研究目的
To extend the SAR-based localization method to the use of multiple reader antennas for locating static UHF-RFID tags using an Unmanned Grounded Vehicle (UGV) equipped with RFID hardware and SLAM for trajectory knowledge.
研究成果
The multi-antenna SAR-based method effectively locates static UHF-RFID tags with centimeter-order accuracy in indoor environments, eliminating the need for reference tags or large phased array antennas. Combined matching functions, particularly the module of the conjugate complex product, reduce ambiguity and improve estimation in the transverse direction. This approach is robust to multipath and suitable for retail applications, with potential for further optimization in dynamic scenarios.
研究不足
The method requires knowledge of the UGV trajectory, which is achieved through SLAM and may be affected by environmental factors. Phase measurements are subject to noise and multipath effects, though mitigated by movement. The approach is limited to static tags and indoor environments; performance may vary with tag orientation and reader power settings.
1：Experimental Design and Method Selection:
The study employs a multi-antenna Synthetic Aperture Radar (SAR) approach (SARFID method) for UHF-RFID tag localization. It involves processing phase data from two reader antennas on a UGV to compute matching functions and combine them to resolve ambiguities in tag position estimation. Theoretical models include phase-based calculations and normalized cross-correlation operators.
2：Sample Selection and Data Sources:
Thirty-eight UHF passive RFID tags with Monza R6 chips were placed in an indoor environment (7 m x 5 m x 1.5 m volume) with different orientations. Tag ground truth positions were measured using Vicon MX calibrated cameras.
3：5 m volume) with different orientations. Tag ground truth positions were measured using Vicon MX calibrated cameras.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: UGV (Pioneer 3-AT by MobileRobots), UHF-RFID reader (Impinj Speedway Revolution R420), two circularly polarized RFID antennas (WANTENNAX019 and WANTENNAX007 by C.A.E.N. RFID), Laser Range Finder (Hokuyo UTM-30LX), IMU, sonar, and Vicon MX cameras.
4：Experimental Procedures and Operational Workflow:
The UGV was remote-controlled to move along a rectilinear trajectory in front of tagged items. Phase data from the RFID reader antennas were collected at different times due to anti-collision protocols. The UGV's trajectory was determined using SLAM with LRF sensors. Phase samples were processed to generate matching functions, which were combined to estimate tag positions.
5：Data Analysis Methods:
Data analysis involved computing normalized phasor sequences, applying normalized cross-correlation in the spatial domain, and combining matching functions (sum of modules, module of sum, module of conjugate complex product). Monte Carlo simulations were used to evaluate uncertainties, with Gaussian error models for antenna position (std dev 1.5 cm) and phase measurements (std dev 0.4 rad).
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