全球定位系统2024，Vol.49Issue(3)：57-64,8.DOI:10.12265/j.gnss.2023198
改进MixNet的CSI图像指纹室内定位方法
Improved MixNet for indoor localization using CSI image fingerprints
摘要
Abstract
To enhance the performance of indoor localization using channel state information(CSI)fingerprints,an CSI image-based indoor localization method based on the improved MixNet model is proposed.In the offline phase,the method involves selecting the three access points(APs)with the highest received signal strength indication(RSSI)at the reference point(RP),extracting their CSI data,and converting it into image.Subsequently,the improved MixNet model is employed to train on these images and save the model.The improved MixNet model introduces coordinate attention(CA)and residual connections.Specifically,it replaces the squeeze-and-excitation(SE)attention in MixNet-s with CA to enhance the network's information representation capability and extract CSI image fingerprint features more accurately.Moreover,it incorporates residual connections,tailored to the characteristics of the MixNet-s model,to enhance the network's representation capacity and prevent overfitting.Finally,the network depth is reduced to ensure that all network layers are adequately trained.During the online phase,CSI data from the target device is collected and converted into image,and then input into the pre-trained improved MixNet model(named MixNet-CA).The final device position is estimated using a weighted centroid algorithm based on the model's output probabilities.The proposed method is validated in an indoor environment and achieve an average positioning error of 0.362 0 m.关键词
MixNet/坐标注意力/Wi-Fi指纹室内定位/信道状态信息图像/残差连接Key words
MixNet/coordinate attention/Wi-Fi fingerprint indoor positioning/CSI image/residual con-nections分类
天文与地球科学引用本文复制引用
龙良,王小鹏,李岗,王江..改进MixNet的CSI图像指纹室内定位方法[J].全球定位系统,2024,49(3):57-64,8.基金项目
兰州市科技计划项目(2023-3-104) （2023-3-104）
甘肃省高校产业支撑计划项目(2023CYZC-40) （2023CYZC-40）
甘肃省优秀研究生"创新之星"项目(2023CXZY-546) （2023CXZY-546）
