摘要
为解决当前物联网(IOT)恶意特征信号检测方案存在实时捕捉性能不佳,且难以实现对节点运动轨迹精确定位等不足,提出了一种基于超带宽滤波一体化映射机制的IOT恶意特征信号检测算法。首先,考虑到接收信号强度指示(RSSI)定位方法存在的不足,利用聚类中心过滤方式来计算精度映射矩阵,以获取信号发射源的拓扑平面坐标,并设计基于迭代投影矢量的锚节点覆盖方法,提高网络对节点信号发射坐标实时监控强度;根据超宽带多径估计机制,构建恶意节点实时捕捉方法,综合节点坐标的无偏估计及运动过程中能量损失来实现节点动态轨迹的精确捕捉,实现对恶意特征信号发射源动态捕捉。仿真实验表明,与超宽带能量相邻启发算法(ENNH-TSP)及黑洞安全组节点探测算法(SGBB-NDS)相比,所提算法具有更好的动态捕捉性能,具备高精度获取恶意节点运动轨迹的特点。
In order to solve the problems of lower coordinate accuracy,less real-time capture performance and less capturing the trajectory of nodes in the detection of malicious feature signals of the IOT,a malicious feature signal detection algorithm based on ultra-bandwidth filtering integrated mapping mechanism is proposed.Firstly,considering the shortcomings of received signal strength indication location method,the accuracy mapping matrix is computed by using the clustering center filtering to obtain the topological plane coordinates of the signal transmitter,and the anchor node coverage method based on iterated projection vectors is designed to enhance the intensity of real-time monitoring of node signal launching coordinates.The real-time malicious node capture method is constructed according to UWB multipath estimation mechanism,and the accurate capture of nodes dynamic trajectory is realized by integrating unbiased estimation of node coordinates and energy loss in motion to realize the dynamic capture of malicious signature signal transmitter.The simulation results show that this algorithm has better dynamic capture performance and better topology than the ENNH-TSP mechanism and the SGBB-NDS mechanism.
作者
任宏德
吴利明
Ren Hongde;Wu Liming(College of Computer Engineering,North China university of Science and Technology,Langfang 065201,China;School of Management,Hebei University,Baoding 071002,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2019年第7期152-158,共7页
Journal of Electronic Measurement and Instrumentation
基金
中央高校基本科研业务费(3142011074)
河北省物联网监控工程技术研究中心项目(3142016020)
河北省自然科学基金(D2017308099)资助项目
关键词
物联网
恶意特征检测
超带宽滤波
接收信号强度指示
超宽带多径估计
无偏估计
拓扑刻录
internet of things
malicious feature detection
ultra-bandwidth filtering
received signal strength indicators
ultra-wideband multipath estimation
unbiased estimation
topology recording
