UWB Wireless Positioning Method Based on LightGBM

IF 2.2 4区计算机科学 Q3 TELECOMMUNICATIONS

Wireless Personal Communications Pub Date : 2024-07-08 DOI:10.1007/s11277-024-11456-x

Xuerong Cui, Yuanxu Li, Juan Li, Bin Jiang, Shibao Li, Jianhang Liu

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Abstract

In the ultra-wideband indoor positioning sceneraio, the non-line of sight (NLOS) propagation may be caused by obstacles, which may lead to the deviation of ranging value and affect the positioning precision. Therefore, we propose a NLOS identification and error regression positioning algorithm based on light gradient boosting machine (LightGBM). Firstly, ReliefF algorithm combined with Spearman correlation coefficient is used to analyze the feature correlation, and eight channel features such as total channel impulse response power and standard deviation of noise are selected as NLOS identification features. Then, we adopt genetic algorithm to optimize the hyperparameters of LightGBM for NLOS identification. On this basis, the proposed error regression model based on convolutional neural network (CNN) combined with LightGBM is used to correct the ranging results, so as to achieve high-precision positioning. Through the verification on the public dataset, the NLOS identification accuracy reached 91.8%, and the positioning precision is improved by 45 cm after correcting the ranging results.

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基于 LightGBM 的 UWB 无线定位方法

在超宽带室内定位场景中，障碍物可能会导致非视线（NLOS）传播，从而导致测距值偏差，影响定位精度。因此，我们提出了一种基于光梯度提升机（LightGBM）的 NLOS 识别和误差回归定位算法。首先，采用 ReliefF 算法结合 Spearman 相关系数分析特征相关性，选取信道总脉冲响应功率、噪声标准偏差等 8 个信道特征作为 NLOS 识别特征。然后，采用遗传算法优化 LightGBM 的超参数，实现 NLOS 识别。在此基础上，提出基于卷积神经网络（CNN）的误差回归模型，结合 LightGBM 对测距结果进行修正，从而实现高精度定位。通过公开数据集的验证，NLOS 识别精度达到 91.8%，校正测距结果后定位精度提高了 45 厘米。

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来源期刊

Wireless Personal Communications 工程技术-电信学

CiteScore

5.80

自引率

9.10%

发文量

663

审稿时长

6.8 months

期刊介绍： The Journal on Mobile Communication and Computing ... Publishes tutorial, survey, and original research papers addressing mobile communications and computing; Investigates theoretical, engineering, and experimental aspects of radio communications, voice, data, images, and multimedia; Explores propagation, system models, speech and image coding, multiple access techniques, protocols, performance evaluation, radio local area networks, and networking and architectures, etc.; 98% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again. Wireless Personal Communications is an archival, peer reviewed, scientific and technical journal addressing mobile communications and computing. It investigates theoretical, engineering, and experimental aspects of radio communications, voice, data, images, and multimedia. A partial list of topics included in the journal is: propagation, system models, speech and image coding, multiple access techniques, protocols performance evaluation, radio local area networks, and networking and architectures. In addition to the above mentioned areas, the journal also accepts papers that deal with interdisciplinary aspects of wireless communications along with: big data and analytics, business and economy, society, and the environment. The journal features five principal types of papers: full technical papers, short papers, technical aspects of policy and standardization, letters offering new research thoughts and experimental ideas, and invited papers on important and emerging topics authored by renowned experts.