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Rameez, Muhammad
Publications (2 of 2) Show all publications
Rameez, M., Dahl, M. & Pettersson, M. (2018). Adaptive digital beamforming for interference suppression in automotive FMCW radars. In: 2018 IEEE Radar Conference, (RadarConf 2018): . Paper presented at 2018 IEEE Radar Conference,Oklahoma City (pp. 252-256). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Adaptive digital beamforming for interference suppression in automotive FMCW radars
2018 (English)In: 2018 IEEE Radar Conference, (RadarConf 2018), Institute of Electrical and Electronics Engineers Inc. , 2018, p. 252-256Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the problem of mutual interference between automotive radars. This problem is getting more attention with an increase in the number of radar systems used in traffic. An adaptive digital beamforming technique is presented here which suppresses the interference without the exact knowledge of the interfering signal's Direction of Arrival (DoA). The proposed technique is robust and does not rely on any calibration for the interference cancellation. The adaptive interference suppression method is evaluated using a simulated scenario. Up to about 20-23 dB improvement in the target Signal to Interference and Noise Ratio (SINR) is measured in the simulation and a better detection performance is achieved using the proposed interference suppression technique. © 2018 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Series
IEEE Radar Conference
Keywords
Beamforming, Frequency modulation, Radar systems, Signal to noise ratio, Adaptive digital beamforming, Adaptive interference suppression, Automotive radar, Detection performance, Interference cancellation, Interfering signals, Mutual interference, Target signals, Radar interference
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-16910 (URN)10.1109/RADAR.2018.8378566 (DOI)000442172700046 ()2-s2.0-85049977586 (Scopus ID)978-1-5386-4167-5 (ISBN)
Conference
2018 IEEE Radar Conference,Oklahoma City
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2018-09-20Bibliographically approved
Javadi, M. S., Rameez, M., Dahl, M. & Pettersson, M. (2018). Vehicle classification based on multiple fuzzy c-means clustering using dimensions and speed features. In: Procedia Computer Science: . Paper presented at 22nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2018), Belgrade (pp. 1344-1350). Elsevier, 126
Open this publication in new window or tab >>Vehicle classification based on multiple fuzzy c-means clustering using dimensions and speed features
2018 (English)In: Procedia Computer Science, Elsevier, 2018, Vol. 126, p. 7p. 1344-1350Conference paper, Published paper (Refereed)
Abstract [en]

Vehicle classification has a significant use in traffic surveillance and management. There are many methods proposed to accomplish this task using variety of sensorS. In this paper, a method based on fuzzy c-means (FCM) clustering is introduced that uses dimensions and speed features of each vehicle. This method exploits the distinction in dimensions features and traffic regulations for each class of vehicles by using multiple FCM clusterings and initializing the partition matrices of the respective classifierS. The experimental results demonstrate that the proposed approach is successful in clustering vehicles from different classes with similar appearanceS. In addition, it is fast and efficient for big data analysiS.

Place, publisher, year, edition, pages
Elsevier, 2018. p. 7
Series
Procedia Computer Science, ISSN 1877-0509
Keywords
Vehicle classification, Fuzzy c-means clustering, Intelligent transportation systems, Pattern recognition
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:bth-17165 (URN)10.1016/j.procS.2018.08.085 (DOI)
Conference
22nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2018), Belgrade
Note

open access

Available from: 2018-10-23 Created: 2018-10-23 Last updated: 2018-11-29Bibliographically approved
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