@inproceedings{4052e0308a494efe980e33b7540aa56c,
title = "Smoothing Method for Range and Angle Super Resolution Frequency-Division-Multiplexing FMCW MIMO Radar",
abstract = "As a low cost and highly reliable sensor in autonomous driving and driver assistance systems, automotive radars has attracted a lot of researchers and companies. Most automotive radars are based on frequency modulated continuous wave (FMCW) and multiple-input multiple-output (MIMO) techniques to achieve high range and angle resolution, respectively. Compared with time-division multiplexing (TDM), frequency division multiplexing (FDM) transmits a signal with different frequencies simultaneously and would not reduce the maximum unambiguous velocity. In this paper, we present a dual smoothing method based on the FDM-FMCW-MIMO radar. By exploiting the time and space shift-invariant structure of the FDM-FMCW-MIMO signal, the proposed method can provide range and angle super-resolution of multiple objects, while the number of detectable objects is also not limited by the number of virtual channels of MIMO radar.",
keywords = "Automotive radar, Dual smoothing, FDM, FMCW-MIMO, Super-resolution",
author = "Shubin Li and Yu Zhai and Bin Yang and Jun Wang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 6th International Conference on Signal and Image Processing, ICSIP 2021 ; Conference date: 22-10-2021 Through 24-10-2021",
year = "2021",
doi = "10.1109/ICSIP52628.2021.9688958",
language = "英语",
series = "2021 6th International Conference on Signal and Image Processing, ICSIP 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "590--594",
booktitle = "2021 6th International Conference on Signal and Image Processing, ICSIP 2021",
address = "美国",
}