Hussein Ahmed Abdulqader, Rahman Tharek A, Leow Chee Yen
Wireless Communication Centre (WCC), Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor 81310, Malaysia.
University of Technology, Baghdad 10066, Iraq.
Sensors (Basel). 2015 Dec 4;15(12):30545-70. doi: 10.3390/s151229817.
Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks.
定位是无线传感器网络的一个显著方面,也是众多有趣研究的焦点。需要考虑的一个严峻情况是,在存在物理屏障攻击的情况下,通过分散的传感器网络对移动目标进行定位。这些攻击会扰乱定位过程并导致位置估计误差。基于距离的方法,如接收信号强度指示(RSSI),会受到这类攻击的重大影响。本文提出了一种基于多频多功率定位(C-MFMPL)和阶跃函数多频多功率定位(SF-MFMPL)相结合的解决方案,包括指纹匹配技术和定位算法,以提供一种强大且准确的定位技术。此外,本文还提出了一种网格着色算法来检测网络中的信号空洞图,即易受攻击区域,以便采取纠正措施。仿真结果表明,面对对数正态阴影衰落效应以及存在物理屏障攻击的情况,通过检测、过滤和消除这些攻击的影响,RSS定位性能得到了增强和提高。