• 中国科学引文数据库（CSCD）
  • 中文科技期刊数据库
  • 中国核心期刊（遴选）数据库
  • 日本科学技术振兴机构数据库（JST）
  • 中国学术期刊（网络版）（CNKI）
  • 中国学术期刊综合评价数据库（CAJCED）
  • 中国超星期刊域出版平台
Advanced Search
GNSS World of China

GNSS World of China

Volume 49 Issue 4
Aug.  2024
Turn off MathJax
Article Contents
Abstract
References
CHENG Hanqing, ZHANG Guomei, PENG Kejun. Localization for GNSS interference sources based on weighted K-Means combined with DRSS positioning[J]. GNSS World of China, 2024, 49(4): 113-120, 126. DOI: 10.12265/j.gnss.2024025
Citation: CHENG Hanqing, ZHANG Guomei, PENG Kejun. Localization for GNSS interference sources based on weighted K-Means combined with DRSS positioning[J]. GNSS World of China, 2024, 49(4): 113-120, 126. DOI: 10.12265/j.gnss.2024025
shu

Localization for GNSS interference sources based on weighted K-Means combined with DRSS positioning

  • School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an 710049, China

More Information
  • Received Date: January 30, 2024
  • Accepted Date: January 30, 2024
  • Available Online: July 04, 2024
    Graphical Abstract
    • Abstract
  • The carrier to noise ratio (CNR) based interference positioning in Global Navigation Satellite System (GNSS) has the problem of high localization difficulty and the low localization precision under the scenarios with multiple interference sources, multi-path transmission and long distance between receivers. Aiming at this problem, a multi-interference localization scheme that combines the weighted K-Means clustering with different receiver signal strength (DRSS) and equation solving based method is proposed in this paper. Assuming that the number of interference sources is determined and a single receiver is only affected by one interference source, the improved weighted K-Means clustering algorithm is designed to realize the initial estimation for multiple interference sources. In order to reduce the positioning error of the weighted K-Means clustering when the distance between receives is long, the receiving CNR affected more obviously by interference within each cluster are used to build the localization equations based on DRSS after clustering processing. To solve the equations can obtain the more accurate localization results. Simulation results demonstrate that the proposed scheme can realize the multi-interference localization. Compared with the scheme only including weighted K-Means, the average positioning errors of the proposed method involving DRSS parameters can be reduced by more than 19% and 38% under the two cases of single source and two single-tone sources, respectively.
    • FullText(HTML)
    • References (15)
  • [1]
    WESSON K D, GROSS J N, HUMPHREYS T E, et al. GNSS signal authentication via power and distortion monitoring[J]. IEEE transactions on aerospace electronic systems, 2018, 54(2): 739-754. DOI: 10.1109/TAES.2017.2765258
    [2]
    SHAFIEE E, MOSAVI M R, MOAZEDI M. Detection of spoofing attack using machine learning based on multi-layer neural network in single-frequency GPS receivers[J]. Journal of navigation, 2018, 71(1): 169-188. DOI: 10.1017/s0373463317000558
    [3]
    WU Z, ZHAO Y, YIN Z, et al. Jamming signals classification using convolutional neural network [C]//IEEE International Symposium on Signal Processing and Information Technology, 2017.
    [4]
    JAHROMI A J, BROUMANDAN A, NIELSEN J, et al. GPS spoofer countermeasure effectiveness based on signal strength, noise power, and C/N0 measurements[J]. International journal of satellite communications and networking, 2012, 30(4): 181-191. DOI: 10.1002/sat.1012
    [5]
    GAO P, SUN S L, ZENG Z , et al. GNSS spoofing jamming recognition based on machine learning[C]//The 3rd international conference on signal and information processing, networking and computers (ICSINC), 2017.
    [6]
    邓旭. 基于载噪比的GNSS欺骗式干扰检测方法研究 [D]. 郑州: 战略支援部队信息工程大学, 2022.
    [7]
    靳睿敏, 甄卫民. 基于接收机位置信息的GNSS干扰源定位技术[J]. 全球定位系统, 2020, 45(1): 51-55.
    [8]
    聂大惟, 朱海, 吴飞, 等. 基于RSSI概率分布与贝叶斯估计的加权定位方法[J]. 全球定位系统, 2022, 47(2): 52-59. DOI: 10.12265/j/gnss.2021080902
    [9]
    刘禹秾. 基于终端聚类的导航信号干扰定位 [D]. 北京: 北京邮电大学, 2021.
    [10]
    PSIAKI M L, AKOS D M, THOR J. A comparison of direct RF sampling and down-convert & sampling GNSS receiver architectures[C]//The 16th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GPS/GNSS 2003), 2003: 1941-1952.
    [11]
    SHARAWI M S, AKOS D M, ALOI D N. GPS C/N0 estimation in the presence of interference and limited quantization levels[J]. IEEE transactions on aerospace and electronic systems, 2007, 43(1): 227-238. DOI: 10.1109/TAES.2007.357129
    [12]
    PAULUZZI D, BEAULIEU N. A comparison of SNR estimation techniques for the AWGN channel[J]. IEEE transactions on communications, 2000, 48(10): 1681-1691. DOI: 10.1109/26.871393
    [13]
    朱海, 史文森, 蔡鹏, 等. 压制式干扰环境中GPS信号的载噪比估计算法[J]. 弹箭与制导学报, 2014, 34(3): 209-212. DOI: 10.3969/j.issn.1673-9728.2014.03.054
    [14]
    LIU R, YANG Z W, CHEN Q, et al. GNSS multi-interference source centroid location based on clustering centroid convergence [J]. IEEE access, 2021(9): 108452-108465. DOI: 10.1109/ACCESS.2021.3101250
    [15]
    刘睿, 杨志伟, 陈奇东, 等. 基于信号传播修正的GNSS干扰源质心定位方法[J]. 系统工程与电子技术, 2021, 43(8): 2083-2089. DOI: 10.12305/j.issn.1001-506X.2021.08.08
    • Related Articles

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (136) PDF downloads (15) Cited by()
    Related

    Copyright © 2009《 GNSS World of China 》 Editorial Office

    Address：84 Jianshe Dong Lu, Muye District, Xinxiang City, Henan Province, China China Pos：453000 Tel：0373-3712411 Fax：0373-3052232 E-mail:qqdwxt@126.com

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return