Integrated object and road border tracking using 77 GHz automotive radars

Polychronopoulos, A; Amditis, A; Floudas, N; Lind, H

dc.contributor.author	Polychronopoulos, A	en
dc.contributor.author	Amditis, A	en
dc.contributor.author	Floudas, N	en
dc.contributor.author	Lind, H	en
dc.date.accessioned	2014-03-01T01:20:38Z
dc.date.available	2014-03-01T01:20:38Z
dc.date.issued	2004	en
dc.identifier.issn	1350-2395	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15999
dc.subject.classification	Telecommunications	en
dc.subject.other	Alarm systems	en
dc.subject.other	Algorithms	en
dc.subject.other	Collision avoidance	en
dc.subject.other	Kalman filtering	en
dc.subject.other	Millimeter wave devices	en
dc.subject.other	Object recognition	en
dc.subject.other	Radar systems	en
dc.subject.other	Sensor data fusion	en
dc.subject.other	Stereo vision	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Automotive radars	en
dc.subject.other	Collision warning	en
dc.subject.other	Integrated object tracking	en
dc.subject.other	Radar sensors	en
dc.subject.other	Road border tracking	en
dc.subject.other	Tracking radar	en
dc.title	Integrated object and road border tracking using 77 GHz automotive radars	en
heal.type	journalArticle	en
heal.identifier.primary	10.1049/ip-rsn:20041067	en
heal.identifier.secondary	http://dx.doi.org/10.1049/ip-rsn:20041067	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	Radar sensors are widely used in automotive on-board systems such as adaptive cruise control, which tracks the preceding vehicle and keeps a safe distance. The authors go a step further and exploit the potential of a high resolution radar sensor for the estimation of the road borders and the reconstruction of the traffic scenario based on object tracking. A FMCW millimetre wave radar is mounted in the front bumper of a vehicle and delivers object lists to the central fusion processor, where detections are considered as measurements to an integrated model based road border estimation system. The algorithm presented is designed to improve the prediction of paths and trajectories of the ego-vehicle in future enhanced collision warning and collision avoidance systems. Given the characteristics and limitations of a radar system, such as heavy clutter, the algorithms are tested with real data and perform reliably in highway and extra-urban scenarios and are competitive with data fusion and stereo vision systems, but with lower computational load. © IEE, 2004.	en
heal.publisher	IEE-INST ELEC ENG	en
heal.journalName	IEE Proceedings: Radar, Sonar and Navigation	en
dc.identifier.doi	10.1049/ip-rsn:20041067	en
dc.identifier.isi	ISI:000228208500006	en
dc.identifier.volume	151	en
dc.identifier.issue	6	en
dc.identifier.spage	375	en
dc.identifier.epage	381	en