@inproceedings{029a27605d6542b688cc02ed36d50f8b,
title = "Rfcm for Data Association and Multitarget Tracking Using 3D Radar",
abstract = "Performance of object classification using 3D automotive radar relies on accurate data association and multitarget tracking' which are greatly affected by data bias and proximity of objects to each other. A regularized fuzzy c-means (RFCM) algorithm is proposed herein to resolve the data association uncertainty problem that has shown to outperform the conventional FCM algorithm. The proposed method exploits results from the companion tracker to increase performance robustness. Simulation results using simulated and field data have proven the efficacy of the proposed method.",
keywords = "ADAS, Autonomous driving, Data association, Multitarget tracking, Regularized fuzzy c-means",
author = "Chan, {Chun Nien} and Fung, {Carrson C.}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 ; Conference date: 15-04-2018 Through 20-04-2018",
year = "2018",
month = sep,
day = "10",
doi = "10.1109/ICASSP.2018.8461917",
language = "American English",
isbn = "9781538646588",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2621--2625",
booktitle = "2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings",
address = "United States",
}