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Underdetermined RFID tag anti-collision method based on optimized bounded component analysis
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AI
DOI：10.1016/j.peva.2026.102542.png)
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Abstract
En 中文
In order to better solve the underdetermined anti-collision problem of RFID system, this paper optimizes the blind source separation algorithm from the initial mixing matrix. Since the mixing matrix determines the linear mapping relationship between the source signal and the observed signal, it directly affects the convergence of the separation algorithm and the quality of the separation results. Therefore, the selection of the initial mixing matrix is crucial to the performance and effectiveness of the algorithm. This paper adopts the successive non-negative projection algorithm (SNPA) to calculate the initial mixing matrix, abandons the traditional random initialization, and avoids the algorithm from falling into the local optimal solution. Then the bounded component analysis (BCA) algorithm is used to separate the mixed signal. The algorithm completes the separation of the mixed tag source signal without considering the arrangement and phase uncertainty of the source signal estimation. The simulation results show that the algorithm can effectively separate the tag source signal and has higher accuracy than the existing algorithms under both low and high signal-to-noise ratio conditions. Its low bit error rate also shows that the system can effectively handle interference and noise during data transmission or reception, thereby reducing the occurrence of data errors.
Keywords:
RFID
Underdetermined
Anti-collision
SNPA
BCA
Journal
P
IF:
0.8
Papers:
38
Citations:
851