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RFID Technology for Identification and Positioning: Components, Problems, and Solutions

This article provides an introduction to Radio Frequency Identification (RFID) technology, focusing on passive tags that respond to readers. It discusses the main components of RFID, the present problems such as ambiguous phase cycles, self-jamming, and bandwidth limitation, and the solutions to address these issues.

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RFID Technology for Identification and Positioning: Components, Problems, and Solutions

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  1. Introduction • Radio Frequency Identification (RFID) Use passive tag responding to reader. Provide information such as identification and position. • Main components of RDIF • Tags • Readers

  2. Present problems • The ambiguous phase cycles • Self-jamming and bandwidth limitation • Large phase error induced by multi-paths:

  3. Ambiguous phase cycles Since the measured phase is always within [0, 2π), cycle ambiguity exists when the distance is longer than one wavelength. When the measured phase is θ, the actual phase can be θ+2nπ where n is the cycle integer. The cycle integer must be solved correctly in order to reduce ambiguity in the 3D location.

  4. Self-jamming and bandwidth limitation • Two mainly leakage signals • Direct leakage • Reflection from antenna • Bode-Fano criteria

  5. Phase error induced by multi-paths • Multi-paths will cause large phase error, Which will also leads to ambiguous phase cycle.

  6. Nonlinear backscatter localization system

  7. Self-jamming elimination • Produce second or higher-order harmonics passive respond • Use LPF/HPF to filter selected frequencies.

  8. HMFCW Ranging Algorithm • They prove that when , the n can be 100% reliable. • They prove that • So, when the bandwidth is unlimited, the tolerance of multi-path phase error can be very large (about -45°~45°)

  9. 3D Localization Algorithm • each ranging result is a differential distance from a tag to two Rx antennas at different position, in 3D space, one differential distance measurement gives a hyperboloid. • Solve the problem with Fletcher-Reeves nonlinear conjugate gradient (CG) method.

  10. Results

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