Abstract
Radar systems have become one of the principal sensory components in automotive vehicles, due to their ability to detect and discriminate between different objects in various scenarios. In this paper the micro-Doppler signature is used to identify road targets as cyclist, person, group of people, dog walking, and dog trotting. In order to boost the performance of Automatic Target Recognition in automotive environment, each node could share its micro-Doppler based features in a co-operative manner, using novel Vehicle To Vehicle communication frameworks based on joint radar and communication systems. The classification performance is evaluated considering two scenarios, a single-sensor scenarios where the micro-Doppler signature is observed by a single user, and a multi-sensor scenarios where each user shares its feature vector.
Original language | English |
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Title of host publication | 2020 IEEE Radar Conference (RadarConf20) |
Place of Publication | Piscataway, NJ. |
Publisher | IEEE |
Number of pages | 6 |
ISBN (Print) | 9781728189437 |
DOIs | |
Publication status | Published - 4 Dec 2020 |
Event | IEEE Radar Conference 2020 - Florence, Florence, Italy Duration: 21 Sept 2020 → 25 Sept 2020 |
Conference
Conference | IEEE Radar Conference 2020 |
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Country/Territory | Italy |
City | Florence |
Period | 21/09/20 → 25/09/20 |
Keywords
- automatic target recognition
- automotive application
- single sensor
- multi sensor