基于移动终端双模定位的多场景入侵报警方法  

Multi⁃scenario intrusion alarm method based on dual⁃mode location of mobile terminal

作　　者：许放 欧清海 张晖 艾雪瑞 程方圆 XU Fang;OU Qinghai;ZHANG Hui;AI Xuerui;CHENG Fangyuan(Beijing FibrLink Communications Co.,Ltd.,Beijing 100070,China)

机构地区：[1]北京中电飞华通信有限公司,北京100070

出　　处：《电子设计工程》2024年第9期6-10,共5页Electronic Design Engineering

基　　金：国家自然科学基金(61302074)。

摘　　要：针对现有入侵检测算法精度偏低且漏检情况较为严重的问题,文中提出了一种基于移动终端双模定位的入侵检测算法。该算法构建了包括监测模块、移动终端模块、无线传输模块、中心数据处理模块及自动报警模块等组成的硬件系统。同时在双模定位技术的基础上,采用最速下降法(SDA)和遗传算法(GA)辅助下的粒子滤波法(GPF)对双模入侵定位数据加以校准,从而设计了基于移动终端双模定位的入侵检测算法。在不同场景下进行的实验测试结果验证了所提算法的可靠性,对比同类入侵报警方法,其误检率低至3.8%,漏检率则平均下降了约70%,而且其他性能指标也优于同类文献。Aiming at the problems of low accuracy and serious missing detection of existing intrusion detection algorithms,this paper proposes an intrusion detection algorithm based on dual-mode location of mobile terminals.The algorithm constructs a hardware system consisting of monitoring module,mobile terminal module,wireless transmission module,central data processing module and automatic alarm module.At the same time,on the basis of dual-mode location technology,the Steepest Descent Algorithm(SDA)and Genetic Particle Filter(GPF)method assisted by Genetic Algorithm(GA)are used to calibrate the dual-mode intrusion location data,and an intrusion detection algorithm based on dual-mode location of mobile terminals is designed.The experimental results in different scenarios verify the reliability of the proposed algorithm.Compared with similar intrusion alarm methods,the false detection rate is as low as 3.8%,and the missed detection rate is reduced by about 70%on average,and other performance indicators are also better than similar literature.

关 键 词：双模定位 入侵检测算法 卷积神经网络 融合算法 

分 类 号：TN711[电子电信—电路与系统]