklim Kim ◽  
Tae-Hyoung Park
Keyword(s):  
Kalman Filter ◽  
Sensor Fusion ◽  
Extended Kalman Filter ◽  
Reliability Function ◽  
Position Estimation ◽  
Position Tracking ◽  
Radar Sensors ◽  
Vehicle Position ◽  
Sensor Errors ◽  
Fuzzy Adaptive

Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations.

Position Estimation by Wearable Walking Navigation System for Visually Impaired with Sensor Fusion

2011 ◽  
Vol 131 (4) ◽  
pp. 490-496 ◽  
Author(s):  
Hiromi Watanabe ◽  
Yoshihiko Yamamoto ◽  
Tsutomu Tanzawa ◽  
Shinji Kotani
Keyword(s):  
Sensor Fusion ◽  
Navigation System ◽  
Visually Impaired ◽  
Position Estimation
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