Abstract
This paper presents the proof of concept of a methodology for radar image segmentation in real aperture low-THz high resolution radar imagery, ultimately as a method to identify traversable free space for path planning for autonomous vehicles. The segmentation method, based on histogram thresholding of super-pixel statistical means is described and then applied to candidate high resolution radar images to show the potential for region finding. The subsequently segmented images are then qualitatively analysed, relevant features such as shadow and anomalous statistical regions are discussed related to identification of hazard areas for path planning.
| Original language | English |
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| Title of host publication | 2019 20th International Radar Symposium, IRS 2019 |
| Editors | Peter Knott |
| Publisher | IEEE Computer Society Press |
| ISBN (Electronic) | 9783736998605 |
| DOIs | |
| Publication status | Published - Jun 2019 |
| Event | 20th International Radar Symposium, IRS 2019 - Ulm, Germany Duration: 26 Jun 2019 → 28 Jun 2019 |
Publication series
| Name | Proceedings International Radar Symposium |
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| Volume | 2019-June |
| ISSN (Print) | 2155-5753 |
Conference
| Conference | 20th International Radar Symposium, IRS 2019 |
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| Country/Territory | Germany |
| City | Ulm |
| Period | 26/06/19 → 28/06/19 |
Bibliographical note
Funding Information:This work was supported by Jaguar Land Rover and the UK-EPSRC grant EP/N012372/1 as part of the jointly funded Towards Autonomy: Smart and Connected Control (TASCC) Programme
Publisher Copyright:
© 2019 German Institute of Navigation (DGON).
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Signal Processing
- Electrical and Electronic Engineering
- Astronomy and Astrophysics
- Instrumentation