基于单快拍信号到达角估计算法的室内入侵检测

doi:10.11772/j.issn.1001-9081.2020071030

计算机应用 ›› 2021, Vol. 41 ›› Issue (4): 1153-1159.DOI: 10.11772/j.issn.1001-9081.2020071030

所属专题：网络与通信

基于单快拍信号到达角估计算法的室内入侵检测

任晓奎, 刘鹏飞, 陶志勇, 刘影, 白立春

辽宁工程技术大学电子与信息工程学院, 辽宁葫芦岛 125105

收稿日期:2020-07-15 修回日期:2020-10-05 出版日期:2021-04-10 发布日期:2020-11-12
通讯作者: 刘鹏飞
作者简介:任晓奎（1965—），男，辽宁阜新人，副教授，主要研究方向：计算机视觉、信号检测与处理；刘鹏飞（1996—），女，辽宁铁岭人，硕士研究生，主要研究方向：工矿网络、宽带通信；陶志勇（1978—），男，辽宁葫芦岛人，副教授，博士，CCF会员，主要研究方向：物联网、大数据、机器学习；刘影（1983—），女，吉林长春人，副教授，博士，主要研究方向：无线定位、智能无线感知；白立春（1980—），男，辽宁抚顺人，讲师，硕士，主要研究方向：电路与系统、图形图像处理。
基金资助:
国家重点研发计划项目（2018YFB1403303）；辽宁省教育厅项目（LJ2017QL013）；辽宁省自然科学基金指导计划项目（2019-ZD-0038）；辽宁省教育厅高等学校基本科研项目（LJ2017FAL008）。

Indoor intrusion detection based on direction-of-arrival estimation algorithm for single snapshot

REN Xiaokui, LIU Pengfei, TAO Zhiyong, LIU Ying, BAI Lichun

School of Electronics and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China

Received:2020-07-15 Revised:2020-10-05 Online:2021-04-10 Published:2020-11-12
Supported by:
This work is partially supported by the National Key Research and Development Program of China (2018YFB1403303), the Program of the Educational Department of Liaoning Province (LJ2017QL013), the Program of Plan Guided by Liaoning Provincial Natural Science Foundation (2019-ZD-0038), the Basic Scientific Research Project of Colleges and Universities of the Educational Department of Liaoning Province (LJ2017FAL008).

摘要/Abstract

摘要： 针对基于信道状态信息（CSI）的入侵检测方法易受环境布局及噪声干扰的影响从而导致检测率下降的问题，提出一种基于单快拍信号到达角（DOA）估计算法的室内入侵检测方法。首先，结合无线信号空间选择性衰落的特点对天线阵列接收到的CSI数据进行数学分解，并将未知的DOA估计问题转化为一个过完备表示的问题。然后，利用l₁范数对稀疏信号的稀疏性进行约束，通过求解稀疏正则优化问题得到准确的DOA信息，由此在数据层面为最终检测结果提供了可靠的特征参数。最后，根据前后时刻的DOA变化评估出室内安全指数（ISIN），进而实现室内入侵检测。在实验中，利用真实的室内场景对检测方法进行验证，并与传统的主成分分析和离散小波变换的数据预处理方法进行对比。实验结果表明：该方法能够在不同的复杂室内环境下准确检测出入侵行为的发生，平均检测率达到98%以上，且在鲁棒性上明显优于对比算法。

关键词: 到达角估计, 入侵检测, 信道状态信息, 稀疏表示, WiFi

Abstract: Intrusion detection methods based on Channel State Information(CSI) are vulnerable to environment layout and noise interference, resulting in low detection rate. To solve this problem, an indoor intrusion detection method based on the algorithm of Direction-Of-Arrival(DOA) estimation for single snapshot was proposed. Firstly, the CSI data received by the antenna array was mathematically decomposed by combining the feature of spatial selective fading of the wireless signals, and the unknown DOA estimation problem was transformed into an over-complete representation problem. Secondly, the sparsity of the sparse signal was constrained by l1 norm, and the accurate DOA information was obtained by solving the sparse regularized optimization problem, so as to provide the reliable feature parameters for the final detection results at data level. Finally, the Indoor Safety Index Number(ISIN) was evaluated according to the DOA changes before and after the moments, and then indoor intrusion detection was realized. In the experiment, the method was verified by real indoor scenes and compared with traditional data preprocessing methods of principal component analysis and discrete wavelet transform. Experimental results show that the proposed method can accurately detect the occurrence of intrusion in different complex indoor environments, with an average detection rate of more than 98%, and has better performance in robustness compared to comparison algorithms.

Key words: Direction-Of-Arrival (DOA) estimation, intrusion detection, Channel State Information (CSI), sparse representation, WiFi

中图分类号:

TP391.4

任晓奎, 刘鹏飞, 陶志勇, 刘影, 白立春. 基于单快拍信号到达角估计算法的室内入侵检测[J]. 计算机应用, 2021, 41(4): 1153-1159.

REN Xiaokui, LIU Pengfei, TAO Zhiyong, LIU Ying, BAI Lichun. Indoor intrusion detection based on direction-of-arrival estimation algorithm for single snapshot[J]. Journal of Computer Applications, 2021, 41(4): 1153-1159.

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基于单快拍信号到达角估计算法的室内入侵检测

Indoor intrusion detection based on direction-of-arrival estimation algorithm for single snapshot

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