摘要
针对无线传感器网络中,以蒙特卡罗为基础的移动传感节点定位算法在定位精度和采样效率方面的不足,提出一种DV-Hop辅助的改进蒙特卡罗盒定位算法.通过利用DV-Hop方法获得节点间的真实距离来建立更加精确的锚盒;引入节点随机运动模型,获得节点真实运动速度来优化采样区域,提高定位精度;根据样本到一跳、两跳锚节点的估计距离和真实距离的差值来动态赋予样本不同的权值,提高采样效率.仿真结果表明,当锚节点和未知节点都移动时,所提出算法的定位精度和采样效率与同等条件下的蒙特卡罗盒算法相比均有所提高.
Because of the shortage of positioning accuracy and sampling efficiency of the Monte Carlo localization algorithm in Wireless Sensor Networks （WSN）, an improved DV-Hop-assisted Monte Carlo Boxed localization algorithm was proposed. A more accurate anchor box was built by making use of the actual distances between nodes which were obtained from DV-Hop method. At the same time, the actual speed of node, which was acquired from the random walk mobility model, was used to optimize the sampling are- a so as to improve the positioning accuracy. Finally, to enhance the sampling efficiency, the weight of sample was dynamically changed according to the difference between estimated distance and actual distance of sample to anchor nodes. Simulation results indicated that, compared with the Monte Carlo Boxed localization algorithm,the proposed algorithm had higher positioning accuracy and sampling efficiency where all unknown and anchor nodes moved randomly.
出处
《小型微型计算机系统》
CSCD
北大核心
2017年第5期1017-1021,共5页
Journal of Chinese Computer Systems
基金
江苏省产学研联合创新资金-前瞻性联合研究项目(BY2013015-33
BY2014024
BY2014023-362014
BY2014023-25)资助
