RFID Speed Estimation Using Signal Strength and Phase Unfolding
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Solution Overview
Problem
Existing RFID systems struggle to accurately determine the location and speed of moving objects due to reliance on signal strength measurements, which are noisy and influenced by environmental factors, and lack effective utilization of phase information for precise distance estimation.
Innovation Solution
A computer-implemented method using machine learning models, trained on signal strength profiles and phase information, to predict the speed of RFID-tagged objects, dynamically unfolding phase information using initial velocity values to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If signal strength measurements are used for location and speed determination, then the system can operate with simple measurements, but the measurement precision deteriorates due to noise and environmental influences
Solution Approach 1:
The patent combines signal strength measurements with phase information measurements to determine location and speed. By merging these two measurement types, the system overcomes the limitations of using signal strength alone, achieving higher measurement precision without proportionally increasing system complexity.
Solution Approach 2:
The patent changes the measurement parameters from only signal strength to include both signal strength and phase information. This parameter change enables more accurate determination of location and speed by utilizing additional information from the RFID signal that was previously unused.
2Measurement precision
If phase information is used for distance estimation, then measurement precision improves, but reliability deteriorates due to phase modulation by moving objects and inability to distinguish stationary vs. moving objects
Solution Approach 1:
The patent uses feedback from signal strength measurements to disambiguate phase information. By comparing phase changes with signal strength variations, the system can determine whether phase changes are due to object movement or stationary position, thereby improving reliability while maintaining precision.
Solution Approach 2:
The patent creates a composite measurement approach by combining phase information and signal strength measurements. This composite measurement strategy leverages the strengths of both measurement types while compensating for their individual weaknesses, achieving both high precision and reliability.
3Device complexity
If assumptions about constant velocity and direction are made, then device complexity is reduced, but measurement precision deteriorates due to inability to handle variable movement patterns
Solution Approach 1:
The patent transitions from static assumptions (constant velocity and direction) to a dynamic approach that adapts to variable movement patterns. By using sequential measurements and comparing phase and signal strength changes over time, the system can accurately determine speed and location regardless of whether the object is moving at constant velocity or changing its motion state.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method provides reliable and precise speed determination of RFID-tagged objects, reducing uncertainties and enabling accurate location and tracking.
Implementation Method 1
These tags can be read by corresponding readers using high-frequency radio waves. In many cases, the RFID tag is powered by radio waves generated by the reader
Implementation Method 2
Phase information (or simply phase) essentially measures the path difference between the transmitted RFID antenna pulse ('input wave') and the signal response ('reflected wave') sent back by the RFID tag
Data Source
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AI summary
The invention relates to a computer-implemented method for determining a movement speed, comprising the steps: a. providing a respective speed value for a respective first radio frequency identification tag (RFID) of a plurality of first RFIDs (RFIDs) (S1); b. providing a respective first radio signal and a respective first signal strength profile for the respective first RFID of the plurality of first RFIDs (S2); c. training a machine learning model based on the first speed values and the first signal strength profiles to determine a corresponding speed value based on at least one signal strength profile (S3); d. determining at least one second initial speed value by applying the trained machine learning model to at least one second signal strength profile of at least one second RFID (RFID) (S4); e.Determining at least one second unfolded velocity value by unfolding associated phase information of the at least one second radio tag (TAG) taking into account the at least one second initial velocity value (S5), and providing the at least one second unfolded velocity value as the movement velocity (S6). The invention further relates to a technical system and a corresponding computer program product.