Xu He;Runkun Yang;Lingfei Mo;Xiaolin Meng;Fanxing Yang;Youdong Zhang;Qing Wang
{"title":"使用参考 CIR 相似度指标的轻量级 UWB NLOS 检测算法","authors":"Xu He;Runkun Yang;Lingfei Mo;Xiaolin Meng;Fanxing Yang;Youdong Zhang;Qing Wang","doi":"10.1109/LWC.2024.3446632","DOIUrl":null,"url":null,"abstract":"A lightweight and effective algorithm is benefit for real-world applications and edge devices. This letter presents a lightweight algorithm for Non-Line-of-Sight (NLOS) detection in Ultra-Wideband (UWB) systems, using the referenced Channel Impulse Response (CIR) similarity metrics. It retains essential UWB channel characteristics while incorporating a Radar Cross-Section (RCS)-inspired feature engineering method to capture the effective NLOS representation. It bears novel features to significantly reduce the input data dimensions, model parameters, and Floating-point operations (Flops) by 64.9%, 78.5%, 76.0%, respectively, with comparable performance to the latest State-Of-The-Art (SOTA) solutions. We demonstrate its effectiveness through actual measurements and comparative experiments in mixed complex Line-Of-Sight (LOS)/NLOS dataset, offering a computationally efficient solution for UWB NLOS detection with effective representation.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"13 10","pages":"2797-2801"},"PeriodicalIF":4.6000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Lightweight UWB NLOS Detection Algorithm Using Referenced CIR Similarity Metrics\",\"authors\":\"Xu He;Runkun Yang;Lingfei Mo;Xiaolin Meng;Fanxing Yang;Youdong Zhang;Qing Wang\",\"doi\":\"10.1109/LWC.2024.3446632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A lightweight and effective algorithm is benefit for real-world applications and edge devices. This letter presents a lightweight algorithm for Non-Line-of-Sight (NLOS) detection in Ultra-Wideband (UWB) systems, using the referenced Channel Impulse Response (CIR) similarity metrics. It retains essential UWB channel characteristics while incorporating a Radar Cross-Section (RCS)-inspired feature engineering method to capture the effective NLOS representation. It bears novel features to significantly reduce the input data dimensions, model parameters, and Floating-point operations (Flops) by 64.9%, 78.5%, 76.0%, respectively, with comparable performance to the latest State-Of-The-Art (SOTA) solutions. We demonstrate its effectiveness through actual measurements and comparative experiments in mixed complex Line-Of-Sight (LOS)/NLOS dataset, offering a computationally efficient solution for UWB NLOS detection with effective representation.\",\"PeriodicalId\":13343,\"journal\":{\"name\":\"IEEE Wireless Communications Letters\",\"volume\":\"13 10\",\"pages\":\"2797-2801\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Wireless Communications Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10640153/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10640153/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A Lightweight UWB NLOS Detection Algorithm Using Referenced CIR Similarity Metrics
A lightweight and effective algorithm is benefit for real-world applications and edge devices. This letter presents a lightweight algorithm for Non-Line-of-Sight (NLOS) detection in Ultra-Wideband (UWB) systems, using the referenced Channel Impulse Response (CIR) similarity metrics. It retains essential UWB channel characteristics while incorporating a Radar Cross-Section (RCS)-inspired feature engineering method to capture the effective NLOS representation. It bears novel features to significantly reduce the input data dimensions, model parameters, and Floating-point operations (Flops) by 64.9%, 78.5%, 76.0%, respectively, with comparable performance to the latest State-Of-The-Art (SOTA) solutions. We demonstrate its effectiveness through actual measurements and comparative experiments in mixed complex Line-Of-Sight (LOS)/NLOS dataset, offering a computationally efficient solution for UWB NLOS detection with effective representation.
期刊介绍：
IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.
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