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An iterative method of processing node flip ambiguity in wireless sensor networks node localization

机译：无线传感器网络节点定位中节点翻转模糊处理的迭代方法

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摘要

In order to solve the problem of the node flip ambiguity generated by using classical least squares method in wireless sensor networks node localization, an iterative method based on triangular node blocks (IP-TNB) to process node flip ambiguity is proposed in this paper. At first, orthogonal projection detection method is adopted to detect an unknown node needed to be positioned. If the node would be detected to have a flip ambiguity, based on the stability of triangle node blocks and the whole network connectivity information, the flip ambiguity node is processed by the iterative method based on coordinate transformation and recursive optimization, so the process can detect and correct the problem of node flip ambiguity using the least squares method. The simulation results demonstrate that IP-TNB has better positioning performance and reduce node localization errors compared with Particle Swarm Optimization (PSO) and Iterative Inflexible Body Merging (IIBM) proposed by Xiao et al. By the simulation experiment of the effect of the number of beacon nodes and range errors on IP-TNB, results show that the proposed method not only can effectively deal with the problem of node flip ambiguity using the least squares method, but also improve the whole network localization accuracy.
机译：为了解决无线传感器网络节点定位中经典最小二乘法产生的节点翻转模糊性问题，提出了一种基于三角节点块（IP-TNB）的迭代算法来处理节点翻转模糊性。首先，采用正交投影检测方法来检测需要定位的未知节点。如果要检测到节点存在翻转歧义，则基于三角形节点块的稳定性和整个网络的连通性信息，可以通过基于坐标变换和递归优化的迭代方法对翻转歧义节点进行处理，从而可以检测到该翻转歧义节点。并使用最小二乘法纠正节点翻转不明确的问题。仿真结果表明，与Xiao等人提出的粒子群优化（PSO）和迭代不灵活体合并（IIBM）相比，IP-TNB具有更好的定位性能，并减少了节点定位错误。通过信标节点数和距离误差对IP-TNB的影响的仿真实验，结果表明，该方法不仅可以有效地解决最小二乘法的节点翻转模糊问题，而且可以改善整体网络定位精度。

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