Intelligent positioning method for the packaging of agricultural products based on passive ultra high frequency(UHF) RFID

Location-based services (LBS) are gradually shifting from "outdoor-oriented" to "indoor-outdoor coexistence" in recent years, with the development of positioning technology. Radiofrequency identification (RFID) has brought tremendous progress to the Industrial Internet of Things (IoT). Radio frequency signals can be used to locate indoor objects or people, considering the intelligent identification of target objects. The key technology has also been widely used in inventory management, intelligent positioning, and warehousing, due to the miniaturization and low power consumption. However, the existing absolute/relative RFID positioning has been easily affected by the warehousing environment, packaging materials, and shelf materials, leading to low positioning accuracy. In this study, a passive RFID positioning was proposed to fusion the received signal strength indicator and phase measurement (RP-RaP). Firstly, MATLAB software was used to simulate the actual situation of the warehouse. A wireless channel model was established to simulate the phase integer ambiguity. RSSI analysis was investigated to explore the impact of path loss factor n on positioning accuracy. The values were taken from 2 to 4, in order to obtain the root mean square error parameter of positioning. The RFIF tags were deployed to simulate the given statistical distribution of the measured phase, according to the "ring" and "corridor" types. The maximum likelihood estimation was used for the horizontal positioning of the labels. The RSSI difference was measured by the tilted reader dual antenna for the vertical positioning of the labels. The horizontal and vertical positioning simulation was achieved in the passive ultra-high frequency RFID tags. Secondly, taking the packaging scenario of agricultural products as an example, a radio frequency positioning testing system was set up in the warehouse. The warehouses were mostly shelved to consider the space utilization in reality. The corridor-type label distribution was selected for experimental testing. An RF reader and antenna were installed on the slide rail. The horizontal and vertical positioning analysis was performed on the attached labels on the shelf items. The experimental results showed that the RP-RaP significantly improved the positioning accuracy, with an average horizontal and vertical positioning accuracy of 94.6% and 94.3%, respectively, compared with the traditional indoor positioning (LANDMARC). The positioning with the received signal strength indicator and measurement phase fusion effectively improved the label positioning accuracy in agricultural product packaging scenarios. Several influencing factors on positioning accuracy were discussed, including different materials attached to the label, rotation of the relative angle between the label and the antenna, the shape of the label, and the spacing between the labels. Experimental verification was conducted on the phase and RSSI data under the above conditions. The results indicated that the attachment of metal and liquid packaging to the tag was significant fluctuations for the backscattered phase and RSSI signal, in cases of severe deformation of the tag. This finding can provide a strong basis to further improve the accuracy of RFID indoor positioning.