Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8970
Title: Position and Velocity Detection with RADAR and GPS Fusion
Other Titles: RADAR ve GPS Füzyonu ile Mesafe ve Hiz Tespiti
Authors: Isil Akcay H.
Onat E.
Keywords: Fusion
GPS
Kalman Filter
Position Estimation
Radar
Velocity Estimation
Global positioning system
Mean square error
Radar
Radar measurement
Velocity
Designed models
Error-free measurements
GPS satellites
Position detection
Position estimation
Radar satellites
Root mean square errors
Time interval
Velocity detection
Velocity estimation
Kalman filters
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: In this paper, the fusion of distance and velocity measurements using radar and GPS is discussed. A Kalman Filter (KF) was designed for the fusion of the measurement results obtained with these different systems. The designed model was used to estimate the position and velocity of a runner. Different scenarios were produced and tested, such as error-free measurements for the entire time interval, unexpected measurements from radar or GPS satellites for a certain period of time. Root Mean Square Error values were calculated and the success of position and velocity estimations were examined. It has been observed that the designed Kalman Filter predictions are more successful than radar and GPS systems. © 2022 IEEE.
Description: 30th Signal Processing and Communications Applications Conference, SIU 2022 -- 15 May 2022 through 18 May 2022 -- -- 182415
URI: https://doi.org/10.1109/SIU55565.2022.9864793
https://hdl.handle.net/20.500.11851/8970
ISBN: 9.78167E+12
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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