Indoor unknown radio transmitter localization using improved RSSD and grey correlation degree

IF 2.7 3区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Science and Technology Pub Date : 2024-07-02 DOI:10.1088/1361-6501/ad5de6

Liyang Zhang, Chenyu Xu, Rui Gao, Yin Liang, Lidong Zhang, Lixia Guo

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引用次数: 0

Abstract

Accurate location of unknown radio transmitter (URT) is the key to secure wireless communication. Since the fingerprint positioning methods based on received signal strength difference (RSSD) can adapt to the diversity of transmitting power and frequency, RSSD has become a popular scheme for locating the unknown radio transmitter. However, the RSSD is obtained by subtracting the RSS from two different access points (APs), so the interference of noise on the RSS is inherited and amplified by the RSSD. Besides, the need for more APs to ensure positioning accuracy leads to an increase in hardware costs. In this paper, a RSSD-based fuzzy weight grey correlation degree positioning algorithm, called FUZZY-GREY, is proposed to reduce the interference of noise, save AP hardware cost and improve the positioning accuracy. Firstly, online RSSD vector is improved by using fuzzy weight to reduce the noise interference. Secondly, the RSSD-based grey correlation coefficient is designed to calculate the correlation degree of the corresponding RSSD and ensure data integrity. Finally, a RSSD-based grey correlation degree scheme combining with fuzzy weight is proposed to select optimal reference points (RPs). Simulation and experimental results show that the proposed algorithm has better positioning performance than weighted k-nearest neighbor (WKNN), maximum correlation coefficient estimation (MCORE), Naive Bayes and support vector machine (SVM) in the case of different selected K numbers, grid distances, noise levels and AP numbers.

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利用改进的 RSSD 和灰色关联度进行室内未知无线电发射机定位

准确定位未知无线电发射机（URT）是确保无线通信安全的关键。由于基于接收信号强度差（RSSD）的指纹定位方法能适应发射功率和频率的多样性，RSSD 已成为定位未知无线电发射机的流行方案。然而，RSSD 是通过减去两个不同接入点（AP）的 RSS 得到的，因此 RSSD 会继承和放大噪声对 RSS 的干扰。此外，由于需要更多接入点来确保定位精度，导致硬件成本增加。本文提出了一种基于 RSSD 的模糊权灰色关联度定位算法 FUZZY-GREY，以减少噪声干扰，节约 AP 硬件成本，提高定位精度。首先，利用模糊权重改进在线 RSSD 向量，以减少噪声干扰。其次，设计基于 RSSD 的灰色关联系数，计算相应 RSSD 的关联度，确保数据完整性。最后，提出了基于 RSSD 的灰色关联度方案，并结合模糊权重选择最佳参考点（RP）。仿真和实验结果表明，与加权 K 近邻（WKNN）、最大相关系数估计（MCORE）、Naive Bayes 和支持向量机（SVM）相比，在选择不同的 K 数、网格距离、噪声水平和 AP 数的情况下，所提出的算法具有更好的定位性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Measurement Science and Technology 工程技术-工程：综合

CiteScore

4.30

自引率

16.70%

发文量

656

审稿时长

4.9 months

期刊介绍： Measurement Science and Technology publishes articles on new measurement techniques and associated instrumentation. Papers that describe experiments must represent an advance in measurement science or measurement technique rather than the application of established experimental technique. Bearing in mind the multidisciplinary nature of the journal, authors must provide an introduction to their work that makes clear the novelty, significance, broader relevance of their work in a measurement context and relevance to the readership of Measurement Science and Technology. All submitted articles should contain consideration of the uncertainty, precision and/or accuracy of the measurements presented. Subject coverage includes the theory, practice and application of measurement in physics, chemistry, engineering and the environmental and life sciences from inception to commercial exploitation. Publications in the journal should emphasize the novelty of reported methods, characterize them and demonstrate their performance using examples or applications.