期刊
出版社
IEEE
DOI: 10.1109/nics48868.2019.9023805
关键词
Indoor Positioning; UWB; Impulse Response; NLOS; CNN
资金
- Beijing Excellent Talent Support Program [2016000026833ZK08]
- Support Plan for the Construction of High Level Teachers in Beijing Municipal Universities [CITTCD201704065]
- Discipline construction project of Beijing Information Science & Technology University [5121911006]
- Beijing Science and Technology Project [Z191100001419001]
In the field of indoor positioning, ultra-wideband (UWB) communication technology is the key technology. But the errors caused by non-line of sight (NLOS) communication channels could greatly affect the positioning accuracy. Therefore, identifying the channel type can effectively avoid the above-mentioned errors, thereby helping to reduce the loss of positioning accuracy. This paper proposes a LOS/NLOS channel identification method by using a convolutional neural network (CNN) to identifying the impulse response figures of the channels. This method is capable of identifying four different types of channel impulse response figures and providing excellent identification accuracy. The results show that the accuracy of identifying LOS (0-4m), NLOS (0-4m), NLOS (4-10m) and extreme NLOS channel impulse response figures can reach 98.24%.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据