基于RFID技術(shù)的室內(nèi)定位系統(tǒng)的研究
[Abstract]:With the rapid development of mobile communication and wireless technology, indoor wireless positioning technology needs more and more widely. In outdoor positioning, GPS and wireless cellular positioning systems have been widely used in all aspects of working life. In the indoor positioning system, there are Zig Bee positioning technology, ultrasonic positioning technology, infrared positioning technology, Bluetooth positioning technology, radio frequency identification (RFID) positioning technology and Wi-Fi positioning technology, etc. The multipath effect is very serious, and most of these techniques are not very good. In contrast, RFID (RFID) technology has the advantages of low cost, non-visual distance, non-contact, and can combine with Internet communication technology to achieve global object tracking identification and information sharing. In this paper, the RFID technology related to RFID indoor positioning system and TOA,RSSI,TDOA localization algorithms are summarized, and then based on the classical RFID indoor positioning algorithm LANDMARC, its working principle is analyzed. The performance characteristics and various factors that may affect the positioning accuracy are discussed. This paper improves the LANDMARC algorithm in two aspects. First, gridding the location area. The reference label in the location area is meshed, that is, the RSSI value between each reference label is processed more finely, so that the location of the tag can be determined more accurately without adding the reference label. Secondly, the selection of adjacent reference labels for test labels is improved. The improved algorithm adopts the idea of clustering and selects the reference label which is closest to the RSSI value of the tag to be tested as the adjacent tag so that the influence between the reader and the tag can be ignored and the actual position of the tag to be tested can be more accurately displayed. Finally, the improved algorithm is simulated by Matlab. The simulation results show that the error of the improved algorithm is lower than that of the original LANDMARC algorithm in most cases, and the average positioning accuracy is nearly three times higher than that of the original algorithm.
【學(xué)位授予單位】:南昌大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TP391.44
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