Photo of Gustaf Hendeby

Gustaf Hendeby

Associate Professor, Docent

Dr. Gustaf Hendeby currently holds an Associate Professor position at the Division of Automatic Control at the Department of Electrical Engineering at Linköping University.

He received his Docent degree in May 2015, his Ph.D. in March 2008, and his Lic. Eng. degree in November 2005, all in Automatic Control from Linköping University.
Dr. Hendeby also has a M.Sc. degree in Applied Physics and Electrical Engineering (Y) in December 2002, also from Linköpings universitet.
After obtaining his Ph.D, Dr. Hendeby remained with the Automatic Control group as a Assistant Professor for a year before moving to Kaiserslautern, Germany, in 2009 to join the German Research Institute for Artificial Intelligence (DFKI) as a Senior Scientist. In Germany he worked in the European projects PAMAP (Ambient Assisted Living Joint Programme) and COGNITO (EU 7th Framework Program for Research, FP7). He acted as technical coordinator for COGNITO until the end of 2011 when he moved back to Sweden. At the same time he was responsible for the software integration of the Colibri inertial measurement units (IMUs) by Trivisio GmbH. On returning to Sweden Dr. Hendeby joined the Swedish Defence Research Agency (FOI) as a target tracking specialist. In 2012 he rejoined the Automatic Control group as a part time Adjunct Associate Professors.


The focus of Dr. Hendeby's research is statistical and model based sensor fusion; in particular with applications in target tracking, simultaneous localization and mapping (SLAM), positioning, and general nonlinear estimation problems. In doing so he has worked with different Kalman filter approximations (extended Kalman filter and unscented Kalman filter), as well as the particle filter. By understanding these methods better, it will be possible to utilize the waste amount of sensor data, often from low quality sensors, better and to make the algorithms more accessible by non-experts.


Dr. Hendeby lecture Sensor Fusion (TSRT14) and acts as examiner for Master's theses in his general area of interest.



Jeongmin Kang, Zoran Sjanic, Gustaf Hendeby (2023) Optical Flow Revisited: how good is dense deep learning based optical flow? 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI) Continue to DOI
Isaac Skog, Gustaf Hendeby, Manon Kok (2023) Tightly Integrated Motion Classification and StateEstimation in Foot-Mounted Navigation Systems Proceedings of 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN)
Jakob Åslund, Fredrik Gustafsson, Gustaf Hendeby (2023) When Does the Marginalized Particle Filter Degenerate? 2023 26th International Conference on Information Fusion (FUSION) Continue to DOI
Peng Liu, Kailai Li, Gustaf Hendeby, Fredrik Gustafsson (2023) Weighted Total Least Squares for Quadratic Errors-in-Variables Regression Proceedings of the 31st Conference on European Signal Processing, p. 1894-1897
Gustav Zetterqvist, Fredrik Gustafsson, Gustaf Hendeby (2023) Using Received Power in Microphone Arrays to Estimate Direction of Arrival ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Continue to DOI


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