IEICE Transactions on Communications
Online ISSN : 1745-1345
Print ISSN : 0916-8516
Special Section on Emerging Communication Technologies in Conjunction with Main Topics of ICETC 2023
Wideband Interference Suppression for Automotive mmWave CS Radar: From Algorithm-Based to Learning-Based Approaches
Xiaoyan WANGRyoto KOIZUMIMasahiro UMEHIRARan SUNShigeki TAKEDA
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2024 年 E107.B 巻 12 号 p. 861-871

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In recent times, there has been a significant focus on the development of automotive high-resolution 77GHz CS (Chirp Sequence) radar, a technology essential for autonomous driving. However, with the increasing popularity of vehicle-mounted CS radars, the issue of intensive inter-radar wideband interference has emerged as a significant concern, leading to undesirable missed targe detection. To solve this problem, various algorithm and learning based approaches have been proposed for wideband interference suppression. In this study, we begin by conducting extensive simulations to assess the SINR (Signal to Interference plus Noise Ratio) and execution time of these approaches in highly demanding scenarios involving up to 7 interfering radars. Subsequently, to validate these approaches could generalize to real data, we perform comprehensive experiments on inter-radar interference using multiple 77GHz MIMO (Multiple-Input and Multiple-output) CS radars. The collected real-world interference data is then utilized to validate the generalization capacity of these approaches in terms of SINR, missed detection rate, and false detection rate.

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© 2024 The Institute of Electronics, Information and Communication Engineers
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