The invention discloses a WLAN indoor positioning method for neural network regional training, which relates to the field of indoor positioning. The invention solves the problems great positioning error and redundant cost caused by irregular geographic environment in the existing indoor neural network positioning method. The method is realized in a way that: setting access points (AP) according to the indoor environment; setting reference points in the indoor environment; determining two APs having the greatest influence on the reference point positioning information according to the amplitude of the signal intensity RSS value of each reference point; obtaining a regional training sample set of the neural network according to the adjustment factor mu, thereby training the neural network according to the regional training sample set and obtaining a satisfactory neural network architecture; and finally, importing the signal intensity RSS value of the point to be detected into the neural network architecture, thereby obtaining the positioning coordinates of the point to be detected. The method of the invention is used for positioning in a complex system.