无源标签多径环境下基于凸优化的定位算法

发布时间：2018-11-17 19:33

【摘要】：在室内无源超高频RFID定位中,多径传播对定位结果的影响不可忽视.为了提高复杂多径环境下的定位精度,提出了基于半定规划(SDP)和二阶锥规划(SOCP)的相位差欧式距离拟合定位算法.运用参考标签的位置信息,对参考标签之间的理想相位差欧氏距离与实际距离进行拟合,实现标签之间的距离估计.建立待定位标签与阅读器、参考标签距离估计模型,将多径传播、高斯白噪声、相位差欧氏距离拟合引起的距离估计误差等效为正态分布,利用参考标签的相位差信息和位置信息计算出正态分布参量.仿真结果表明,提出的算法在最大多径数目为7时,定位误差有90%,的概率低于2.3,m,定位性能优于传统的基于测距的定位算法.
[Abstract]:In indoor passive UHF RFID location, the influence of multipath propagation on location results can not be ignored. In order to improve the positioning accuracy in complex multipath environment, a phase difference Euclidean distance fitting algorithm based on semidefinite programming (SDP) and second-order cone programming (SOCP) is proposed. The Euclidean distance of ideal phase difference between reference labels and the actual distance are fitted with the position information of reference labels, and the distance estimation between reference labels is realized. The distance estimation model of tag and reader to be located is established, and the distance estimation error caused by multipath propagation, Gao Si white noise and phase difference Euclidean distance fitting is equivalent to normal distribution. The normal distribution parameters are calculated by using the phase difference information and the position information of the reference label. The simulation results show that when the maximum number of multipath is 7, the localization error is 90 and the probability is less than 2.3 m.The performance of the proposed algorithm is better than that of the traditional location algorithm based on ranging.
【作者单位】：天津大学微电子学院;
【基金】：国家自然科学基金资助项目(61671318,61401301) 天津市应用基础与前沿技术研究资助项目(15JCQNJC41900)~~
【分类号】：TP391.44

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