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[1] Sun Minhong, Shao Zhangyi, Bao Jianrong, et al. GNSS spoofing detection based on uncultivated wolf pack algorithm [J]. Journal of Southeast University (English Edition), 2017, 33 (1): 1-4. [doi:10.3969/j.issn.1003-7985.2017.01.001]
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GNSS spoofing detection based on uncultivated wolf pack algorithm()
基于狼群算法的GNSS欺骗干扰识别
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
33
Issue:
2017 1
Page:
1-4
Research Field:
Electromagnetic Field and Microwave Technology
Publishing date:
2017-03-30

Info

Title:
GNSS spoofing detection based on uncultivated wolf pack algorithm
基于狼群算法的GNSS欺骗干扰识别
Author(s):
Sun Minhong1;  2;  Shao Zhangyi2;  Bao Jianrong2;  Yu Xutao1
1School of Information Science and Engineering, Southeast University, Nanjing 210096, China
2School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
孙闽红1;  2;  邵章义2;  包建荣2;  余旭涛1
1东南大学信息科学与工程学院, 南京 210096; 2杭州电子科技大学通信工程学院, 杭州 310018
Keywords:
global navigation satellite system(GNSS);  spoofing detection;  system identification;  uncultivated wolf pack algorithm
全球卫星导航系统;  欺骗干扰检测;  系统辨识;  狼群算法
PACS:
TN973
DOI:
10.3969/j.issn.1003-7985.2017.01.001
Abstract:
In order to solve the problem that the global navigation satellite system(GNSS)receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer, a model-based approach for the identification of the GNSS spoofing is proposed. First, a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel. Then, a novel method based on the uncultivated wolf pack algorithm(UWPA)is proposed to estimate the model parameters. Taking the estimated model parameters as a feature vector, the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors. Simulations verify the effectiveness and the robustness of the proposed method.The results show that, compared with the other identification algorithms, such as least square(LS), the iterative method and the bat-inspired algorithm(BA), although the UWPA has a little more time-complexity than the LS and the BA algorithm, it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing, even for relative low signal-to-noise ratios.
为解决卫星导航接收机在受到欺骗干扰时难以识别欺骗干扰这一问题, 提出了一种基于模型的欺骗干扰识别方法.首先将干扰机/卫星发射机以及通信信道建模为Hammerstein模型, 然后使用一种新的模型辨识方法——狼群算法来进行模型参数辨识.将估计得到的模型参数作为特征参数, 使用欧氏距离比较法实现欺骗干扰的识别.仿真实验验证了所提方法的有效性和鲁棒性.结果表明:狼群算法与最小二乘法、迭代法和蝙蝠算法等其他模型辨识算法相比, 虽然在算法时间复杂度上比最小二乘法和蝙蝠算法略高, 但具有更高的模型参数辨识精度和欺骗干扰识别率, 甚至在信噪比较低时识别性能也最优.

References:

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Memo

Memo:
Biography: Sun Minhong(1974—), male, doctor, associate professor, cougar@hdu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.61271214, 61471152), the Postdoctoral Science Foundation of Jiangsu Province(No.1402023C), the Natural Science Foundation of Zhejiang Province(No.LZ14F010003).
Citation: Sun Minhong, Shao Zhangyi, Bao Jianrong, et al. GNSS spoofing detection based on uncultivated wolf pack algorithm.[J].Journal of Southeast University(English Edition), 2017, 33(1):1-4.DOI:10.3969/j.issn.1003-7985.2017.01.001.
Last Update: 2017-03-20