Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11777
Title: Compression Analysis of Automotive Radar Raw Data
Other Titles: Otomotiv Radar Ham Verilerinin Sıkıştırma Analizi
Authors: Erog, Ö.
Orduyılmaz, A.
Keywords: Compression
image
radar
raw data
Automotive radar
Data handling
Image compression
Mean square error
Petroleum reservoir evaluation
Radar equipment
Radar imaging
Radar measurement
Tracking radar
Advanced vehicle
Automotive radar
Automotive radar system
Compression
Image
JPEG 2000
Multiple radar
Radar sensors
Raw data
Support systems
Signal to noise ratio
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Automotive radar system is one of the most important components of the advanced vehicle support systems. Basically, it stands out from other sensors with its capability of being less affected by weather conditions and precise range and speed measurement. Multiple radar sensors are used for precise detection and full coverage for near and far range. By using multiple radar sensors in the vehicle, precise detection and full coverage are provided at near and far range. Processing data received from multiple sensors in a single center enables both the commonality of data and the creation of higher capacity signal processing capabilities. For this purpose, a central processing analysis of the compression of radar raw data with the JPEG 2000 method was carried out. JPEG 2000 method with low loss for high compression ratios can be provided via hardware accelerators. In these analyses, image evaluation tools such as peak SNR and mean squared error, as well as the distortions in radar parameters such as range and speed estimation have been observed. It was determined that for the compression rates of up to 70%, there was no consequential decline in radar detection performance. © 2024 IEEE.
Description: Berdan Civata B.C.; et al.; Figes; Koluman; Loodos; Tarsus University
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 -- 15 May 2024 through 18 May 2024 -- Mersin -- 201235
URI: https://doi.org/10.1109/SIU61531.2024.10600895
https://hdl.handle.net/20.500.11851/11777
ISBN: 979-835038896-1
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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