The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20089133

Krasnov, Oleg; Fred van der Zwan; Yarovoy, Alexander (2022): Coherent radar observations of a highway: Datasets for radar practicum in signal processing. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20089133.v1

Dataset

• Electrical and Electronic Engineering
• Environmentally Sustainable Transport
• Environmental Engineering
• Automotive Engineering
• Other Technology
• Teaching and Instruction

cars, coherent radar, ground clutter, highway, S-band radar

06.02.2017

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Oleg Krasnov , Fred van der Zwan , Alexander Yarovoy

25 datasets of the A13 highway observations using the TU Delft PARSAX S-band coherent radar, which can be used for radar practicum in BSc/MSc education.

Every dataset archived using the ZIP-archiver and includes:

• the MATLAB mat file with the array of complex radar signals within range-slow time coordinates;
• the similar MATLAB mat file with the array of complex radar signals within range-slow time coordinates with noise-only measurements (without signal transmission);
• the video file from the collocated with the radar video camera, which is more-less synchronized with the radar observations.

More details about the measurements, data access and processing in the MATLAB can be found at the file "Krasnov - Radar practicum - Doppler processing.pdf".

The geo-location of the measurements can be found in the Google Earth file "PARSAX measurements of the highway.kml"

If you will use this data for the scientific publications, we would appreciate it if you cite not only this data but also the paper with the description of the PARSAX radar:  

• O. A. Krasnov, L. P. Ligthart, Zhijian Li, P. Lys and F. van der Zwan,  "The PARSAX - full polarimetric FMCW radar with dual-orthogonal  signals," 2008 European Radar Conference, 2008, pp. 84-87 (see the web-link below). 

• 2022-06-21 first online, published, posted

4TU.ResearchData

application/vnd.google-earth.kml+xml; application/zip; video/mp4; application/matlab text/pdf

• https://ieeexplore.ieee.org/abstract/document/4760807/

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Sciences (EEMCS), Microwave Sensing, Signals and Systems (MS3) group.