Quote
Zhang, Zheng u. a. 2023. Interference Mitigation for Automotive Radar in Continious Wavelet Transform Domain. Proceedings IET International Radar Conference 2023, n.n. https://www.researchgate.net/publication/377115890_Interference_Mitigation_for_Automotive_Radar_in_Continious_Wavelet_Transform_Domain.
Content
nterference mitigation is a crucial aspect of automotive radar research, especially in dense vehicle scenarios, where radardetection performance needs enhancement. This paper proposes a novel interference mitigation algorithm, the continuouswavelet transform and morphological component analysis (CWT-MCA). By converting the time-domain signal to thetime-frequency domain, CWT-MCA achieves direct separation of target and interference components without requiringinterference detection and identification. The paper compares the proposed algorithm with the traditional linear predictionmethod. Numerical simulations show that our algorithm excels in interference mitigation performance and computationalefficiency, making it well-suited for real-time implementation in automotive radar systems.