基于局部线性嵌入和梯度提升决策树的信道状态信息室内指纹定位算法研究  

Channel State Information Indoor Fingerprint Localization Algorithm Based on Locally Linear Embedding and Gradient Boosting Decision Tree

作　　者：李新春[1] 赵忠婷 于洪仕[1] Li Xinchun;Zhao Zhongting;Yu Hongshi(School of Electronics and Information Engineering,Liaoning Technical University,Huludao,Liaoning 125105,China;Graduate School,Liaoning Technical University,Huludao,Liaoning 125105,China)

机构地区：[1]辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛125105 [2]辽宁工程技术大学研究生院,辽宁葫芦岛125105

出　　处：《激光与光电子学进展》2022年第2期392-402,共11页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61372058);辽宁省教育厅青年项目(NOLJ2019QL024)。

摘　　要：针对室内定位中相邻定位点之间信道状态信息(CSI)指纹特征易模糊和定位算法鲁棒性低等问题,提出了一种基于局部线性嵌入(LLE)和梯度提升决策树(GBDT)的定位算法。离线阶段,首先将经过预处理的幅值和相位作为CSI联合指纹,然后再用LLE降维前用弹性网络(EN)对联合指纹的不同子载波进行加权,既保证了降维后CSI指纹的真实性又增强了其独有的特征,最后用基于果蝇优化算法(FOA)改进的GBDT算法训练降维后的数据以提高CSI指纹的可靠性和稳定性,并建立指纹库。在线阶段,将待测点的联合指纹代入LLE+GBDT算法训练出指纹信息,然后通过与指纹库匹配预测出待测点的物理位置。室内定位实验结果表明,所提算法相较于对比算法具有较高的定位精度和鲁棒性,具有一定的应用价值。Aiming at the problems such as the low algorithm robustness and easily blurred fingerprint of channel state information(CSI)in indoor localization,a location algorithm based on locally linear embedding(LLE)and gradient boosting decision tree(GBDT)is proposed.In the offline stage,first,the preprocessed amplitude and phase are regarded as joint CSI fingerprints,and then the individual subcarriers of the joint fingerprint are weighted using the elastic network(EN)algorithm before dimensionality reduction by LLE,which not only ensures the authenticity of CSI fingerprint after dimensionality reduction,but also enhances its unique characteristics.Finally,GBDT algorithm based on fruit fly optimization algorithm(FOA)is used to train the reduced dimension data to improve the reliability and stability of CSI fingerprint,and the fingerprint database is established.In the online stage,the LLE+GBDT algorithm is adopted to find the fingerprint information of the test point,so that actual physical locations can be predicted by matching with the fingerprint library.The indoor localization experiments results show that the proposed algorithm has higher localization accuracy and robustness compared with the comparison algorithm,and has certain application value.

关 键 词：室内定位 信道状态信息 梯度提升决策树 局部线性嵌入 

分 类 号：TN925.93[电子电信—通信与信息系统]