RFID indoor positioning system and method based on artificial neural networks

Abstract

The invention relates to an RFID indoor positioning system and method based on ANNs (artificial neural networks). The RFID indoor positioning method comprises following steps of carrying out positioning area data acquisition in an off-line stage, pre-processing original data, establishing a training database and constructing an ANNs indoor location positioning model; carrying out noise filtering and data normalization pre-processing on the original data by means of a Gaussian filtering principle in dependence on the signal statistical data characteristic; obtaining real time signals in the on-line stage, pre-processing data, inputting the pre-processed data into the ANNs indoor location positioning model constructed in the off-line phase in real time, and outputting the location of the object to be positioned. The RFID indoor positioning system comprises a passive RFID tag, an RFID reader and a computer terminal. Compared with the prior art, the RFID indoor positioning system and method are advantaged in that the noise filtering, pre-processing and positioning precision is high, the Gaussian filtering process calculating time is short, the noise jamming resistance is high, the cost is low and the positioning real-time performance is high and the like.

Description

technical field [0001] The invention relates to the technical field of wireless network and wireless communication positioning, in particular to an artificial neural network-based RFID indoor positioning system and method. Background technique [0002] Following the waves of computer networks, mobile networks and the Internet, the Internet of Things with "intelligence" as the core has become another huge wave in the development of the information industry, and as an indoor location service (Location Based Service, LBS ) Due to its advantages in indoor navigation, personnel tracking, cargo positioning and emergency rescue, etc., it has been increasingly favored by people, and it has shown broad market value and commercial application prospects, such as consumer demand navigation in large shopping malls, smart airports Location tracking of luggage, real-time monitoring of prisoner location information in smart prisons, location tracking of goods in large warehouses, etc. [0...

AI Technical Summary

Problems solved by technology

Its purpose is to solve the problems of high cost, low positioning accuracy, poor real-time performance and poor anti-noise ability of the algorithm to the environment of the indoor positioning system.

Images