Ändra sökning
Länk till posten
Permanent länk

Direktlänk
BETA
Rameez, Muhammad
Publikationer (4 of 4) Visa alla publikationer
Rameez, M., Dahl, M. & Pettersson, M. (2020). Experimental Evaluation of Adaptive Beamforming for Automotive Radar Interference Suppression. In: IEEE Radio and Wireless Symposium, RWS: . Paper presented at IEEE Radio and Wireless Symposium, RWW 2020; San Antonio; United States; 26 January 2020 through 29 January 2020 (pp. 183-186). IEEE, Article ID 9049982.
Öppna denna publikation i ny flik eller fönster >>Experimental Evaluation of Adaptive Beamforming for Automotive Radar Interference Suppression
2020 (Engelska)Ingår i: IEEE Radio and Wireless Symposium, RWS, IEEE, 2020, s. 183-186, artikel-id 9049982Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Mutual interference between automotive radars can make it difficult to detect targets, especially the weaker ones, such as cyclists and pedestrians. In this paper, the interference suppression performance of a Least Mean Squares (LMS) algorithm-based adaptive beamformer is evaluated using measurements from a 77 GHz Frequency Modulated Continuous Wave (FMCW) radar in an outdoor environment. It is shown that the adaptive beamformer increases detection performance and that the interference is suppressed down to the noise floor of the radar in the Range-Doppler domain. In the paper, real baseband sampling and complex-baseband sampling (IQ) radar receivers are compared in the context of interference suppression. The measurements show that IQ receivers are more beneficial in the presence of interference.

Ort, förlag, år, upplaga, sidor
IEEE, 2020
Nyckelord
Automotive radar, Frequency Modulated Continuous Wave (FMCW), interference mitigation, digital beamforming
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
urn:nbn:se:bth-19368 (URN)10.1109/RWS45077.2020.9049982 (DOI)
Konferens
IEEE Radio and Wireless Symposium, RWW 2020; San Antonio; United States; 26 January 2020 through 29 January 2020
Anmärkning

Sponsorer: AESS,APS,IEEE,MTT-S

Tillgänglig från: 2020-04-07 Skapad: 2020-04-07 Senast uppdaterad: 2020-04-24Bibliografiskt granskad
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.
Öppna denna publikation i ny flik eller fönster >>Adaptive digital beamforming for interference suppression in automotive FMCW radars
2018 (Engelska)Ingår i: 2018 IEEE Radar Conference, (RadarConf 2018), Institute of Electrical and Electronics Engineers Inc. , 2018, s. 252-256Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers Inc., 2018
Serie
IEEE Radar Conference
Nyckelord
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
Nationell ämneskategori
Annan elektroteknik och elektronik
Identifikatorer
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)
Konferens
2018 IEEE Radar Conference,Oklahoma City
Tillgänglig från: 2018-08-20 Skapad: 2018-08-20 Senast uppdaterad: 2020-04-07Bibliografiskt granskad
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
Öppna denna publikation i ny flik eller fönster >>Vehicle classification based on multiple fuzzy c-means clustering using dimensions and speed features
2018 (Engelska)Ingår i: Procedia Computer Science, Elsevier, 2018, Vol. 126, s. 7s. 1344-1350Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
Elsevier, 2018. s. 7
Serie
Procedia Computer Science, ISSN 1877-0509
Nyckelord
Vehicle classification, Fuzzy c-means clustering, Intelligent transportation systems, Pattern recognition
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
urn:nbn:se:bth-17165 (URN)10.1016/j.procS.2018.08.085 (DOI)
Konferens
22nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2018), Belgrade
Anmärkning

open access

Tillgänglig från: 2018-10-23 Skapad: 2018-10-23 Senast uppdaterad: 2018-11-29Bibliografiskt granskad
Rameez, M.Signal Reconstruction for Automotive Radar Interference Mitigation.
Öppna denna publikation i ny flik eller fönster >>Signal Reconstruction for Automotive Radar Interference Mitigation
(Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
Nyckelord
Automotive radar, Autoregressive (AR) modelling, Chirp Sequence (CS), Frequency Modulated Continuous Wave (FMCW), interference mitigation, signal reconstruction
Nationell ämneskategori
Elektroteknik och elektronik Signalbehandling
Identifikatorer
urn:nbn:se:bth-19375 (URN)
Tillgänglig från: 2020-04-07 Skapad: 2020-04-07 Senast uppdaterad: 2020-04-07Bibliografiskt granskad
Organisationer

Sök vidare i DiVA

Visa alla publikationer