{"title":"二维超分辨距离多普勒成像在汽车雷达中的应用","authors":"Jieru Ding, Min Wang, Xinghui Wu, Zhiyi Wang","doi":"10.1109/ICSAI57119.2022.10005501","DOIUrl":null,"url":null,"abstract":"Automotive radar plays a significant role in un-manned auto-drive system, and most vehicle-mounted radars improve the angular resolution by the MIMO radar. Two-dimension (2D) fast Fourier transform (FFT) is usually used to extract the range frequency and Doppler frequency. When there is few sampling points in the observed signal, imaging results of range-Doppler rapidly deteriorates. In this paper, we exploit the sparsity of scattering points in space and the robustness of l1 norm, to finish the super-resolution imaging of range-Doppler (RD) map. l1 is employed to update the sparse result by introducing the Lagrange multiplier. Finally, the algorithm has been validated by the simulated data, and it has demonstrated the algorithm’s effectiveness.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two-dimension Super-resolution Range Doppler Imaging in Automotive Radar\",\"authors\":\"Jieru Ding, Min Wang, Xinghui Wu, Zhiyi Wang\",\"doi\":\"10.1109/ICSAI57119.2022.10005501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automotive radar plays a significant role in un-manned auto-drive system, and most vehicle-mounted radars improve the angular resolution by the MIMO radar. Two-dimension (2D) fast Fourier transform (FFT) is usually used to extract the range frequency and Doppler frequency. When there is few sampling points in the observed signal, imaging results of range-Doppler rapidly deteriorates. In this paper, we exploit the sparsity of scattering points in space and the robustness of l1 norm, to finish the super-resolution imaging of range-Doppler (RD) map. l1 is employed to update the sparse result by introducing the Lagrange multiplier. Finally, the algorithm has been validated by the simulated data, and it has demonstrated the algorithm’s effectiveness.\",\"PeriodicalId\":339547,\"journal\":{\"name\":\"2022 8th International Conference on Systems and Informatics (ICSAI)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 8th International Conference on Systems and Informatics (ICSAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAI57119.2022.10005501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI57119.2022.10005501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two-dimension Super-resolution Range Doppler Imaging in Automotive Radar
Automotive radar plays a significant role in un-manned auto-drive system, and most vehicle-mounted radars improve the angular resolution by the MIMO radar. Two-dimension (2D) fast Fourier transform (FFT) is usually used to extract the range frequency and Doppler frequency. When there is few sampling points in the observed signal, imaging results of range-Doppler rapidly deteriorates. In this paper, we exploit the sparsity of scattering points in space and the robustness of l1 norm, to finish the super-resolution imaging of range-Doppler (RD) map. l1 is employed to update the sparse result by introducing the Lagrange multiplier. Finally, the algorithm has been validated by the simulated data, and it has demonstrated the algorithm’s effectiveness.
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