UHF RFID Indoor Localization Algorithm Based on BP-SVR

• Published in: IEEE journal of radio frequency identification (Online) Vol. 6; pp. 385 - 393
• Main Authors: Mo, Lingfei, Zhu, Yaojie, Zhang, Dongkai
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna measurements; Antennas; Back propagation networks; BP neural networks; Fingerprint recognition; Indoor environments; indoor localization; Internet of Things; Localization; Location awareness; Machine learning; Neural networks; Optimization; Periodic structures; Phase shift; Radio frequency identification; RFID tags; Signal strength; Support vector machines; SVR; UHF RFID
• ISSN: 2469-7281; 2469-729X
• DOI: 10.1109/JRFID.2022.3145153

With the widespread of Internet of Things (IoT), Radio Frequency Identification (RFID) technology is used in various fields. In the complex indoor environment, the traditional RFID indoor localization algorithm cannot give superior performance. Because a large number of antennas cannot be deployed in practical applications, the dimension of the signal strength feature vector obtained is relatively low, and it is not easy to fully describe the information in the environmental field. Thus, must adopt the appropriate antenna placement structure, the phase difference information can be effectively used as the feature. In this paper, a method of indoor localization algorithm based on Back Propagation-Support Vector Regression (BP-SVR) is proposed, which takes the signal strength and phase difference of the RFID tag as the feature inputs and uses the hidden layer of the neural network to enhance the dimensionality of the data. Moreover, the Sequential Minimal Optimization (SMO) algorithm is used to increase the rate of model learning. The method was valid in a 2D scene. Experimental results show that the method has an average positioning error of 9.5cm in the indoor area of 6m <inline-formula> <tex-math notation="LaTeX">\times </tex-math></inline-formula> 8m.