Aiming at problem of KNN algorithm low precision of indoor positioning based on RSSI

an improved KNN—PIT indoor positioning algorithm is put forward. According to structure feature of indoor space

establish location fingerprint database which has class labels. Introduce virtual reference points

use theory of PIT to further constrain localization area of target point

use positioning algorithm adaptively to carry out positioning.Comprehensively use Gauss filtering and mean filtering to reduce random errors of signal in online and offline stages. Results show that the improved KNN—PIT algorithm can better estimate the user’s actual location

and decrease significantly localization errors

positioning precision is improved by 12. 5 %.