无线传感器网络中一种改进的凸规划定位算法
发布时间：2018-10-11 20:05
【摘要】：本文以无线传感器网络中的凸规划(Convex)定位算法为研究对象,针对传统凸规划算法引入无效区域导致定位精度不高的问题,提出了一种改进定位算法Convex-CIS(Circle In Shadow)。Convex-CIS算法在传统凸规划算法基础上,在不增加节点开销和硬件设施的情况下,以多边形的最大内接圆圆心作为定位结果,减少影响定位精度的无效区域,进而降低未知节点的定位误差。仿真表明,Convex-CIS算法能有效提高无线传感器网络中未知节点的定位精度。
[Abstract]:In this paper, the convex planning (Convex) localization algorithm in wireless sensor networks is taken as the research object, aiming at the problem that the traditional convex planning algorithm leads to the low localization accuracy caused by the introduction of invalid areas. In this paper, an improved localization algorithm, Convex-CIS (Circle In Shadow). Convex-CIS algorithm, is proposed. Based on the traditional convex programming algorithm and without adding node overhead and hardware facilities, the maximum circular center of the polygon is used as the location result. Reduce the invalid region which affects the positioning accuracy, and then reduce the location error of unknown nodes. Simulation results show that Convex-CIS algorithm can effectively improve the location accuracy of unknown nodes in wireless sensor networks.
【作者单位】： 南昌大学软件学院;
【基金】：国家自然科学基金项目(61362022,61362008) 江西省科技计划项目(20142BBE50019)
【分类号】：TP212.9;TN929.5
[Abstract]:In this paper, the convex planning (Convex) localization algorithm in wireless sensor networks is taken as the research object, aiming at the problem that the traditional convex planning algorithm leads to the low localization accuracy caused by the introduction of invalid areas. In this paper, an improved localization algorithm, Convex-CIS (Circle In Shadow). Convex-CIS algorithm, is proposed. Based on the traditional convex programming algorithm and without adding node overhead and hardware facilities, the maximum circular center of the polygon is used as the location result. Reduce the invalid region which affects the positioning accuracy, and then reduce the location error of unknown nodes. Simulation results show that Convex-CIS algorithm can effectively improve the location accuracy of unknown nodes in wireless sensor networks.
【作者单位】： 南昌大学软件学院;
【基金】：国家自然科学基金项目(61362022,61362008) 江西省科技计划项目(20142BBE50019)
【分类号】：TP212.9;TN929.5
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