自组织映射节点定位算法中邻域函数的优化方法研究
发布时间：2019-02-16 03:24
【摘要】：针对无线传感器网络全节点定位求精问题展开研究,应用自组织映射算法进行定位求精,提出一种优化领域函数,实现快速收敛的双向调整定位算法.利用传感器节点作为神经元节点,通过节点间距离相关度建立自组织神经元网络,通过双向调整邻域函数实现算法对节点间距与测量距离误差的正负性的适应能力,达到收敛性、高定位精度性、快速性要求,最终实现传感器网络的自组织定位.应用MATLAB仿真对本文提出的算法与单向调整算法进行比较,本文提出的算法较大地提高了算法的收敛性和定位精度,较好地反映传感器节点的拓扑结构,且稳定性好.
[Abstract]:In order to solve the problem of all-node location refinement in wireless sensor networks (WSN), the self-organizing mapping algorithm is applied to the localization refinement, and an optimized domain function is proposed to realize the fast convergence bidirectional adjustment localization algorithm. The sensor node is used as the neuron node, the self-organizing neural network is established by the distance correlation between the nodes, and the adaptive ability of the algorithm to the positivity of the distance between the nodes and the measurement distance error is realized by bidirectional adjustment of the neighborhood function. To achieve convergence, high positioning accuracy, fast requirements, and finally achieve the sensor network self-organization localization. The proposed algorithm is compared with the unidirectional adjustment algorithm by using MATLAB simulation. The proposed algorithm greatly improves the convergence and positioning accuracy of the algorithm, and reflects the topology structure of the sensor node well, and has good stability.
【作者单位】： 三峡大学计算机与信息学院;三峡大学智能视觉与图像信息研究所;
【基金】：湖北省自然科学基金项目(2012FFC09701)资助 水电工程智能视觉监测湖北省重点实验室开放基金项目(2014KLA05)资助
【分类号】：TP212.9;TN929.5
本文编号：2423992
[Abstract]:In order to solve the problem of all-node location refinement in wireless sensor networks (WSN), the self-organizing mapping algorithm is applied to the localization refinement, and an optimized domain function is proposed to realize the fast convergence bidirectional adjustment localization algorithm. The sensor node is used as the neuron node, the self-organizing neural network is established by the distance correlation between the nodes, and the adaptive ability of the algorithm to the positivity of the distance between the nodes and the measurement distance error is realized by bidirectional adjustment of the neighborhood function. To achieve convergence, high positioning accuracy, fast requirements, and finally achieve the sensor network self-organization localization. The proposed algorithm is compared with the unidirectional adjustment algorithm by using MATLAB simulation. The proposed algorithm greatly improves the convergence and positioning accuracy of the algorithm, and reflects the topology structure of the sensor node well, and has good stability.
【作者单位】： 三峡大学计算机与信息学院;三峡大学智能视觉与图像信息研究所;
【基金】：湖北省自然科学基金项目(2012FFC09701)资助 水电工程智能视觉监测湖北省重点实验室开放基金项目(2014KLA05)资助
【分类号】：TP212.9;TN929.5
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