RFID static ranging method

Abstract

The invention discloses an RFID (Radio Frequency Identification Device) static ranging method, which comprises the following steps of: 1, introducing an OFDM (Orthogonal Frequency Division Multiplexing) communication mechanism on the basis of an existing RFID communication protocol to realize concurrent transmission and receiving of multi-frequency signals, and further acquiring multi-frequency phase information; 2, correcting the acquired multi-frequency phase information, eliminating a phase error introduced by hardware, and calculating a frequency-phase gradient based on the corrected multi-frequency phase; and step 3, constructing two types of distance evaluation models based on frequency-phase gradient and multipath characteristics, selecting a model adaptive to the current environment in combination with the distribution complexity of the frequency-phase gradient, and accurately estimating the distance between the RFID reader and the tag. According to the method, two types of distance evaluation models based on frequency-phase gradient and multipath characteristics are constructed, and the multipath condition of the environment where the tag is located is evaluated by combining the distribution complexity of the frequency-phase gradient, so that the adaptive distance evaluation model is selected, and high-precision RFID distance measurement is realized.

Description

Technical Field

[0001] The present invention relates to an RFID static distance measurement method, in particular to an RFID static distance measurement method. Background Art

[0002] Radio Frequency Identification (RFID) is a core technology in the IoT's perception layer. Compared to traditional sensing media, RFID boasts distinct advantages such as small size, low cost, passive sensing (no power required), non-line-of-sight communication, and batch reading capabilities, making it the most widely used technology in IoT systems. With the continuous development of this technology and its in-depth application across various industries, large-scale RFID systems are becoming increasingly popular. Against this backdrop, RFID ranging, as one of the core technologies in the IoT's perception layer, is becoming increasingly important. By accurately estimating the distance between the reader and the tag, RFID ranging provides fundamental data support for intelligent management, automated control, and precise positioning within the IoT. Its applications span a wide range of fields, including warehousing and logistics, industrial manufacturing, smart healthcare, and intelligent transportation, demonstrating significant scientific value and broad application prospects.

[0003] However, existing RFID ranging methods (such as those based on signal strength, phase difference, or time of flight) face problems such as phase ambiguity, low sampling rate, and hardware dependence in static environments (fixed reader deployment), which significantly restrict the accuracy and robustness of the system. Specifically, 1) Phase ambiguity: The phase of the carrier signal exhibits periodic repetition as the signal propagates over distance, making it unable to accurately reflect the true distance, thus affecting ranging accuracy; 2) Low sampling rate: Traditional RFID systems have low communication efficiency due to limited bandwidth, and are prone to phase information loss or inaccuracy in dense tag ranging scenarios, thereby weakening the real-time and reliability of ranging; 3) Hardware dependence: Most ranging methods rely on complex modifications to the RFID hardware system, which not only significantly increases the deployment cost and complexity of the system, but may also cause compatibility issues with existing systems; 4) In environments such as warehouses, RFID distance detection is difficult in the presence of metal objects and metal shelves. Summary of the Invention

[0004] Purpose of the invention: The technical problem to be solved by the present invention is to provide an RFID static ranging method in view of the shortcomings of the existing technology.

[0005] In order to solve the above technical problems, the present invention discloses an RFID static ranging method, comprising the following steps:

[0006] Step 1: Based on the existing RFID communication protocol, the OFDM communication mechanism is introduced to realize the concurrent transmission and reception of multi-frequency signals, thereby collecting multi-frequency phase information;

[0007] Step 2: Correct the collected multi-frequency phase information to eliminate the phase error introduced by the hardware, and calculate the frequency-phase gradient based on the corrected multi-frequency phase;

[0008] Step 3: Construct two types of distance evaluation models based on frequency-phase gradient and multipath characteristics. Combined with the distribution complexity of frequency-phase gradient, select the model that adapts to the current environment to accurately estimate the distance between RFID reader and tag.

[0009] The method for concurrently acquiring multi-frequency phases using the OFDM mechanism described in step 1 includes:

[0010] Step 1-1, constructing a corresponding OFDM symbol X(f) according to OFDM symbol parameter information and RFID communication protocol parameter configuration;

[0011] Step 1-2: Use OFDM symbol X(f) to replace the high-level carrier in the tag response EPC phase and send it to the tag;

[0012] Step 1-3: extract the OFDM symbol Y(f) from the tag reflected signal, compare the frequency domain representations X(f) and Y(f) of the transmitted and received OFDM symbols, and obtain the multi-frequency phase information.

[0013] The frequency phase gradient calculation method in step 2 includes:

[0014] Step 2-1-1: Attach the RFID tag to the surface of the reader antenna and measure the phase of the received signal to obtain the phase deviation introduced by the hardware.

[0015] Step 2-1-2, subtracting the phase deviation from the multi-frequency phase collected in step 1 to obtain a corrected multi-frequency phase;

[0016] Step 2-1-3, calculate the phase gradient between adjacent frequencies based on the corrected multi-frequency phase. The frequency phase gradient calculation formula is:

[0017]

[0018] in, represents the phase gradient of the ith frequency, f i represents the frequency of the i-th channel, θ(f i ) indicates that the channel frequency is f i The phase of time;

[0019] In step 2-1-4, assuming that the OFDM symbol contains n subchannels, calculate the frequency-phase gradient vector containing n-1 dimensions according to the frequency-phase gradient calculation formula defined in step 2-2-1

[0020] The method for performing RFID ranging based on frequency-phase gradient distribution complexity in step 3 includes:

[0021] Step 3-1, constructing a distance assessment model based on frequency-phase gradient and a distance assessment model based on multipath propagation characteristics;

[0022] Step 3-2, calculate the distribution complexity of the frequency-phase gradient, and select a distance evaluation model that is suitable for the current deployment environment based on the distribution complexity, so as to achieve accurate estimation of the distance between the RFID reader and the tag.

[0023] The OFDM symbol construction method described in step 1-1 includes:

[0024] Step 1-1-1, set the bandwidth and number of subcarriers of OFDM symbols, and assign subchannel parameters;

[0025] Step 1-1-2, set the OFDM symbol length according to the tag state switching period, and define the tag state switching period as T switch , set the OFDM symbol length T ofdm Set to half of the label state switching cycle, that is, Ensure that a complete OFDM symbol is included in any tag state period;

[0026] Step 1-1-3, add a cyclic prefix to the OFDM symbol, copy the tail data of the OFDM symbol and place it at the beginning of the symbol to form the final OFDM symbol for transmission.

[0027] The multi-frequency phase extraction method described in steps 1-3 includes:

[0028] Step 1-3-1, perform moving average filtering on the signal received by the RFID reader, and perform correlation matching with the tag response preamble to detect the starting position of the tag response packet;

[0029] Step 1-3-2: Based on the cyclic prefix characteristics of the OFDM symbol, two sliding windows are defined. One window is used to cover the cyclic prefix part of the OFDM symbol, and the other window is used to cover the tail part of the OFDM symbol. By calculating the correlation between the two sliding windows, the starting position of the OFDM symbol is determined and the complete OFDM symbol is extracted.

[0030] Step 1-3-3: perform differential processing on the OFDM symbols under different reflection states to eliminate environmental interference, and perform Fourier transform on the differential symbols and the OFDM symbols sent by the reader to obtain their frequency domain complex representations X(f) and Y(f);

[0031] Steps 1-3-4, calculate the frequency domain complex difference Get the multi-frequency phase set Here, Real(·) represents the real part of a complex number, and Imag(·) represents the imaginary part of a complex number.

[0032] The construction of the frequency-phase gradient-based distance estimation model described in step 3-1 includes:

[0033] Step 3-1-1-1: construct a distance evaluation model based on frequency-phase gradient, which satisfies:

[0034]

[0035] in, represents the frequency phase gradient, d represents the distance between the reader and the tag, and c represents the propagation speed of the signal;

[0036] Step 3-1-1-2, average the frequency-phase gradient phase vector obtained in step 2-1-4 to obtain The frequency-phase gradient mean The distance between the reader and the tag is obtained by bringing it into the frequency-phase gradient based distance evaluation model.

[0037] The distance assessment model based on multipath propagation characteristics described in step 3-1 is specifically constructed as follows:

[0038] Step 3-1-2-1, construct a distance assessment model based on multipath characteristics, the multipath channel distance assessment model parameterizes two main unknown quantities: the length of each multipath path d i (where d0 represents the line-of-sight (LOS) path distance) and the tag's reflection coefficient μ, while the remaining minor parameters are assigned empirically determined constant values. On this basis, a set of observation equations are established through phase measurement at multiple frequencies. Each equation reflects the coherent superposition effect of signals from different paths at the corresponding frequency. Assume that the downlink signal emitted by the RFID reader can be expressed as:

[0039] S R (t) = Ae j2πft ,

[0040] Where A represents the amplitude of the signal sent by the reader, f represents the frequency of the signal, j represents the imaginary unit, and t is the time variable, which is used to calculate the value of the signal at a certain moment. Considering the impact factor M on the signal caused by the i-th non-line-of-sight path (NLoS) i , including amplitude attenuation With the phase change 2πfτ i , which is expressed as:

[0041]

[0042] Among them, the amplitude attenuation It approximately satisfies the inverse square law of free space path loss and is affected by frequency, propagation distance, and the reflection coefficient r of the reflector. i To simplify the expression, let where r i is the reflection coefficient of the reflector corresponding to the i-th path, and for the LOS path, r i =1; propagation delay where c is the signal propagation speed; hence, the composite effect of all downlink paths on the signal is:

[0043]

[0044] Downlink signal S R (t) becomes S after reaching the label TR (t):

[0045] S TR (t) = S R (t)·M

[0046] Considering the reflective characteristics of the tag and the symmetrical uplink channel, the signal received by the reader is:

[0047] S TR (t) = μ·S R (t)·M 2

[0048] Step 3-1-2-2, the reader receives the S TR After IQ demodulation of the (t) signal, the total phase θ(f) including the downlink, reflection, and uplink channel effects is obtained. This phase can be formalized as a function g:

[0049] θ(f)=g(f,μ,d0,d1,…,d n )

[0050] Where f represents the signal frequency, μ represents the tag reflection coefficient, and d i Indicates the propagation distance of the signal under different paths, n represents the total number of paths; based on multi-frequency phase measurement values Then the following equations are established:

[0051]

[0052] Step 3-1-2-3, by numerically solving the above equations, the propagation distance of each path is analyzed, that is, the actual distance between the tag and the reader is calculated.

[0053] The distance model selection strategy based on the frequency-phase gradient distribution complexity described in step 3-2 includes:

[0054] Step 3-2-1, frequency-phase gradient vector obtained according to step 2-1-4 The distribution complexity of the frequency-phase gradient is calculated. The distribution complexity of the phase gradient is:

[0055]

[0056] in, represents the normalized phase gradient, represents the mean of the normalized phase gradient;

[0057] Step 3-2-2: Select an appropriate distance evaluation model based on the comparison of the distribution complexity (MCE) with a preset threshold (δ). 10. The RFID static ranging method according to claim 9, wherein step 3-2-2 specifically comprises: if MCE is greater than δ, the tag is judged to be in a multipath-intensive scenario, and a distance evaluation model based on a multipath model is selected to improve ranging accuracy; if MCE is less than or equal to δ, the tag is judged to be in a multipath-sparse scenario, and a model based on a frequency-phase gradient is selected to improve ranging real-time performance.

[0058] Beneficial effects:

[0059] This paper proposes an RFID static ranging method. This method uses concurrent phase acquisition and frequency-phase compensation mechanisms to construct two distance estimation models based on frequency-phase gradient and multipath characteristics. This method, combined with the distribution complexity of the frequency-phase gradient, assesses the multipath characteristics of the tag's environment, thereby selecting an appropriate distance estimation model and achieving high-precision RFID distance measurement. This method not only achieves high ranging accuracy and time efficiency, but is also compatible with standard RFID tags, enabling direct deployment in commercial RFID systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a flow chart of an RFID static ranging method provided by the present invention.

[0061] Figure 2 The present invention provides a flowchart of a method for concurrently acquiring multi-frequency phases based on an OFDM communication mechanism.

[0062] Figure 3 The present invention provides a flow chart for calculating the frequency phase gradient.

[0063] Figure 4 This is a flow chart of distance measurement based on the distance estimation model provided by the present invention.

[0064] Figure 5This is a schematic diagram of the ranging accuracy comparison experiment results provided by the present invention.

[0065] Figure 6 This is a schematic diagram of the time efficiency comparison experimental results provided by the present invention. DETAILED DESCRIPTION

[0066] The method of the present invention can not only achieve high-precision ranging while ensuring time efficiency, but also is compatible with standard RFID tags and can be directly deployed in commercial RFID systems.

[0067] An OFDM symbol refers to a composite waveform formed by parallel transmission of multiple modulated (such as QAM) subcarriers within one symbol period.

[0068] The RFID ranging problem, that is, evaluating the distance between the reader or antenna and the tag based on the physical layer characteristics of the tag's reflected signal, mainly solves three problems: 1) How to simplify the system deployment to meet the requirements of most scenarios, that is, to improve versatility; 2) How to complete the evaluation of the distance between the tag and the reader in a shorter time, that is, to improve time efficiency; 3) How to achieve high-precision RFID ranging without modifying the RFID tag hardware, that is, to improve compatibility. Specifically, given a set of tags in any environment, How to maintain the original deployment as much as possible and complete the Evaluation of label distances.

[0069] An RFID static ranging method is proposed. Its basic idea is to introduce an orthogonal frequency division multiplexing communication mechanism based on the RFID communication protocol, concurrently obtain multi-frequency phase information, and construct two types of distance evaluation models based on frequency-phase gradient and multipath characteristics. In addition, the multipath situation of the tag environment is evaluated by combining the distribution complexity of the frequency-phase gradient. The adaptive distance evaluation model is then selected to achieve high-precision RFID distance measurement.

[0070] Example:

[0071] This method uses static antenna deployment to measure the distance of static RFID tags, independent of antenna or tag movement, providing a universal distance assessment method for static IoT scenarios. In smart warehouses, multiple RFID antennas are deployed at different locations on the ceiling or walls for real-time inventory and monitoring of goods. Each item is attached with an RFID tag. Because the goods and antennas remain nearly stationary, distance detection algorithms that rely on antenna or tag movement will fail. Furthermore, the metal shelving used in warehouses can cause severe multipath effects—RFID signals are easily blocked or reflected by the metal, severely impacting signal quality and rendering distance detection algorithms based on the sparse multipath assumption ineffective. This method constructs a frequency-phase gradient-based distance estimation model to address ranging in static scenarios and proposes a multipath-based distance estimation model to address ranging in scenarios with multipath interference. This method can quickly and accurately calculate the distance of a static tag. Combining the distance information between the tag and multiple antennas, a triangulation algorithm is used to accurately locate each item in real time. This method can promptly detect misplaced goods, out-of-stock items, or abnormal stacking, effectively improving the efficiency and accuracy of warehouse management.

[0072] In smart warehouses, if goods are placed in the wrong location, it can lead to chaotic inventory management, reduced picking efficiency, and errors in subsequent logistics processes. The method of the present invention promptly detects abnormal placement of goods and triggers an early warning, allowing staff to quickly locate and address the problem, effectively avoiding order errors and inventory discrepancies caused by misplaced goods. This solves the common problems of inaccurate inventory and picking errors in warehouse management systems, improving overall operational efficiency and service quality.

[0073] An RFID static ranging method comprises the following steps:

[0074] Step 1: Based on the existing RFID communication protocol, the OFDM communication mechanism is introduced to realize the concurrent transmission and reception of multi-frequency signals, thereby collecting multi-frequency phase information;

[0075] Step 2: Correct the collected multi-frequency phase information to eliminate the phase error introduced by the hardware, and calculate the frequency-phase gradient based on the corrected multi-frequency phase;

[0076] Step 3: Construct two types of distance evaluation models based on frequency-phase gradient and multipath characteristics. Combined with the distribution complexity of frequency-phase gradient, select the model that adapts to the current environment to accurately estimate the distance between RFID reader and tag.

[0077] The method for concurrently acquiring multi-frequency phases using the OFDM mechanism described in step 1 includes:

[0078] Step 1-1, constructing a corresponding OFDM symbol X(f) according to OFDM symbol parameter information and RFID communication protocol parameter configuration;

[0079] Step 1-2: Use OFDM symbol X(f) to replace the high-level carrier in the tag response EPC phase and send it to the tag;

[0080] Step 1-3: extract the OFDM symbol Y(f) from the tag reflected signal, compare the frequency domain representations X(f) and Y(f) of the transmitted and received OFDM symbols, and obtain the multi-frequency phase information.

[0081] The frequency phase gradient calculation method in step 2 includes:

[0082] Step 2-1-1: Attach the RFID tag to the surface of the reader antenna and measure the phase of the received signal to obtain the phase deviation introduced by the hardware.

[0083] Step 2-1-2, subtracting the phase deviation from the multi-frequency phase collected in step 1 to obtain a corrected multi-frequency phase;

[0084] Step 2-1-3, calculate the phase gradient between adjacent frequencies based on the corrected multi-frequency phase. The frequency phase gradient calculation formula is:

[0085]

[0086] in, represents the phase gradient of the ith frequency, f i represents the frequency of the i-th channel, θ(f i ) indicates that the channel frequency is f i The phase of time;

[0087] In step 2-1-4, assuming that the OFDM symbol contains n subchannels, calculate the frequency-phase gradient vector containing n-1 dimensions according to the frequency-phase gradient calculation formula defined in step 2-2-1

[0088] The method for performing RFID ranging based on frequency-phase gradient distribution complexity in step 3 includes:

[0089] Step 3-1, constructing a distance assessment model based on frequency-phase gradient and a distance assessment model based on multipath propagation characteristics;

[0090] Step 3-2, calculate the distribution complexity of the frequency-phase gradient, and select a distance evaluation model that is suitable for the current deployment environment based on the distribution complexity, so as to achieve accurate estimation of the distance between the RFID reader and the tag.

[0091] The OFDM symbol construction method described in step 1-1 includes:

[0092] Step 1-1-1, set the bandwidth and number of subcarriers of OFDM symbols, and assign subchannel parameters;

[0093] Step 1-1-2, set the OFDM symbol length according to the tag state switching period, and define the tag state switching period as T switch , set the OFDM symbol length T ofdm Set to half of the label state switching cycle, that is, Ensure that a complete OFDM symbol is included in any tag state period;

[0094] Step 1-1-3, add a cyclic prefix to the OFDM symbol, copy the tail data of the OFDM symbol and place it at the beginning of the symbol to form the final OFDM symbol for transmission.

[0095] The multi-frequency phase extraction method described in steps 1-3 includes:

[0096] Step 1-3-1, perform moving average filtering on the signal received by the RFID reader, and perform correlation matching with the tag response preamble to detect the starting position of the tag response packet;

[0097] Step 1-3-2: Based on the cyclic prefix characteristics of the OFDM symbol, two sliding windows are defined. One window is used to cover the cyclic prefix part of the OFDM symbol, and the other window is used to cover the tail part of the OFDM symbol. By calculating the correlation between the two sliding windows, the starting position of the OFDM symbol is determined and the complete OFDM symbol is extracted.

[0098] Step 1-3-3: perform differential processing on the OFDM symbols under different reflection states to eliminate environmental interference, and perform Fourier transform on the differential symbols and the OFDM symbols sent by the reader to obtain their frequency domain complex representations X(f) and Y(f);

[0099] Steps 1-3-4, calculate the frequency domain complex difference Get the multi-frequency phase set Here, Real(·) represents the real part of a complex number, and Imag(·) represents the imaginary part of a complex number.

[0100] The construction of the frequency-phase gradient-based distance estimation model described in step 3-1 includes:

[0101] Step 3-1-1-1: construct a distance evaluation model based on frequency-phase gradient, which satisfies:

[0102]

[0103] in, represents the frequency phase gradient, d represents the distance between the reader and the tag, and c represents the propagation speed of the signal;

[0104] Step 3-1-1-2, average the frequency-phase gradient phase vector obtained in step 2-1-4 to obtain The frequency-phase gradient mean The distance between the reader and the tag is obtained by bringing it into the frequency-phase gradient based distance evaluation model.

[0105] The distance evaluation model based on multipath propagation characteristics is specifically constructed as follows:

[0106] Step 3-1-2-1, construct a distance assessment model based on multipath characteristics, the multipath channel distance assessment model parameterizes two main unknown quantities: the length of each multipath path d i (where d0 represents the line-of-sight (LoS) path distance) and the tag's reflection coefficient μ, while the remaining minor parameters are assigned empirically determined constant values. On this basis, a set of observation equations are established through phase measurement at multiple frequencies. Each equation reflects the coherent superposition effect of signals from different paths at the corresponding frequency. Assume that the downlink signal emitted by the RFID reader can be expressed as:

[0107] S R (t) = Ae j2πft ,

[0108] Where A represents the amplitude of the signal sent by the reader, f represents the frequency of the signal, j represents the imaginary unit, and t is the time variable, which is used to calculate the value of the signal at a certain moment. Considering the impact factor M on the signal caused by the i-th non-line-of-sight path (NLoS) i , including amplitude attenuation With the phase change 2πfτ i , which is expressed as:

[0109]

[0110] Among them, the amplitude attenuation It approximately satisfies the inverse square law of free space path loss and is affected by frequency, propagation distance, and the reflection coefficient r of the reflector. i To simplify the expression, let where r i is the reflection coefficient of the reflector corresponding to the i-th path, and for the LOS path, r i =1; propagation delay where c is the signal propagation speed; hence, the composite effect of all downlink paths on the signal is:

[0111]

[0112] Downlink signal S R (t) becomes S after reaching the label RT (t):

[0113] S RT (t) = S R (t)·M

[0114] Considering the reflective characteristics of the tag and the symmetrical uplink channel, the signal received by the reader is:

[0115] S TR (t) = μ·S R (t)·M 2

[0116] Step 3-1-2-2, the reader receives the S TR After IQ demodulation of the (t) signal, the total phase θ(f) including the downlink, reflection, and uplink channel effects is obtained. This phase can be formalized as a function g:

[0117] θ(f)=g(f,μ,d0,d1,…,d n )

[0118] Where f represents the signal frequency, μ represents the tag reflection coefficient, and d i Indicates the propagation distance of the signal under different paths, n represents the total number of paths; based on multi-frequency phase measurement values Then the following equations are established:

[0119]

[0120] Step 3-1-2-3, by numerically solving the above equations, the propagation distance of each path is analyzed, that is, the actual distance between the tag and the reader is calculated.

[0121] The distance model selection strategy based on the frequency-phase gradient distribution complexity described in step 3-2 includes:

[0122] Step 3-2-1, frequency-phase gradient vector obtained according to step 2-1-4 The distribution complexity of the frequency-phase gradient is calculated. The distribution complexity of the phase gradient is:

[0123]

[0124] in, represents the normalized phase gradient, represents the mean of the normalized phase gradient;

[0125] In step 3-2-2, a suitable distance evaluation model is selected based on the comparison between the distribution complexity MCE and the preset threshold δ.

[0126] Step 3-2-2 is as follows: If MCE is greater than δ, the tag is judged to be in a multipath dense scenario, and a distance evaluation model based on the multipath model is selected to improve the ranging accuracy; if MCE is less than or equal to δ, it is judged to be a multipath sparse scenario, and a model based on frequency-phase gradient is selected to improve the real-time performance of ranging.

[0127] This method was developed in a real-world scenario using a typical RFID system using standard RFID tags, and extensive experiments were conducted to verify its practical performance. The experiments used a USRPN210 software-defined radio (SDR) device to implement a reader enhanced with OFDM communication mechanisms, enabling concurrent multi-frequency phase acquisition. The experimental equipment included two 9dBic circularly polarized antennas (one transmitting and one receiving) operating at approximately 920MHz, and several Alien9640 tags.

[0128] To verify the ranging accuracy of the method proposed in this embodiment, 100 tags were randomly placed in a 4*4 meter area. The multipath environment of each tag was different. The actual distance between the reader and the tag was measured in advance. Then, the distance between the reader and the tag was evaluated using the method proposed in this embodiment. Different OFDM symbol bandwidths were configured to verify the impact of OFDM on ranging accuracy. Figure 5 As shown in the figure, the vertical distances in the boxplots corresponding to different OFDM symbol bandwidth configurations represent their ranging errors. Longer distances indicate greater ranging errors, while shorter distances indicate smaller ranging errors. Clearly, the method proposed in this embodiment can achieve sub-meter positioning accuracy, and the ranging error decreases as the OFDM symbol bandwidth increases.

[0129] In addition to ranging accuracy, the time efficiency of the method is also crucial. Taking the time division frequency hopping (TDFH) method of acquiring phase as a benchmark, the improvement in time efficiency of the method proposed in this embodiment is verified. Except for the different phase acquisition methods, the other ranging steps of the two methods remain consistent. The experiment was carried out in three scenarios. In scenario one, 10 tags were randomly placed in an area of ​​4*4 meters; in scenario two, 20 tags were randomly placed in an area of ​​4*4 meters; in scenario three, 50 tags were randomly placed in an area of ​​4*4 meters. In the three scenarios, the bandwidth of the OFDM symbol is set to 25MHz. As Figure 6 The figure shows a comparison of the ranging time efficiency of the method proposed in this embodiment and the TDFH method in three scenarios. In all scenarios, the time overhead of the method proposed in this embodiment is much lower than that of the TDFH method.

[0130] The present invention provides an RFID static ranging method. Numerous methods and approaches exist for implementing this technical solution. The foregoing description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Any components not specified in this embodiment may be implemented using existing technologies.

Claims

1. An RFID static ranging method, characterized in that: The following steps are involved: Step 1: Based on the existing RFID communication protocol, the OFDM communication mechanism is introduced to realize the concurrent transmission and reception of multi-frequency signals, thereby collecting multi-frequency phase information; Step 2: Correct the collected multi-frequency phase information to eliminate the phase error introduced by the hardware, and calculate the frequency-phase gradient based on the corrected multi-frequency phase; Step 3: Construct two types of distance evaluation models based on frequency-phase gradient and multipath characteristics. Combined with the distribution complexity of frequency-phase gradient, select the model that adapts to the current environment to accurately estimate the distance between RFID reader and tag.

2. The RFID static ranging method according to claim 1, characterized in that: The method for concurrently acquiring multi-frequency phases using the OFDM mechanism described in step 1 includes: Step 1-1, constructing a corresponding OFDM symbol X(f) according to OFDM symbol parameter information and RFID communication protocol parameter configuration; Step 1-2: Use OFDM symbol X(f) to replace the high-level carrier in the tag response EPC phase and send it to the tag; Step 1-3: extract the OFDM symbol Y(f) from the tag reflected signal, compare the frequency domain representations X(f) and Y(f) of the transmitted and received OFDM symbols, and obtain the multi-frequency phase information.

3. The RFID static ranging method according to claim 2, characterized in that: The frequency phase gradient calculation method in step 2 includes: Step 2-1-1: Attach the RFID tag to the surface of the reader antenna and measure the phase of the received signal to obtain the phase deviation introduced by the hardware. Step 2-1-2, subtracting the phase deviation from the multi-frequency phase collected in step 1 to obtain a corrected multi-frequency phase; Step 2-1-3, calculate the phase gradient between adjacent frequencies based on the corrected multi-frequency phase. The frequency phase gradient calculation formula is: in, represents the phase gradient of the ith frequency, f i represents the frequency of the i-th channel, θ(f i ) indicates that the channel frequency is f i The phase of time; In step 2-1-4, assuming that the OFDM symbol contains n subchannels, calculate the frequency-phase gradient vector containing n-1 dimensions according to the frequency-phase gradient calculation formula defined in step 2-2-1 4. The RFID static ranging method according to claim 3, characterized in that: The method for performing RFID ranging based on frequency-phase gradient distribution complexity in step 3 includes: Step 3-1, constructing a distance assessment model based on frequency-phase gradient and a distance assessment model based on multipath propagation characteristics; Step 3-2, calculate the distribution complexity of the frequency-phase gradient, and select a distance evaluation model that is suitable for the current deployment environment based on the distribution complexity, so as to achieve accurate estimation of the distance between the RFID reader and the tag.

5. The RFID static ranging method according to claim 4, characterized in that: The OFDM symbol construction method described in step 1-1 includes: Step 1-1-1, set the bandwidth and number of subcarriers of OFDM symbols, and assign subchannel parameters; Step 1-1-2, set the OFDM symbol length according to the tag state switching period, and define the tag state switching period as T switch , set the OFDM symbol length T ofdm Set to half of the label state switching cycle, that is, Step 1-1-3, add a cyclic prefix to the OFDM symbol, copy the tail data of the OFDM symbol and place it at the beginning of the symbol to form the final OFDM symbol for transmission.

6. The RFID static ranging method according to claim 5, characterized in that: The multi-frequency phase extraction method described in steps 1-3 includes: Step 1-3-1, perform moving average filtering on the signal received by the RFID reader, and perform correlation matching with the tag response preamble to detect the starting position of the tag response packet; Step 1-3-2: Based on the cyclic prefix characteristics of the OFDM symbol, two sliding windows are defined. One window is used to cover the cyclic prefix part of the OFDM symbol, and the other window is used to cover the tail part of the OFDM symbol. By calculating the correlation between the two sliding windows, the starting position of the OFDM symbol is determined and the complete OFDM symbol is extracted. Step 1-3-3: perform differential processing on the OFDM symbols under different reflection states, and perform Fourier transform on the differential symbols and the OFDM symbols sent by the reader to obtain their frequency domain complex representations X(f) and Y(f); Steps 1-3-4, calculate the frequency domain complex difference Get the multi-frequency phase set Here, Real(·) represents the real part of the complex number, and Imaxg(·) represents the imaginary part of the complex number.

7. The RFID static ranging method according to claim 6, characterized in that: The construction of the frequency-phase gradient-based distance estimation model described in step 3-1 includes: Step 3-1-1-1: construct a distance evaluation model based on frequency-phase gradient, which satisfies: in, represents the frequency phase gradient, d represents the distance between the reader and the tag, and c represents the propagation speed of the signal; Step 3-1-1-2, average the frequency-phase gradient phase vector obtained in step 2-1-4 to obtain The frequency-phase gradient mean The distance between the reader and the tag is obtained by bringing it into the frequency-phase gradient based distance evaluation model.

8. The RFID static ranging method according to claim 7, characterized in that: The distance assessment model based on multipath propagation characteristics described in step 3-1 is specifically constructed as follows: Step 3-1-2-1, construct a distance assessment model based on multipath characteristics, the multipath channel distance assessment model parameterizes two main unknown quantities: the length of each multipath path d i The reflection coefficient μ of the tag is given by the user, and the other minor parameters are assigned constant values ​​determined by experience. On this basis, a set of observation equations are established through phase measurement at multiple frequencies. Each equation reflects the coherent superposition effect of signals from different paths at the corresponding frequency. The downlink signal sent by the RFID reader can be expressed as: S R (t)=Ae j2πft , Among them, A represents the amplitude of the signal sent by the reader, f represents the frequency of the signal, j represents the imaginary unit, and t is the time variable. Considering the influence factor M caused by the i-th non-line-of-sight path on the signal i , including amplitude attenuation With the phase change 2πfτ i , which is expressed as: Among them, the amplitude attenuation It approximately satisfies the inverse square law of free space path loss and is affected by frequency, propagation distance, and the reflection coefficient r of the reflector. i The combined influence of where r i is the reflection coefficient of the reflector corresponding to the i-th path, and for the LOS path, r i =1; propagation delay where c is the signal propagation speed; hence, the composite effect of all downlink paths on the signal is: Downlink signal S R (t) becomes S after reaching the label RT (t): S RT (t)=S R (t)·M Considering the reflective characteristics of the tag and the symmetrical uplink channel, the signal received by the reader is: S TR (T)=μ·S R (t)·M 2 Step 3-1-2-2, the reader receives the S TR After IQ demodulation of the (t) signal, the total phase θ(f) including the downlink, reflection, and uplink channel effects is obtained. This phase can be formalized as a function g: θ(f)=g(f,μ,d0,d1,…,d n ) Where f represents the signal frequency, μ represents the tag reflection coefficient, and d i Indicates the propagation distance of the signal under different paths, n represents the total number of paths; based on multi-frequency phase measurement values Then the following equations are established: Step 3-1-2-3, by numerically solving the above equations and analyzing the propagation distance of each path, the actual distance between the tag and the reader can be calculated.

9. The RFID static ranging method according to claim 8, characterized in that: The distance model selection strategy based on the frequency-phase gradient distribution complexity described in step 3-2 includes: Step 3-2-1, frequency-phase gradient vector obtained according to step 2-1-4 The distribution complexity of the frequency-phase gradient is calculated. The distribution complexity of the phase gradient is: in, represents the normalized phase gradient, represents the mean of the normalized phase gradient; In step 3-2-2, the distance evaluation model is selected based on the comparison between the distribution complexity MCE and the preset threshold δ.

10. The RFID static ranging method according to claim 9, characterized in that: Step 3-2-2 is as follows: If MCE is greater than δ, the tag is judged to be in a multipath dense scenario, and a distance evaluation model based on the multipath model is selected to improve the ranging accuracy; if MCE is less than or equal to δ, it is judged to be a multipath sparse scenario, and a model based on frequency-phase gradient is selected to improve the real-time performance of ranging.

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