Aiming at the problem of low positioning precision of WiFi fingerprint positioning algorithm based on weighted K-nearest neighbor（ WKNN）

a WiFi fingerprint localization algorithm based on the normalized received signal strength（ RSS） and constraint WKNN is proposed. Use Gaussian filtering for denoising on RSS value acquired in offline and online stage

decrease the random error of signal

and construct radio map; WKNN algorithm based on 4-domain system is used to match and locate

to prevent the reference points far from the specific points to participate in the match

so as to results in error. The experimental results show that the improved WiFi fingerprint positioning algorithm can better estimate the user ’s actual location

the average positioning error is reduced by 19. 4 %.