基于电力线室内定位算法研究

针对现有室内定位系统成本高、供电不方便和扩展性差等问题,提出了基于电力线室内定位系统,论述该系统工作原理。在此基础上,提出基于支持向量分类机SVCM和K近邻法KNN的混合室内定位算法进行定位并详细论述其原理;通过试验采集信号,分析了基于电力线定位信号室内传播特点,建立了接收信号强度RSS特征样本库;最后分别应用SVCM、KNN以及SVCM-KNN算法进行定位实验,对比了三者定位性能。实验结果表明,SVCM-KNN算法可以有效降低定位误差,达到室内定位精度的要求。

Research on indoor positioning algorithm based on power-line

Aiming at the deficiencies of high cost, inconvenience in powering the positioning system and poor scalability of the existing indoor positioning systems, this paper proposes an indoor positioning system based on power-line; and the working principle of the system is discussed. On the basis of above the hybrid indoor positioning algorithm based on Support Vector Classification Machine and K-Nearest Neighbor is proposed. The principle of the algorithm is discussed in detail. Through the signal collection with the acquisition system, the indoor transmission characteristics of the positioning signal based on power-line is analyzed and the RSSI feature sample library is established. At last, the positioning experiments were conducted using SVCM, KNN and SVCM KNN algorithms; their positioning performances were compared. The experiment results show that the SVCM-KNN algorithm can reduce the position error effectively and achieve the indoor positioning precision requirement.