A Lightweight UWB NLOS Detection Algorithm Using Referenced CIR Similarity Metrics

被引：0

作者：

He, Xu ^{[1
]}

Yang, Runkun ^{[1
]}

Mo, Lingfei ^{[1
]}

Meng, Xiaolin ^{[1
]}

Yang, Fanxing ^{[1
]}

Zhang, Youdong ^{[1
]}

Wang, Qing ^{[1
]}

机构：

[1] Southeast Univ, Sch Instrument & Engn, Nanjing 210096, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2024年 / 13卷 / 10期

关键词：

Vectors; Measurement; Radio frequency; Feature extraction; Data models; Probability distribution; Entropy; UWB; NLOS; CIR; similarity metric; RCS;

D O I：

10.1109/LWC.2024.3446632

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：2797 / 2801

页数：5

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