A data reading method and system based on RFID reader

Abstract

The application discloses a data reading method and system based on an RFID reader and writer, and particularly relates to the field of radio frequency identification data collection, and is used for solving the problem of the decline of communication reliability of an existing RFID system caused by carrier frequency offset and multipath interference in a high-speed moving environment; phase change characteristics and a bit error rate index are obtained by analyzing double-antenna receiving signals; when the bit error rate is out of limit, spatial correlation and bit error rate distribution difference are jointly analyzed to determine a multipath interference level; a relative motion state is judged by detecting a phase trajectory curvature characteristic; and data reading is re-performed by dynamically selecting an optimal modulation and coding mode according to a calculated motion speed evaluation and the interference level, so that the optimal balance between communication speed and reliability in a moving environment is realized.

Description

Technical Field

[0001] This invention relates to the field of radio frequency identification (RFID) data acquisition technology, and in particular to a data reading method and system based on an RFID reader. Background Technology

[0002] In the field of radio frequency identification (RFID)-based data acquisition, RFID readers communicate with electronic tags via radio waves to acquire data. To improve communication efficiency and data rate, existing technologies employ various modulation and coding methods, among which higher-order modulation methods can carry more data information per unit time. This technology is widely used in scenarios requiring high-speed data exchange, such as logistics, asset tracking, and production automation. In practical applications, this solution can operate stably when the reader and tag are in a relatively stationary state.

[0003] However, when there is high-speed relative motion between the reader and the electronic tag, the resulting carrier frequency offset will seriously affect the communication link, causing the phase of the received signal to change continuously. This leads to a large number of bit errors in the demodulation process of the signal using high-order modulation, significantly reducing the reliability of data reading. It is difficult to balance the data communication rate and reliability in high-speed mobile environments, thus affecting the application effect of radio frequency identification technology in high-speed mobile scenarios. Summary of the Invention

[0004] This invention addresses the technical problems existing in the prior art by providing a data reading method and system based on an RFID reader.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0006] This invention provides the following technical solution:

[0007] A data reading method based on an RFID reader includes:

[0008] S1. The reader sends a query command to the electronic tag using the first modulation and coding method and receives a response signal;

[0009] S2. Analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and extract the channel response from the signals received by the two antennas of the reader respectively;

[0010] S3. When the bit error rate exceeds the preset threshold, the multipath interference level of the current environment is determined by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment.

[0011] S4. Geometric feature extraction is performed on the signal phase change characteristics. The curvature characteristics of the phase change trajectory on the complex plane are analyzed to determine whether there is a continuous unidirectional phase drift.

[0012] S5. If there is a continuous unidirectional phase drift, calculate the relative motion velocity estimate based on the phase drift direction and rate.

[0013] S6. Based on the relative motion speed estimate and multipath interference level, select the second modulation and coding scheme that matches the current motion speed and channel environment to reread the data.

[0014] Furthermore, the first modulation and coding scheme is a high-order modulation and coding scheme;

[0015] Sending query commands includes sending query commands to electronic tags using quadrature phase shift keying modulation or quadrature amplitude modulation.

[0016] The received response signal includes receiving the modulated signal reflected back from the electronic tag through the reader's receiving antenna.

[0017] Furthermore, the analysis of the response signal includes: extracting signal phase change features from the response signal using phase-locked loop technology: using a phase detector to compare the phase of the response signal with the local oscillation signal, smoothing the phase error signal through a loop filter, and controlling the voltage-controlled oscillator to output a synchronization signal that tracks the phase of the signal, thereby extracting continuous signal phase change features;

[0018] The bit error rate (BER) of the response signal is calculated using a cyclic redundancy check (CRC) method: polynomial division is performed on the data frames in the response signal to generate a check code. The generated check code is compared bit by bit with the received check code, and the ratio of the number of mismatched bits to the total number of bits is used as the BER.

[0019] Channel estimation is performed on the received signals from the two antennas respectively, and the channel responses of the two antennas are extracted.

[0020] Furthermore, when the bit error rate exceeds a preset threshold, the multipath interference level of the current environment is determined by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment, including:

[0021] When the bit error rate exceeds the corresponding preset threshold, the spatial correlation coefficient is calculated based on the response of the two antenna channels and converted into the spatial interference level.

[0022] Calculate the bit error rate of the preamble sequence and the data segment separately, and then calculate the relative difference value.

[0023] Multi-dimensional feature fusion is performed between the spatial interference level and the relative difference in bit error rate: a two-dimensional decision matrix is ​​established between the spatial interference level and the relative difference in bit error rate. Multipath interference level determination rules are preset according to different level combinations. The final multipath interference level is determined according to the position of the current spatial interference level and the relative difference in bit error rate in the two-dimensional decision matrix.

[0024] Furthermore, calculating the spatial correlation coefficient based on the two antenna channel responses and converting it into a spatial interference level includes: calculating the cross-correlation coefficient of the two antenna channel response vectors, comparing the cross-correlation coefficient with multiple preset level thresholds, and quantifying the spatial correlation into discrete spatial interference levels based on the comparison results.

[0025] Furthermore, the calculation of the relative difference between the bit error rates of the preamble sequence and the data segment includes: separately counting the number of erroneous bits in the preamble sequence and the number of erroneous bits in the data segment, calculating the absolute difference between their bit error rates, and using the ratio of the absolute difference to the total bit error rate as the relative difference in bit error rates.

[0026] Furthermore, geometric feature extraction is performed on the signal phase change characteristics. By analyzing the curvature characteristics of the phase change trajectory in the complex plane, it is determined whether there is a continuous unidirectional phase drift, including:

[0027] The phase change characteristics of a signal at multiple consecutive moments are mapped to a sequence of coordinate points on the complex plane to form a phase trajectory.

[0028] Calculate the curvature values ​​at each point on the phase trajectory and statistically analyze the curvature distribution characteristics;

[0029] When the curvature distribution characteristics show that the curvature value is consistently below the motion determination threshold and the phase change direction is consistent, it is determined that there is a continuous unidirectional phase drift.

[0030] Furthermore, if a continuous unidirectional phase drift exists, the relative velocity estimate is calculated based on the phase drift direction and rate, including:

[0031] The radial direction of relative motion is determined based on the phase drift direction;

[0032] Calculate the Doppler frequency shift based on the phase change rate;

[0033] The Doppler frequency shift is converted into an estimate of relative motion velocity using the Doppler frequency shift calculation formula, which includes the carrier frequency parameter and the speed of light constant.

[0034] Furthermore, based on the relative motion speed estimate and multipath interference level, a second modulation and coding scheme matching the current motion speed and channel environment is selected for data re-reading, including:

[0035] Establish a modulation and coding configuration mapping table that includes combinations of different relative motion speed ranges and multipath interference levels;

[0036] Query the modulation and coding configuration mapping table based on the combination of the current relative motion speed estimate to its speed range and the current multipath interference level;

[0037] Select the corresponding modulation and coding configuration in the mapping table as the second modulation and coding method to reread the data.

[0038] On the other hand, the present invention provides a data reading system based on an RFID reader, comprising:

[0039] The signal transceiver module is used by the reader to send query commands to the electronic tag in the first modulation and coding scheme and to receive response signals.

[0040] The signal analysis module is used to analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and to extract the channel response from the signals received by the two antennas of the reader.

[0041] The interference analysis module is used to determine the multipath interference level of the current environment by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment when the bit error rate index exceeds a preset threshold.

[0042] The feature extraction module is used to extract geometric features of signal phase change features. It analyzes the trajectory curvature features of phase change in the complex plane to determine whether there is a continuous unidirectional phase drift.

[0043] The velocity estimation module is used to calculate the relative motion velocity estimate based on the phase drift direction and rate if there is a continuous unidirectional phase drift.

[0044] The reread control module is used to select a second modulation and coding scheme that matches the current motion speed and channel environment to reread the data based on the relative motion speed estimate and multipath interference level.

[0045] The beneficial effects of this invention are:

[0046] 1. By employing a multi-dimensional environmental perception and intelligent modulation switching mechanism, the reliability of data reading in high-speed mobile scenarios is significantly improved. By analyzing the phase change characteristics and bit error rate distribution of the response signal in real time, combined with the spatial correlation analysis of the dual-antenna channel response, the multipath interference level can be accurately identified and the relative motion state can be detected. Based on the geometric analysis of the curvature characteristics of the signal phase trajectory, the random phase fluctuations caused by environmental reflections and the continuous unidirectional phase drift caused by motion can be effectively distinguished, thereby accurately calculating the relative motion speed. This overcomes the limitations of single signal feature analysis and ensures the accuracy of environmental state judgment. On this basis, the optimal modulation and coding scheme is adaptively selected according to the real-time motion speed and channel conditions, which not only ensures the communication reliability during high-speed motion but also maintains a high data transmission rate in stationary or low-speed states.

[0047] 2. Achieving a dynamic optimal balance between communication rate and reliability, by establishing a joint mapping model between motion speed and multipath interference level, the most suitable modulation and coding scheme is intelligently selected for different scenarios, effectively solving the problem of insufficient adaptability of traditional fixed modulation schemes in mobile environments. When high-speed motion is detected, it automatically switches to a modulation scheme with stronger anti-interference capabilities to ensure the stability of data reading; in a relatively stationary state, a higher-order modulation scheme is adopted to improve data transmission efficiency, which not only extends the readable range of the tag, but also improves the communication success rate in complex environments, providing reliable technical support for application scenarios such as logistics tracking and mobile asset management. Attached Figure Description

[0048] Figure 1 This is a flowchart of a data reading method based on an RFID reader / writer according to the present invention;

[0049] Figure 2 This is a schematic diagram of the structure of a data reading system based on an RFID reader according to the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Example 1: Figure 1 This invention provides a data reading method based on an RFID reader, comprising:

[0052] S1. The reader sends a query command to the electronic tag using the first modulation and coding method and receives a response signal;

[0053] S2. Analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and extract the channel response from the signals received by the two antennas of the reader respectively;

[0054] S3. When the bit error rate exceeds the preset threshold, the multipath interference level of the current environment is determined by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment.

[0055] S4. Geometric feature extraction is performed on the signal phase change characteristics. The curvature characteristics of the phase change trajectory on the complex plane are analyzed to determine whether there is a continuous unidirectional phase drift.

[0056] S5. If there is a continuous unidirectional phase drift, calculate the relative motion velocity estimate based on the phase drift direction and rate.

[0057] S6. Based on the relative motion speed estimate and multipath interference level, select the second modulation and coding scheme that matches the current motion speed and channel environment to reread the data.

[0058] S1. The reader sends a query command to the electronic tag and receives a response signal using the first modulation and coding scheme, implemented as follows:

[0059] During data reading, the reader first sends a query command to the electronic tag using the first modulation and coding scheme. This first modulation and coding scheme employs a higher-order modulation and coding scheme, which increases the data transmission rate by increasing the number of bits carried per symbol, making it suitable for the initial communication establishment phase when channel conditions are favorable. Specifically, the higher-order modulation and coding scheme can use orthogonal phase-shift keying (QPSK) modulation, for example, using four phase states of the carrier signal (0 degrees, 90 degrees, 180 degrees, and 270 degrees) to represent 2-bit data combinations; or it can use orthogonal amplitude modulation, for example, simultaneously changing the amplitude and phase of the carrier signal to form 16 different signal points to represent 4-bit data combinations. In actual implementation, the reader's transmitting circuit generates a carrier signal at a specific frequency. The baseband processor maps the query command data stream into corresponding modulation symbols. The modulator adjusts the phase or amplitude of the carrier signal according to the symbol value, and finally, the modulated signal is transmitted to the transmitting antenna through a power amplifier.

[0060] When sending a query command, the reader's digital signal processing unit generates a complete frame structure containing a preamble and command data. The preamble consists of a specific bit sequence, such as an alternating 10101010 sequence, used for subsequent signal synchronization and channel estimation. During modulation, a raised cosine filter with a roll-off factor of 0.35 is used for pulse shaping. This roll-off factor can be adjusted from 0.3 to 0.5 depending on the actual application scenario to achieve a balance between limiting signal bandwidth and reducing intersymbol interference. The center frequency of the transmitted signal is set in the ultra-high frequency band, such as a frequency point between 920MHz and 925MHz. The specific frequency selection must comply with the radio frequency planning requirements of the region. The transmit power is set to an adjustable value according to the reader's operating level, typically in the range of 0.5 watts to 2 watts. The specific value is determined based on the read / write distance requirements of the actual application scenario. For example, a lower transmit power can be used in indoor environments, while a higher transmit power can be used in outdoor long-distance reading scenarios.

[0061] When receiving a response signal, the reader simultaneously captures the modulated signal reflected back from the electronic tag using two spatial diversity receiving antennas. Each receiving antenna is designed with circular polarization to reduce the impact of antenna orientation on signal reception. The received signal is first pre-amplified by a low-noise amplifier, with the amplification gain automatically adjusted according to the received signal strength, for example, within a range of 20 dB to 60 dB. The signal is then down-converted to an intermediate frequency (IF) signal by a mixer, with the IF frequency chosen, for example, at 10.7 MHz. The selection of this frequency value must take into account the implementation complexity of the filter and image frequency suppression requirements. After bandpass filtering, the IF signal is converted into a digital signal by an analog-to-digital converter (ADC) for subsequent processing. The sampling rate of the ADC must satisfy the Nyquist sampling theorem, for example, set to at least 2.5 times the IF frequency.

[0062] During signal reception, considering the path loss of the radio frequency signal during spatial propagation, the received signal strength may significantly decrease with increasing tag distance. The path loss is calculated based on the free space propagation model: Path Loss = 32.4 + 20log10(f) + 20log10(d), where f is the frequency unit in MHz and d is the distance unit in kilometers. According to this model, at a frequency of 920MHz, the signal strength decreases by approximately 2 dB for every 1 meter increase in transmission distance. Therefore, an automatic gain control circuit is installed on the receiving link to keep the received signal amplitude within a certain range, facilitating subsequent signal processing. The dynamic range of the automatic gain control is set to 60 dB, and the control response time is adjustable from 10 microseconds to 100 microseconds, with the specific value adjusted according to the tag's moving speed.

[0063] Meanwhile, due to the multipath effect, the received signal may contain multiple copies of the signal arriving via different paths. These copies can cause constructive or destructive interference at the receiver, leading to signal amplitude fluctuations. The range of multipath delay spread depends on environmental characteristics, potentially reaching 100 to 500 nanoseconds indoors and typically 50 to 200 nanoseconds outdoors. To address the multipath effect, equalization techniques are employed in the receiver design. The equalizer has 16 taps, and the tap coefficients are adaptively updated using a least mean square algorithm. The update step size is set to within the range of 0.01 to 0.001 based on the channel change rate.

[0064] The spacing between the two receiving antennas is set to be between half and one times the carrier wavelength. For example, at a frequency of 920MHz, the wavelength is approximately 0.33 meters, so the antenna spacing is set between 0.16 meters and 0.33 meters. This spacing ensures that the signals received by the two antennas have sufficient spatial correlation differences, facilitating subsequent spatial characteristic analysis. The phase consistency of each receiving channel needs to be strictly calibrated, with phase error controlled within 5 degrees and amplitude imbalance controlled within 1 dB to ensure the accuracy of subsequent signal processing.

[0065] The digital processing of the received signal employs a 12-bit analog-to-digital converter with a sampling rate of 20MHz. This parameter configuration ensures sufficient capture of signal details. During digital down-conversion, a coordinate rotation digital algorithm is used for quadrature demodulation. This algorithm calculates complex exponential multiplication iteratively, with 12 iterations, achieving a phase calculation accuracy of 0.01 degrees. The demodulated baseband signal undergoes matched filtering, with the coefficients of the matched filter consistent with the shaping filter at the transmitting end to maximize the output signal-to-noise ratio.

[0066] S2. Analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and extract the channel response from the signals received by the two antennas of the reader, as follows:

[0067] When analyzing the response signal, the phase change characteristics are first extracted using phase-locked loop (PLL) technology. The PLL employs a second-order loop structure, consisting of a phase detector, a loop filter, and a voltage-controlled oscillator (VCO). The phase detector, implemented using a multiplier, multiplies the received response signal with the local oscillator signal, outputting a phase error signal. The initial frequency of the local oscillator signal is set to the carrier frequency, for example, 920MHz. The phase error signal is smoothed by the loop filter, which uses a proportional-integral (PI) structure. Its loop bandwidth is set according to the expected Doppler shift range, for example, adjustable from 10kHz to 50kHz, with the specific value dynamically adjusted based on the tag's movement speed. The output of the loop filter controls the VCO to generate a tracking signal. The VCO's tuning sensitivity is set to 100MHz / V to ensure rapid tracking of signal phase changes. In this way, continuous signal phase change characteristics can be extracted, achieving a phase resolution of 0.1 degrees. The sampling rate is set to 100kHz, sufficient to capture phase changes caused by tag movement, thus extracting continuous signal phase change characteristics.

[0068] When calculating the bit error rate (BER) of the response signal using Cyclic Redundancy Check (CRC), the received data frames are first synchronized to locate the frame start position. CRC employs a standard polynomial, such as the CRC-16 polynomial x^16 + x^15 + x^2 + 1, with the generator polynomial having binary coefficients of 110000000000000101. During the calculation, each bit of the data frame is divided modulo-2, with the shift register initialized to all 1s. This yields a 16-bit checksum. The calculated checksum is then compared bit-by-bit with the checksum carried in the received frame, and the number of mismatched bits is counted. The BER is calculated as the ratio of the number of mismatched bits to the total number of data bits, excluding the preamble and checksum itself. For example, in a 256-bit data frame, with 240 information bits and 16 checksum bits, the BER calculation is based on the 240 information bits. To ensure statistical reliability, it is necessary to analyze multiple data frames continuously, such as 10 data frames, and take the average bit error rate as the final indicator.

[0069] When performing channel estimation on the received signals from the two antennas separately, an estimation algorithm based on training sequences is employed. The received signals from each antenna are processed separately, first extracting the preamble portion as a training sequence. The training sequence uses sequences with good autocorrelation properties, such as m-sequences or Gold sequences, with a sequence length of 64 bits. The impulse response estimate of the channel is obtained by calculating the cross-correlation function between the received training sequence and the locally stored ideal training sequence. The time-domain resolution of the channel estimation is determined by the sampling rate; for example, a 20MHz sampling rate corresponds to a 50ns time resolution. For each antenna, the estimated channel response contains amplitude and phase information for multiple paths, with a maximum of 10 paths; energy exceeding 10 paths is considered noise. The channel response estimation update frequency is set according to the channel change rate, for example, once per frame or 100 times per second.

[0070] When extracting the channel responses of the two antennas, response calibration is required to eliminate the influence of hardware differences. The calibration process employs a standard signal source method. During system initialization, a standard signal source is connected to both receiving channels, and the amplitude and phase response deviations of each channel are measured and recorded. In practice, the estimated channel responses are compensated by applying calibration coefficients. The update period for these calibration coefficients is set to 24 hours to accommodate hardware characteristic drift caused by temperature variations. The calibrated channel response contains complex form, representing the amplitude and phase information for each path. The amplitude is expressed in decibels, and the phase in degrees. The sampling interval is 50 ns, the time window length is 5 μs, and the maximum multipath delay spread is covered.

[0071] During the extraction of signal phase change features, phase unwrapping processing is also required to eliminate 2π phase ambiguity. When the phase change exceeds 180 degrees, phase transition points are detected and 360 degrees are added or subtracted to maintain phase continuity. The phase change rate is calculated using the differential method, that is, the difference between the phase values ​​of adjacent sampling points is divided by the sampling time interval, which is 10μs. The phase change feature data is low-pass filtered with a cutoff frequency set to 1kHz to suppress the influence of high-frequency noise and retain the low-frequency phase change components generated by tag movement.

[0072] The calculation of the bit error rate (BER) also needs to consider the impact of frame synchronization errors. When frame synchronization fails, that frame is not included in the BER statistics. The reliability of frame synchronization is judged by calculating the ratio of the peak to the second-highest peak value related to synchronization. The threshold for this ratio is set to 3; if it is lower than this threshold, the synchronization is considered unreliable. A counter for consecutive frame synchronization failures is also set. When the number of consecutive failures exceeds 5, a resynchronization process is triggered, and the frame start position is searched again.

[0073] Channel response extraction from both antennas requires time synchronization, employing the same local oscillator and sampling clock with clock jitter less than 1 ps. The sampling time deviation between the two channels is compensated for using digital interpolation, achieving an interpolation accuracy of 1% of the sampling interval, or 0.5 ns. This processing accurately obtains the channel responses of both antennas, providing reliable input data for subsequent spatial correlation analysis. All processing algorithms are implemented in a digital signal processor using 32-bit floating-point arithmetic to ensure computational accuracy. Various parameter thresholds during processing are derived from statistical analysis of extensive experimental data and optimized for practical application environments.

[0074] S3. When the bit error rate exceeds a preset threshold, the multipath interference level of the current environment is determined by jointly analyzing the spatial correlation between the two antenna channel responses and the difference in bit error rate distribution between the preamble and the data segment. This is implemented as follows:

[0075] When the bit error rate (BER) exceeds a preset threshold, the system initiates a multipath interference level assessment process. The preset threshold is derived from statistical analysis of experimental data. For example, in typical application environments, a BER exceeding 0.1% is considered a sign of channel quality degradation, necessitating the initiation of a multipath interference assessment. This threshold can be adjusted according to specific application scenarios. In scenarios requiring high reliability, a more stringent value, such as 0.05%, can be set, while in scenarios requiring high throughput, it can be appropriately relaxed to 0.2%. The BER calculation is based on the results obtained in the previous step using cyclic redundancy check (CRC) to ensure the reliability of the data source. Factors such as signal bandwidth, modulation scheme, and channel characteristics are considered during threshold setting, and the optimal threshold range is determined through Monte Carlo simulation.

[0076] When calculating the spatial correlation coefficient based on the channel responses of two antennas, the channel response vectors of the two antennas are first obtained. Each channel response vector contains a complex representation of multiple sampling points, with each sampling point containing amplitude and phase information. The cross-correlation coefficient is calculated using the standard correlation coefficient formula, treating the two vectors as two random variable sequences and calculating the ratio of the product of their covariance and their respective standard deviations. The cross-correlation coefficient ranges from -1 to +1, with a value closer to 1 indicating a stronger correlation. In practical calculations, since the channel response vectors may have different lengths, length alignment is required, achieved through interpolation or truncation to ensure the two vectors have the same length. The calculated cross-correlation coefficient is then compared with several preset level thresholds. These level thresholds are determined through cluster analysis of extensive experimental data; for example, a cross-correlation coefficient above 0.8 is defined as high correlation, 0.5 to 0.8 as medium correlation, and below 0.5 as low correlation. Based on the comparison results, the spatial correlation is quantified into discrete spatial interference levels, such as 3 or 5 levels, with higher level values ​​indicating more severe spatial interference. The quantization process employs either uniform or non-uniform quantization methods. Non-uniform quantization adjusts the level intervals based on the distribution characteristics of the actual measurement data.

[0077] When calculating the bit error rate (BER) of the preamble sequence and the data segment separately, it is necessary to accurately identify the boundaries of the preamble and data segment in the frame structure. The preamble sequence has a specific bit pattern, such as an alternating 10101010 sequence. Correlation detection can accurately locate the start and end positions of the preamble. The count of erroneous bits is based on bit-level comparison, comparing the received bits with the expected bits bit by bit. When calculating the absolute difference between the two BERs, the preamble BER is the ratio of the number of erroneous bits in the preamble to the total number of bits in the preamble, and the data segment BER is the ratio of the number of erroneous bits in the data segment to the total number of bits in the data segment. The absolute difference is the absolute value of the difference between these two BER values. The total BER is the ratio of the number of erroneous bits in the entire frame to the total number of bits. The relative difference in BER is calculated as the ratio of the absolute difference to the total BER. This ratio can eliminate the influence of the total BER level on the evaluation result and better reflect the difference in BER distribution characteristics between the preamble and the data segment. A sliding window mechanism was used in the statistical process, with the window size set to 8 frames. One frame was slid at a time to ensure the continuity of the statistical results.

[0078] When fusing spatial interference levels and relative differences in bit error rate (BER) using multi-dimensional features, a two-dimensional decision matrix needs to be established. The rows of the decision matrix correspond to spatial interference levels, and the columns correspond to the ranges of relative BER differences. Each cell stores a multipath interference level determination result. The division of the relative BER difference range is based on statistical distribution characteristics; for example, 0-0.1 is defined as a low difference range, 0.1-0.3 as a medium difference range, and above 0.3 as a high difference range. The multipath interference level determination rules are based on the analysis of a large amount of experimental data. By collecting data under different environmental conditions, the relationship between the combination of spatial interference levels and relative BER differences and the actual degree of multipath interference is observed, and mapping rules are established. For example, when the spatial interference level is high and the relative BER difference is large, it is determined to be severe multipath interference. This is because a high spatial interference level indicates weak spatial correlation, and a large relative BER difference indicates significant channel frequency selectivity, both typical characteristics of severe multipath interference. The dimensions of the decision matrix are determined according to actual needs. For example, a 3×3 or 5×5 matrix can be used. The larger the matrix size, the higher the accuracy of the decision, but the higher the computational complexity.

[0079] In practical applications, the construction of the decision matrix needs to consider environmental adaptability. By setting multiple decision matrix templates, different judgment rules are adopted for different types of application environments, such as indoor, outdoor, and metallic environments. The system automatically selects the appropriate decision matrix template based on the preliminary environment identification results. Environment identification is based on signal feature analysis, such as average multipath delay spread and signal strength fluctuation characteristics. The update and maintenance of the decision matrix are achieved through an online learning mechanism. The system continuously monitors the relationship between the judgment results and the actual communication quality. When a significant deviation is found between the judgment results and the actual situation, the judgment rules in the decision matrix are automatically adjusted. During the adjustment process, a gradient descent algorithm is used, with communication quality indicators as the optimization objective, to gradually adjust the decision rules.

[0080] The determination of multipath interference levels also needs to consider stability over time. By setting a time window, such as a 1-second window, the relative differences between the spatial interference level and the bit error rate are calculated multiple times within this window. The weighted average of these multiple calculations is then used as the final input value. The weighting coefficients are set according to the freshness of the measurement time, with more recent measurements given greater weight. A state-holding mechanism is also implemented. When a multipath interference level changes abruptly, the same result must be obtained for several consecutive calculation cycles before the level change is confirmed, avoiding accidental misjudgments. For example, an increase in the level must be shown for three consecutive calculation cycles to confirm a genuine increase in multipath interference level. The parameters of the state-holding mechanism are dynamically adjusted according to the rate of environmental change, reducing the required number of confirmations in rapidly changing environments and increasing the required number of confirmations in stable environments.

[0081] The entire multipath interference level assessment process is implemented using a pipelined architecture, with each processing stage executing in parallel to ensure real-time assessment. The assessment cycle is synchronized with the data frame reception cycle, performing an assessment after each complete data frame is received. The assessment result outputs a discrete multipath interference level, along with a confidence index calculated based on the quality and quantity of data used in the assessment. All calculations use 32-bit floating-point precision to ensure accuracy. Parameter thresholds and decision rules are stored in non-volatile memory, supporting online updates and debugging. Using this method, the multipath interference level of the current environment can be accurately and reliably determined, providing an important basis for subsequent modulation and coding scheme selection.

[0082] S4. Geometric feature extraction is performed on the signal phase change characteristics. By analyzing the curvature characteristics of the phase change trajectory in the complex plane, it is determined whether there is a continuous unidirectional phase drift. This is implemented as follows:

[0083] When extracting geometric features from signal phase change characteristics, the signal phase change characteristics at multiple consecutive time points are first mapped to a sequence of coordinate points on the complex plane. The signal phase change characteristics, extracted in the previous step using phase-locked loop (PLL) technology, include phase angle and amplitude information. During the mapping process, a polar coordinate to Cartesian coordinate conversion method is used. The phase angle θ at each time point is taken as the polar angle, and the signal amplitude r as the polar radius. The corresponding Cartesian coordinate points are obtained using the formulas x = r × cosθ and y = r × sinθ, where x and y represent the abscissa and ordinate, respectively. The number of coordinate points is set according to the estimated motion speed; for example, 32 points are used when the tag moves quickly, and 64 points are used when the movement speed is slow, to ensure the integrity of the trajectory features. The coordinate point sequence is connected in chronological order to form a phase trajectory, with adjacent points connected by straight lines to form a continuous trajectory line. The trajectory sampling interval is set according to the signal rate; for example, at a 920MHz carrier frequency, the sampling interval is set to 10μs to ensure that phase changes caused by motion can be captured.

[0084] When calculating the curvature values ​​at each point on the phase trajectory, a curvature estimation algorithm based on discrete points is used. For each point Pi on the trajectory, where i represents the point number, five points are selected as the calculation window: two adjacent points before and after Pi, i.e., Pi-2, Pi-1, Pi, Pi+1, and Pi+2. First, the chord length between adjacent points is calculated, and then the change in angle between adjacent chords is calculated. The curvature value k is calculated using the formula k=Δα / Δs, where Δα is the change in angle between adjacent chords, and Δs is the chord length. During the calculation, a cubic spline interpolation method is used to smooth the trajectory, and the smoothing coefficient λ of the spline function is set to 0.5 to reduce calculation errors caused by noise. After the curvature value of each point is calculated, the curvature distribution characteristics of the entire trajectory are statistically analyzed, including the curvature mean, curvature variance, maximum curvature, and minimum curvature values. The statistical analysis of the curvature distribution characteristics is based on a sliding window, with the window size set to one-quarter of the number of trajectory points. For example, when the number of trajectory points is 64, the window size is 16 points, sliding one point at a time to ensure the continuity of the statistical results.

[0085] When the curvature distribution characteristics show that the curvature value is consistently below the motion determination threshold and the phase change direction is consistent, a persistent unidirectional phase drift is determined to exist. The motion determination threshold is determined through experimental data analysis. A large number of trajectory curvatures are measured in a static environment, collecting at least 1000 sets of curvature data. Their statistical distribution characteristics are calculated, and the 95th percentile is used as the initial threshold, for example, 0.05m⁻¹. This threshold is dynamically adjusted according to the environment. A stricter threshold is used when the signal quality is good, and the threshold requirement is appropriately relaxed when the signal quality is poor. The adjustment range is based on the signal-to-noise ratio (SNR) index; for every 3dB decrease in SNR, the threshold is relaxed by 5%. The consistency of the phase change direction is determined by calculating the sign consistency of the phase angle difference between adjacent points. The phase angle difference between 10 consecutive points is calculated, and the direction is considered consistent when at least 8 points have the same sign. A double confirmation mechanism is used in the determination process. First, it is checked whether the curvature value is consistently below the threshold, requiring the curvature values ​​of 20 consecutive points to be below the threshold. Then, it is verified whether the phase change direction is consistent. Only when both conditions are met is a persistent unidirectional phase drift determined to exist.

[0086] The entire geometric feature extraction process is implemented using a digital signal processor with 32-bit floating-point precision. During trajectory point coordinate calculation, normalization is performed to standardize the amplitude values ​​to the 0-1 range, avoiding the impact of amplitude variations on curvature calculation. Maximum-minimum value normalization is used. An outlier handling mechanism is implemented during curvature calculation. When an abnormal change in curvature value is detected, such as a change in curvature exceeding 10 times between adjacent points, neighboring point interpolation is used as a replacement. Linear interpolation is employed, taking the average curvature of the two preceding and following points as the replacement value. For phase change direction determination, a minimum number of consecutive points is required; at least eight consecutive points must maintain the same direction of change to be considered consistent, avoiding misjudgments due to random errors. All calculation parameters and thresholds are stored in non-volatile memory, supporting online calibration and updates. The reasonableness of the calculation results is monitored in real time during processing. When an anomaly is detected, a recalculation process is automatically triggered to ensure system stability and reliability.

[0087] S5. If there is a continuous unidirectional phase drift, the relative velocity estimate is calculated based on the phase drift direction and rate, as follows:

[0088] If a continuous unidirectional phase drift exists, the relative motion velocity estimate is calculated based on the phase drift direction and rate. When determining the radial direction of relative motion based on the phase drift direction, the monotonicity characteristics of the phase change are first analyzed. The phase change characteristics come from the signal phase change feature sequence extracted through geometric features in the previous step. When the phase value monotonically increases with time, it is determined that the relative motion direction is approaching the reader; when the phase value monotonically decreases with time, it is determined that the relative motion direction is moving away from the reader. Direction determination is based on the phase change trend of multiple consecutive sampling points. For example, 20 consecutive sampling points need to maintain the same monotonicity to confirm the motion direction. The motion direction determination result is accompanied by a confidence index. The confidence level is calculated based on the consistency of monotonicity; the higher the consistency, the higher the confidence level. To eliminate the judgment error caused by phase winding, phase dewinding processing is performed before direction determination. When the absolute value of the phase difference between adjacent sampling points exceeds 300 degrees, the phase continuity is maintained by adding or subtracting an integer multiple of 360 degrees.

[0089] When calculating the Doppler frequency shift based on the phase change rate, the phase difference Δθ between adjacent sampling points is first calculated, and then divided by the sampling time interval Δt to obtain the instantaneous angular frequency change ω = Δθ / Δt. The Doppler frequency shift fd is calculated using the formula fd = ω / (2π). A moving average filter is used during the calculation, with a window size of 10 sampling points to suppress noise. The Doppler frequency shift is calculated based on data from multiple consecutive sampling points; for example, the average phase change rate of 100 consecutive sampling points is taken as the final estimated Doppler frequency shift. To ensure accuracy, outliers are eliminated. When the phase change rate of a sampling point differs from that of its adjacent points by more than three standard deviations, that point is considered an outlier and replaced with linear interpolation. The update frequency of the Doppler frequency shift is consistent with the sampling rate; for example, at a sampling rate of 100 kHz, the estimated Doppler frequency shift is updated every 10 ms.

[0090] When converting the Doppler frequency shift into a relative velocity estimate using the Doppler frequency shift calculation formula, the formula v = (fd × c) / fc is used, where v represents the relative velocity estimate. The speed of light constant c is taken as 299,792,458 meters per second, and the carrier frequency parameter fc uses the actual transmission frequency used by the reader, for example, 920 MHz. Consistency of dimensions must be ensured during the calculation: the unit of the Doppler frequency shift fd is Hertz, the unit of the carrier frequency parameter fc is Hertz, and the unit of the calculated relative velocity estimate v is meters per second. The accuracy of the velocity estimate calculation is guaranteed by 32-bit floating-point arithmetic. Overflow and outlier checks are performed during the calculation process. When the calculation result exceeds a reasonable range, for example, exceeding 100 meters per second, the previous valid estimate is used. To further improve the estimation accuracy, Kalman filtering is used to smooth multiple consecutive velocity estimates. The state variables are set as velocity and acceleration. The observation noise covariance matrix R is dynamically adjusted according to the measurement environment, and the process noise covariance matrix Q is adjusted according to the rate of change of the motion state. The final output of the relative velocity estimate includes a timestamp and a confidence index. The timestamp is used for subsequent data synchronization processing, and the confidence index is calculated based on the data quality and computational consistency used in the estimation process. All calculation parameters and constants are stored in non-volatile memory, supporting online calibration and updates to ensure the system's adaptability in different environments. Using this method, the relative velocity estimate can be calculated accurately and reliably, providing an important basis for subsequent modulation and coding scheme selection.

[0091] If there is no persistent unidirectional phase drift, the current first modulation and coding scheme is maintained.

[0092] S6. Based on the relative motion speed estimate and multipath interference level, select the second modulation and coding scheme that matches the current motion speed and channel environment to reread the data, as follows:

[0093] Based on the relative motion speed estimate and multipath interference level, a second modulation and coding scheme matching the current motion speed and channel environment is selected for data re-reading. When establishing a modulation and coding configuration mapping table containing different combinations of relative motion speed ranges and multipath interference levels, the method for dividing the relative motion speed ranges is first determined. The relative motion speed estimate comes from the result calculated using Doppler frequency shift in the previous step. The speed range division is based on statistical analysis of experimental data. For example, by testing communication performance under different speed conditions, the speed range is divided into four intervals: 0–0.5 m / s is the static interval, 0.5–2 m / s is the low-speed interval, 2–5 m / s is the medium-speed interval, and above 5 m / s is the high-speed interval. The multipath interference level comes from the result obtained in the previous step through joint analysis of spatial correlation and bit error rate distribution differences, and is divided into three levels: low interference level, medium interference level, and high interference level. The modulation and coding configuration mapping table adopts a two-dimensional matrix structure, with rows corresponding to the four speed ranges and columns corresponding to the three interference levels, for a total of 12 cells. Each cell stores one modulation and coding configuration scheme.

[0094] The modulation and coding scheme configuration includes three main parameters: modulation scheme, coding rate, and preamble length. The modulation scheme offers three options: QPSK, 16QAM, and 64QAM; the coding rate offers three options: 1 / 2, 2 / 3, and 3 / 4; and the preamble length offers three options: 16 bits, 32 bits, and 64 bits. The specific combinations of these parameters were determined through extensive experimental testing. During testing, the bit error rate and throughput performance of various parameter combinations were measured under different speeds and interference conditions. The parameter combination with a bit error rate below 10^-4 and the highest throughput was selected as the configuration scheme for that cell. Each configuration scheme also includes other auxiliary parameters, such as transmit power adjustment values ​​and equalizer parameters, which were also determined based on experimental test results.

[0095] When querying the modulation and coding configuration mapping table based on the combination of the current relative motion speed estimate and the current multipath interference level, the speed range to which the current relative motion speed estimate belongs is first determined. Speed ​​range matching uses a range boundary judgment method: when the speed estimate is greater than or equal to the lower limit of the range and less than the upper limit, it is determined to belong to that range. For boundary cases, such as when the speed estimate is exactly 2 meters per second, the configuration schemes of adjacent ranges are also considered. The final configuration is obtained by calculating the weighted average of the two configurations, with the weights determined based on the distance from the range center. The current multipath interference level directly uses the evaluation result from the previous step; if an intermediate level is encountered, the final level is determined using a rounding method.

[0096] Multiple verification mechanisms are implemented during the query process. First, the validity of the speed estimate is checked. If the speed estimate exceeds a reasonable range, such as greater than 100 meters per second, the default configuration is used. Second, the validity of the multipath interference level is checked. If the level value exceeds the range of 1-3, a medium-level configuration is used. The query results are also compared with historical configurations. If three consecutive query results are inconsistent, an expert diagnostic mode is activated. By analyzing speed change trends and interference level change patterns, the most stable configuration is selected. All query operations are logged, including query time, input parameters, and output results, for subsequent performance analysis and optimization.

[0097] When selecting the corresponding modulation and coding scheme from the mapping table as the second modulation and coding scheme for re-reading data, the various parameters in the configuration scheme are first parsed. The modulation scheme parameter is implemented by setting the reader's modulation register: QPSK corresponds to register value 0, 16QAM to register value 1, and 64QAM to register value 2. The coding rate parameter is implemented by setting the coding control register: 1 / 2 code rate corresponds to value 0, 2 / 3 code rate corresponds to value 1, and 3 / 4 code rate corresponds to value 2. The preamble length parameter is implemented by setting the frame structure register: 16 bits corresponds to value 0, 32 bits to value 1, and 64 bits to value 2. Other auxiliary parameters are also implemented by setting the corresponding registers.

[0098] After parameter configuration, the reader reinitializes the transceiver link. The initialization process includes resetting the baseband processor, reconfiguring the frequency synthesizer, and updating the automatic gain control parameters. A query command is sent to the electronic tag using a new modulation and coding scheme, with the transmission power set according to the power adjustment parameters in the configuration scheme. During the re-data reading process, communication quality indicators are continuously monitored, including bit error rate, signal strength, and signal-to-noise ratio. If the bit error rate still exceeds 10^-3 after three consecutive reading attempts, a reconfiguration process is triggered, and a new modulation and coding scheme is selected based on the latest movement speed and interference level.

[0099] The entire configuration selection process employs an adaptive control mechanism, dynamically adjusting the modulation and coding scheme configuration by monitoring environmental changes and communication performance in real time. The system updates speed estimates and interference levels every 100 milliseconds and evaluates the configuration effect every 500 milliseconds, triggering reconfiguration immediately upon detecting performance degradation. All configuration parameters and mapping tables are stored in EEPROM, supporting online updates and debugging via serial port. A read-before-write verification mechanism is used during configuration updates to ensure data correctness, and CRC checks guarantee data integrity. The system also features a default configuration set, automatically activating the default configuration when the mapping table is corrupted or lost, ensuring basic communication functionality. These methods ensure the selection of the optimal modulation and coding scheme under varying motion speeds and interference conditions, achieving reliable data reading.

[0100] Example 2: Figure 2 A schematic diagram of a data reading system based on an RFID reader is provided according to the present invention. The data reading system based on an RFID reader includes:

[0101] The signal transceiver module is used by the reader to send query commands to the electronic tag in the first modulation and coding scheme and to receive response signals.

[0102] The signal analysis module is used to analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and to extract the channel response from the signals received by the two antennas of the reader.

[0103] The interference analysis module is used to determine the multipath interference level of the current environment by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment when the bit error rate index exceeds a preset threshold.

[0104] The feature extraction module is used to extract geometric features of signal phase change features. It analyzes the trajectory curvature features of phase change in the complex plane to determine whether there is a continuous unidirectional phase drift.

[0105] The velocity estimation module is used to calculate the relative motion velocity estimate based on the phase drift direction and rate if there is a continuous unidirectional phase drift.

[0106] The reread control module is used to select a second modulation and coding scheme that matches the current motion speed and channel environment to reread the data based on the relative motion speed estimate and multipath interference level.

[0107] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0108] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0109] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. Computer-readable storage media can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0112] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0114] If a function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0116] In conclusion, the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data reading method based on an RFID reader, characterized in that, include: S1. The reader sends a query command to the electronic tag using the first modulation and coding method and receives a response signal; S2. Analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and extract the channel response from the signals received by the two antennas of the reader respectively; S3. When the bit error rate exceeds a preset threshold, the multipath interference level of the current environment is determined by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment, including: When the bit error rate exceeds the corresponding preset threshold, the spatial correlation coefficient is calculated based on the response of the two antenna channels and converted into the spatial interference level. Calculate the bit error rate of the preamble sequence and the data segment separately, and then calculate the relative difference value. Multi-dimensional feature fusion of spatial interference level and relative difference in bit error rate: A two-dimensional decision matrix of spatial interference level and relative difference in bit error rate is established. Multipath interference level determination rules are preset according to different level combinations. The final multipath interference level is determined according to the position of the current spatial interference level and relative difference in bit error rate in the two-dimensional decision matrix. S4. Geometric feature extraction is performed on the signal phase change characteristics. The curvature characteristics of the phase change trajectory on the complex plane are analyzed to determine whether there is a continuous unidirectional phase drift. S5. If there is a continuous unidirectional phase drift, calculate the relative motion velocity estimate based on the phase drift direction and rate. S6. Based on the relative motion speed estimate and multipath interference level, select the second modulation and coding scheme that matches the current motion speed and channel environment to reread the data.

2. The data reading method based on an RFID reader according to claim 1, characterized in that, The first modulation and coding scheme is a high-order modulation and coding scheme; Sending query commands includes sending query commands to electronic tags using quadrature phase shift keying modulation or quadrature amplitude modulation. The received response signal includes receiving the modulated signal reflected back from the electronic tag through the reader's receiving antenna.

3. The data reading method based on an RFID reader according to claim 1, characterized in that, The analysis of the response signal includes: extracting the signal phase change features from the response signal using phase-locked loop technology; using a phase detector to compare the phase of the response signal with the local oscillator signal; smoothing the phase error signal through a loop filter; and controlling the voltage-controlled oscillator to output a synchronization signal that tracks the phase of the signal, thereby extracting the continuous signal phase change features. The bit error rate (BER) of the response signal is calculated using a cyclic redundancy check (CRC) method: polynomial division is performed on the data frames in the response signal to generate a check code. The generated check code is compared bit by bit with the received check code, and the ratio of the number of mismatched bits to the total number of bits is used as the BER. Channel estimation is performed on the received signals from the two antennas respectively, and the channel responses of the two antennas are extracted.

4. The data reading method based on an RFID reader according to claim 1, characterized in that, Calculating the spatial correlation coefficient based on the channel responses of two antennas and converting it into a spatial interference level includes: calculating the cross-correlation coefficient of the two antenna channel response vectors, comparing the cross-correlation coefficient with multiple preset level thresholds, and quantifying the spatial correlation into a discrete spatial interference level based on the comparison results.

5. The data reading method based on an RFID reader according to claim 1, characterized in that, The calculation of the relative difference between the bit error rates of the preamble sequence and the data segment includes: separately counting the number of erroneous bits in the preamble sequence and the number of erroneous bits in the data segment, calculating the absolute difference between their bit error rates, and using the ratio of the absolute difference to the total bit error rate as the relative difference in bit error rates.

6. The data reading method based on an RFID reader according to claim 1, characterized in that, Geometric feature extraction is performed on the signal phase change characteristics. The curvature characteristics of the phase change trajectory in the complex plane are analyzed to determine whether a persistent unidirectional phase drift exists, including: The phase change characteristics of a signal at multiple consecutive moments are mapped to a sequence of coordinate points on the complex plane to form a phase trajectory. Calculate the curvature values ​​at each point on the phase trajectory and statistically analyze the curvature distribution characteristics; When the curvature distribution characteristics show that the curvature value is consistently below the motion determination threshold and the phase change direction is consistent, it is determined that there is a continuous unidirectional phase drift.

7. The data reading method based on an RFID reader according to claim 1, characterized in that, If a continuous unidirectional phase drift exists, the estimated relative velocity is calculated based on the phase drift direction and rate, including: The radial direction of relative motion is determined based on the phase drift direction; Calculate the Doppler frequency shift based on the phase change rate; The Doppler frequency shift is converted into an estimate of relative motion velocity using the Doppler frequency shift calculation formula, which includes the carrier frequency parameter and the speed of light constant.

8. The data reading method based on an RFID reader according to claim 1, characterized in that, Based on the relative motion velocity estimate and multipath interference level, a second modulation and coding scheme matching the current motion velocity and channel environment is selected for data re-reading, including: Establish a modulation and coding configuration mapping table that includes combinations of different relative motion speed ranges and multipath interference levels; Query the modulation and coding configuration mapping table based on the combination of the current relative motion speed estimate to its speed range and the current multipath interference level; Select the corresponding modulation and coding configuration in the mapping table as the second modulation and coding method to reread the data.

9. A data reading system based on an RFID reader / writer, used to implement the data reading method based on an RFID reader / writer as described in any one of claims 1-8, characterized in that, include: The signal transceiver module is used by the reader to send query commands to the electronic tag in the first modulation and coding scheme and to receive response signals. The signal analysis module is used to analyze the response signal to obtain the signal phase change characteristics and bit error rate index, and to extract the channel response from the signals received by the two antennas of the reader. The interference analysis module is used to determine the multipath interference level of the current environment by jointly analyzing the spatial correlation between the responses of the two antenna channels and the difference in bit error rate distribution between the preamble and the data segment when the bit error rate index exceeds a preset threshold. The feature extraction module is used to extract geometric features of signal phase change features. It analyzes the trajectory curvature features of phase change in the complex plane to determine whether there is a continuous unidirectional phase drift. The velocity estimation module is used to calculate the relative motion velocity estimate based on the phase drift direction and rate if there is a continuous unidirectional phase drift. The reread control module is used to select a second modulation and coding scheme that matches the current motion speed and channel environment to reread the data based on the relative motion speed estimate and multipath interference level.

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