RSSI (Received Signal Strength Indicator) weighted centroid algorithm-based passive RFID (Radio Frequency Identification Device) label locating method

Abstract

The invention relates to an RSSI (Received Signal Strength Indicator) weighted centroid algorithm-based passive RFID (Radio Frequency Identification Device) label locating method, which comprises the steps of: calculating a corresponding Euclidean distance according to a to-be-located label and a signal strength value of a reference label relative to an RFID antenna, finding known reference labels of K coordinates, which are closest to the to-be-located label, wherein K is generally selected to be 4 according to the existing experiment result; calculating weights of the K reference labels which are closest to the to-be-located label; and finally, figuring out coordinates of the to-be-located label according to the coordinates and the weights of the reference labels. The method achieves a better balance between location cost and property, has the advantages of convenience, flexibility, easy configuration and the like, and can be suitable for a large quantity of RFID passive labels on the market; and because an RSSI is easy to obtain, a location system can also have better instantaneity.

Description

technical field [0001] The invention relates to a RFID (radio frequency identification) tag positioning method, in particular to a passive RFID tag positioning method based on an RSSI centroid weighting algorithm. Background technique [0002] With the development of embedded technology, the computing power of mobile devices is also increasing significantly. As a typical representative of mobile computing services, the successful popularization and application of GPS (Global Positioning System) system has made people have a new understanding of positioning services, and also put forward new requirements. Location-based services (Location-Base Service) have broad application prospects in many fields such as life, production, commerce, medical care, logistics, and transportation. Among many indoor positioning technologies, RFID technology is receiving more and more attention and favor due to its advantages of non-line-of-sight, non-contact, and low cost, and has become the pr...

AI Technical Summary

Problems solved by technology

The advantage of using scene analysis for positioning is that it does not require the participation of the target to be positioned, and it is carried out without the knowledge of the tag to be positioned. It has a certain degree of confidentiality. The disadvantage is that it is necessary to collect The scene data and establish a data set, and when the positioning area scene changes, the data set needs to be re-established

The advantage of using the neural network is that the system has high efficiency and good scalability, and it can be reasoned to generate an automatic identification system. The disadvantage is that it is not easy for users who are not familiar with the principle of the positioning system to understand.

The disadvantage is that the positioning form is relatively simple, and it can only passively wait for the positioning result, and it is not convenient to actively initiate positioning and track an object that may be in a moving state.

In practical applications, due to the influence of the indoor environment (such as refraction and reflection of wireless signals), the same strength of the signal does not necessarily spread out in a circle, and the attenuation power of the reader is constantly adjusted to determine the signal received by the tag. Intensity, the real-time performance of the system is not ideal

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