Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition - Mu ZHOU; Yuexin LONG; Qiaolin PU; Yong WANG; Wei HE (Tongxin xuebao)
Aiming at the problem that as the scale of the fingerprint database increases, the training cost and processing complexity of CSI fingerprints will also greatly increase, an indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition was proposed.Firstly, the tensor decomposition algorithm based on the PARAFAC (parallel factor) analysis model and the ALS (alternate least squares) iterative algorithm were combined to reduce the interference of the environment.Then, the tensor wavelet decomposition algorithm was used to extract the feature and obtain the CSI fingerprint.Finally, a localization model was established based on the PLSR (partial least squares regression) algorithm to realize the location estimation.Experimental results show that the confidence probability of the proposed method is 94.88% within 4 m localization error, which verifies that the proposed method has good localization performance while fitting the relationship between CSI location fingerprints and location coordinates.