@inproceedings{7a150fae16594682997021cdc389ca9b,
title = "Robust and Adaptive Radar Elliptical Density-Based Spatial Clustering and labeling for mmWave Radar Point Cloud Data",
abstract = "In this paper, a robust and adaptive radar point cloud clustering algorithm, named radar elliptical density-based spatial clustering of applications with noise (REDBSCAN), is presented. The proposed algorithm shows better clustering results for adapting to the arbitrary shape of targets as well as any number of targets comparing with traditional clustering methods. The algorithm is presented and is implemented in experiments using the state-of-art mmWave radar sensor with multiple-input multiple-output (MIMO) antennas. The related signal processing chain and the clustering outcomes are also discussed.",
keywords = "Clustering, DBSCAN, Point Cloud, REDBSCAN, Radar Clustering, Radar Signal Processing",
author = "Renyuan Zhang and Siyang Cao",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 ; Conference date: 03-11-2019 Through 06-11-2019",
year = "2019",
month = nov,
doi = "10.1109/IEEECONF44664.2019.9048869",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "IEEE Computer Society",
pages = "919--924",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019",
}