Indoor localization algorithm based on deep neural network
A received signal strength indication(RSSI)fingerprint positioning algorithm based on deep learning is proposed.The algorithm introduces the deep neural network(DNN)into two stages of fingerprint positioning:the offline stage performs feature training on the fingerprint database of different occlusion conditions,in which the fingerprint data is used as input,and the fingerprint database number of different occlusion conditions is used as the label;in the online stage,the real-time received data is sent to the network for fingerprint database matching,and then combined with the improved weighted K-nearest neighbor(WKNN)algorithm for positioning.Comparison experimental results show that the positioning precision of the proposed algorithm is prior to other positioning algorithms,and it has good positioning performance.
indoor positioningfingerprint positioningreceived signal strength indication(RSSI)
万方数据
维普
