A single-chip multiple-nfc-antenna tag, a production process thereof, and a tag communication method

Abstract

The application relates to the technical field of anti-fake labels, and provides a single-chip extended multi-NFC antenna label and a production process and label communication method thereof, the method comprising the following steps: a chip generates a dynamic energy field in a three-dimensional space through phase-adjustable multi-path radio frequency units, a space distribution map of the label type is generated, and each antenna unit is driven to exchange data with the label according to a priority through an asymmetric time division multiple access scheduling mechanism; the dynamic energy field is captured through label resonance feedback to obtain an original response set containing time domain overlapping signals; the original response set is extracted into a physical layer feature vector of each label through parallel demodulation based on deep learning signal separation, and is converted into a unified structured instruction set; and the operation result is finally reconstructed into an anti-interference communication result set through a redundancy check matrix. The label comprises a first coil, a second coil, a riveting position, a chip and a defective ink spot. The application significantly improves the multi-label processing capacity and communication reliability of an NFC system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anti-counterfeiting labels, and in particular to a single-chip extended multi-NFC antenna label and a production process and label communication method thereof. BACKGROUND

[0002] Near field communication (NFC) technology, as a short-range high-frequency wireless communication technology, has been widely used in mobile payment, access control systems, and logistics tracking fields. In traditional NFC applications, a single chip usually drives only a single antenna. However, with the increasing complexity of Internet of Things scenarios, such as smart shelves and multi-label inventory, there is an urgent need for a solution that can extend multiple antennas through a single chip to reduce hardware costs, simplify system structure, and improve communication efficiency. Existing multi-antenna extension solutions have problems such as timing conflicts, power consumption surges, and signal interference, which limit the feasibility of large-scale deployment. In the prior art, NFC labels are added to 3D printing consumable products to improve product market competitiveness and brand value, better maintain product market stability, and combat the influx of counterfeit products into the consumer market. Currently, two labels are attached to a tray, which is very inconvenient for data collection of the product (tray) and can easily lead to data confusion. The current design uses a double-coil single-wire tag to solve the data collection problem through multiple-to-multiple reading. Attaching two labels to a tray is too costly, and the existing double-coil single-wire tag is more cost-effective.

[0003] Prior art one, application number: CN202510213383.9 discloses a high-sensitivity metal micro-strain sensor label and a detection method thereof, which is applied to the fields of non-destructive testing and structural health monitoring. To solve the problems of low strain detection sensitivity and difficulty in detecting micro-strain of existing label antennas, a high-sensitivity metal micro-strain RFID sensor label is provided to be attached to the surface of a component. When the label deforms, its impedance changes to Zsensed, and the radar cross section changes accordingly. The reader can remotely monitor the antenna parameters according to the changes in RCS0 and RCS1 while communicating with the label, thereby inferring the changes in the return signal strength RSSI and indirectly obtaining the label deformation. When the label antenna impedance changes, the resonant frequency of the label also changes, and by analyzing the resonant frequency shift, the deformation information of the label can also be indirectly obtained. Although this solution solves the problems of low strain detection sensitivity and difficulty in detecting micro-strain of existing label antennas, it focuses on improving the sensitivity of metal micro-strain RFID labels for structural health monitoring. It is only suitable for detecting the impedance and resonant frequency changes of a single label and cannot handle concurrent communication of multiple labels. It lacks concurrent identification and communication capabilities in dense multi-label environments and does not address signal aliasing separation and protocol compatibility issues.

[0004] The prior art two, application number: CN202510455838.8 discloses a preparation method and system of high-performance electronic tag, comprising: obtaining the working parameters of high-frequency / NFC electronic tag in high-temperature environment, analyzing the conductive performance change trend of antenna material, establishing a mathematical model of the influence of high-temperature environment on antenna material, adjusting the component ratio of antenna material according to the model, and obtaining the optimized antenna material formula; on the basis of optimizing the electromagnetic shielding scheme, collecting the comprehensive performance data of high-frequency / NFC electronic tag in different environments, establishing a performance prediction model under the coupling action of multiple environmental factors, using the model to simulate the working state of the label under complex working conditions, and judging the performance stability; after accurately processing the antenna pattern, collecting the characteristic data of each layer of material of high-frequency / NFC electronic tag, and establishing a relationship model of material characteristics and bonding strength. Although the plasma surface treatment technology is used to enhance the interlayer adhesion, and the optimized bonding process scheme is obtained; however, optimizing the high-temperature stability and material performance of high-frequency / NFC label only involves physical layer material optimization, and does not improve the multi-label collaborative communication capability; lacks a dynamic radio frequency scheduling mechanism, and cannot optimize the parallel communication efficiency of multiple labels; does not solve the problem of heterogeneous protocol compatibility and anti-interference.

[0005] The prior art three, application number: CN202410177214.X discloses an electronic device, a communication method and system based on NFC, comprising: the electronic device comprises an NFC module, the NFC module comprises a plurality of NFC tags with the same content, and the antennas of any two NFC tags do not completely overlap, which can increase the range and sensitivity of the electronic device being inducted by a card reading device, so as to facilitate the induction and reading of the NFC tags in the electronic device by the card reading device. Although the success rate and efficiency of the induction of the NFC tags in the electronic device are improved, and the communication efficiency and reliability of the electronic device, the communication method and system based on NFC applied to different scenes can be improved; however, the induction range of a single device is improved by the multi-antenna layout, which is only applicable to the communication optimization of a single device, and cannot be extended to multiple labels simultaneously interacting; lacks spatial energy scheduling capability, and cannot realize efficient concurrent access of dense label groups; does not involve security authentication and data aggregation mechanism.

[0006] The prior art one, the prior art two and the prior art three have the problem that the existing NFC label can only be read one by one at a fixed point and cannot be read in multiple directions. Therefore, the present application provides a single-chip expansion of multiple NFC antenna labels and a production process and label communication method. SUMMARY

[0007] In order to solve the above technical problems, the present application provides a single-chip expansion of multiple NFC antenna label communication method, comprising the following steps:

[0008] The chip constructs a dynamic energy field to realize multi-tag differentiated excitation, and completes concurrent communication driven by priority through protocol analysis and intelligent scheduling; the system integrates deep learning and semantic translation to decouple and convert the aliasing signal into standardized instructions, solves the multi-protocol compatibility problem; the structured instruction set is processed through a bidirectional authentication pipeline to complete multi-tag security key negotiation, and the security channel negotiated is executed through a block chain data aggregation engine to perform distributed read-write operation, and the operation result is reconstructed through a redundancy check matrix to finally generate an anti-interference communication result set.

[0009] Optionally, the process of generating the anti-interference communication result set comprises the following steps:

[0010] The cryptographic hash values of the physical layer feature vectors of each tag reserved by the previous flow are separated from the unified structured instruction set, and a set of temporary identity credentials with spatial correlation is generated by combining the spatial distribution map provided by the tag spatial topology information;

[0011] The temporary identity credential set and the physical layer feature vector are processed through a dynamic physically unclonable function engine to generate a dynamic challenge sequence according to the historical state parameters of the dynamic energy field, and generate a one-time variable encrypted authentication evidence stream; after the encrypted authentication evidence stream is verified through consensus based on fuzzy matching, an asynchronous key negotiation mechanism is triggered, the key shares of each tag are interleaved and aggregated using the initial link of the block chain data aggregation engine, forming a shared master key chain and deriving an independent security channel;

[0012] The original operation result generated by the independent security channel executing distributed read-write operation is output as an original result vector set with complete space-time marks; the original result vector set is processed through a redundancy check matrix constructor to dynamically generate an optimal check dimension according to the number of communication channels, spatial density and historical interference mode, and construct an anti-tamper multi-dimensional check tensor introducing the shared master key chain as a randomization seed;

[0013] The original result vector set with space-time marks is executed through a multi-dimensional check tensor to generate a strengthened result set attached with strong encryption check codes; the strengthened result set is finally processed through a consistency reconstructor, cross-verified and corrected using the check tensor, and the dynamic energy field historical data corresponding to the time-space marks of the data unit whose verification fails is repaired and restored, and a high-integrity anti-interference communication result set is aggregated and generated.

[0014] Optionally, the process of constructing an anti-tamper multi-dimensional check tensor introducing the shared master key chain as a randomization seed comprises the following steps:

[0015] Convolve the spatial density and the historical interference mode to generate a spatial weighted interference probability distribution map, and perform matrix multiplication with the number of communication channels to calculate the minimum amount of redundant information; output the dynamic optimal check dimension value;

[0016] create an empty base tensor with the dynamic optimal check dimension value as the order; each initial element position of the empty base tensor is initialized and scrambled by a coordinate offset derived from the shared master key chain; an initial tensor framework with a cryptographic chaos characteristic is formed from the scrambled empty base tensor;

[0017] split the key chain into multiple segments, each segment controls the polynomial coefficient of the different section of the empty base tensor; and the metadata of the original result vector set with the space-time mark is subjected to a modulo operation to construct an anti-tamper multi-dimensional check tensor which is strongly bound to the session key and has a unique structure.

[0018] Optionally, the process of modulo operation between the polynomial coefficient and the metadata of the original result vector set with the space-time mark includes the following steps:

[0019] The spatial coordinate index of the target cell in the initial tensor framework and a specific key segment shared by the master key chain are input into the coordinate-key obfuscator; the coordinate-key obfuscator performs XOR and cyclic shift operations on the coordinate value and the key segment to generate a temporary cell-specific entropy value; at the same time, a context token strongly related to the specific operation time and place is output;

[0020] The cell-specific entropy value and the context token are spliced, and then another different key segment is used as a selector to extract bytes at a specific position from the spliced result to generate an intermediate decision seed; the intermediate decision seed is multiplied by the historical error rate weight to generate a dynamic decision factor;

[0021] The generated dynamic decision factor is subjected to a modulo operation with a modulus reference value derived from the polynomial coefficient to obtain a normalized algorithm selection index value; the algorithm decision mapping table outputs a specific algorithm identifier according to the algorithm selection index value, and the algorithm identifier indicates which one of the parity check, cyclic redundancy check, or Reed-Solomon encoding variant should be used to fill the algorithm for the cell;

[0022] The algorithm identifier and the original data content of the current cell are sent to the parameterized algorithm execution unit; a unique check code is calculated for the specific cell, and it is filled into the corresponding position of the initial tensor framework to complete the construction of the cell.

[0023] Optionally, the process of the algorithm decision mapping table outputting a specific algorithm identifier according to the algorithm selection index value includes the following steps:

[0024] The dynamic optimal check dimension value calculated by the check strategy fusion core is squared to obtain a basic mapping space size; the basic mapping space size is subjected to bitwise AND operation with a fixed key segment of the shared master key chain to generate an actual mapping table size value, and an empty mapping table skeleton to be filled is initialized by the actual mapping table size value;

[0025] The remaining part of the key chain is divided into a plurality of cryptographic slices with different lengths, the first slice is used to generate an initial algorithm type distribution weight vector, and the second and subsequent slices are used to create a nonlinear perturbation program; an original mapping table whose content is preliminarily shaped by the key but has not yet been associated with the current environment is output by the mapping logic filler;

[0026] According to the frequency of occurrence of each type of error in the error feature vector, the distribution density of the corresponding algorithm identifier in the original mapping table is dynamically adjusted; in the area where the historical burst error is high, the mapping probability of the Reed-Solomon encoding variant algorithm is increased; an environment experience optimized adaptive mapping table is generated;

[0027] The normalized algorithm selection index value is first subjected to a nonlinear perturbation program controlled by the key to generate a final encrypted and confused lookup key value, and a fuzzy matching mechanism is used for addressing in the environment experience optimized adaptive mapping table; the specific algorithm identifier that determines the cell is output by the fuzzy matching mechanism.

[0028] Optionally, the process of using the fuzzy matching mechanism based on the key value range includes the following steps:

[0029] The last few digits of the dynamic optimal check dimension value are processed by the numerical feature extractor to separate the parity characteristics and prime factor distribution characteristics to form an initial threshold modulation vector; the initial threshold modulation vector generates a reference floating threshold through nonlinear transformation;

[0030] The reference floating threshold is coupled with the current load factor of the environment experience optimized adaptive mapping table to generate a dynamic range radius; the dynamic range radius is added or subtracted with the encrypted and confused lookup key value to determine the upper and lower bounds of fuzzy matching, forming a dynamic matching window;

[0031] All entries in the dynamic matching window enter the weight evaluation stage, and the spatial error correlation coefficient extracted from the historical interference mode is used as a weighting factor; the weighting factor is convoluted with the inherent priority of each entry to generate a candidate entry confidence sequence; the optimal matching candidate set is screened out;

[0032] The optimal matching candidate set adopts the nearest neighbor priority principle based on time decay, and combines the numerical distribution characteristics of the lookup key value to output the determined algorithm identifier from the optimal matching candidate set.

[0033] Optionally, the process of outputting the determined algorithm identifier from the optimal matching candidate set comprises the following steps:

[0034] The optimal matching candidate set uses the time stamp information of the spatial error code correlation coefficient extracted from the historical interference mode to obtain the interval between the historical decision time corresponding to each candidate entry and the current time; the time interval is transformed by a negative exponential function to generate a time decay factor sequence;

[0035] The time decay factor sequence and the candidate entry confidence sequence are weighted and fused, wherein the time decay factor is used as a weight coefficient to multiply the confidence; the multiplication operation produces a time-sensitive confidence score; the time-sensitive confidence score is normalized to form a priority sequence with time-sensitive characteristics;

[0036] At the same time, the neighborhood optimization program adjusts the arrangement order of each candidate entry in the priority sequence according to the stability index, enhances the weight of the nearest neighbor principle in the numerical distribution area with lower stability, and maintains the original priority order in the area with higher stability;

[0037] The candidate set adjusted by the neighborhood optimization program uses a proximity measurement method based on Mahalanobis distance to obtain the comprehensive distance between each candidate entry and the ideal matching point in combination with the numerical distribution stability index; the distance produces a final matching degree score; the final matching degree score is sorted and selected, and the algorithm identifier corresponding to the highest score is output as the final decision result.

[0038] Optionally, it also comprises a chip that generates a dynamic energy field in three-dimensional space through a phase-adjustable multi-path radio frequency unit, so that multiple tags entering the induction area simultaneously obtain differentiated energy distribution and feedback resonance characteristics; the feedback resonance characteristics are processed by an adaptive protocol analysis engine to generate a spatial distribution map of the tag type, and the spatial distribution map drives each antenna unit to exchange data with the tag according to the priority through an asymmetric time division multiple access scheduling mechanism.

[0039] The dynamic energy field is captured through tag resonance feedback processing to obtain an original response set containing time domain overlapping signals, the original response set is extracted through parallel demodulation based on deep learning signal separation to obtain physical layer feature vectors of each tag, and the physical layer feature vectors are converted into a unified structured instruction set through cross-protocol semantic translation.

[0040] The single-chip extended multiple NFC antenna tag provided by the application comprises a first coil, a second coil, a riveting position, a chip and a defective ink dot.

[0041] The chip is connected with the first coil and the second coil through double parallel circuits to form a redundant design, and the riveting position realizes the connection of the first coil, the second coil and the pad of the chip; the defective ink dot is printed on the test point of the chip, and detection is carried out during automatic testing.

[0042] The application provides a production process of a single-chip extended multiple NFC antenna label, comprising the following steps:

[0043] Step one, the blank flexible substrate is subjected to surface cleaning and plasma activation treatment to obtain a pretreated substrate with uniform surface energy;

[0044] Step two, the pretreated substrate is subjected to a screen printing conductive silver paste or etching copper foil process to obtain an array pattern comprising multiple NFC antenna units, and after high-temperature curing or chemical etching post-treatment, a stable conductive antenna network layer is obtained;

[0045] Step three, the antenna network layer is positioned, a single NFC chip is connected with the antenna unit through conductive adhesive dispensing or flip chip bonding process to obtain a primary complex, and the primary complex is subjected to heat pressing curing or reflow soldering process to obtain a chip-antenna module with stable electrical performance;

[0046] Step four, the chip-antenna module is subjected to a laminating process of covering a PET protective film or injection molding epoxy resin to obtain a semi-finished product with a protective structure, and the semi-finished product is subjected to die cutting or laser cutting process to obtain independent label units;

[0047] Step five, the label units are subjected to radio frequency performance test screening, the qualified products are subjected to data burning equipment to write personalized information to obtain identifiable intelligent labels, and the intelligent labels are subjected to appearance quality inspection and impedance matching debugging to finally obtain NFC antenna label finished products meeting industrial standards.

[0048] The application realizes concurrent communication and data integration of high-density NFC tag groups through a multi-level cooperative processing mechanism; a three-dimensional dynamic energy field formed by a phase-adjustable multi-path radio frequency unit realizes spatial differentiation of electromagnetic energy distribution, combined with a spatial distribution map generated by an adaptive protocol analysis engine, forming a spatial addressing basis for physical layer multi-tag identification; an asymmetric time division multiple access scheduling mechanism extends the time slice allocation of traditional TDMA to a space-time two-dimensional scheduling domain, realizing parallel communication access control of multiple tags; a deep separation architecture of time domain overlapping signals solves the signal aliasing problem in dense tag environment through physical layer feature vector extraction; a cross-protocol semantic translation layer establishes a normalization processing pipeline for heterogeneous tag protocols, eliminating the influence of protocol differences of multiple manufacturers' tags on system-level operations. A bidirectional authentication pipeline realizes distributed negotiation of multi-tag keys, and a block chain type data aggregation engine guarantees the atomicity of multi-tag operations through fragmentation-recombination mechanism; a redundancy check matrix reconstructs the integrity of distributed read-write results based on the principle of forward error correction coding, forming a closed-loop protection system for anti-interference communication.

[0049] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the application. The objects and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims.

[0050] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0051] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0052] Figure 1 The flow chart of the method for expanding multiple NFC antenna tags to communicate by a single chip in embodiment 1 of the present application;

[0053] Figure 2 The schematic diagram of the method for expanding multiple NFC antenna tags to communicate by a single chip in embodiment 2 of the present application;

[0054] Figure 3 The process diagram of driving each antenna unit to exchange data with tags according to priority in embodiment 3 of the present application;

[0055] Figure 4 The process diagram of extracting physical layer feature vectors of each tag in embodiment 5 of the present application;

[0056] Figure 5 The process diagram of generating an anti-interference communication result set in embodiment 7 of the present application;

[0057] Figure 6 This is a schematic diagram of the structure of a single chip extending multiple NFC antenna tags in Embodiment 13 of the present invention;

[0058] Figure 7 This is an application effect diagram of extending multiple NFC antenna tags onto a single chip in Embodiment 13 of the present invention. Detailed Implementation

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0060] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0061] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0062] Example 1: As Figure 1 As shown, this embodiment of the invention provides a communication method for extending multiple NFC antenna tags with a single chip, comprising the following steps:

[0063] S100: The chip generates a dynamic energy field in three-dimensional space through a phase-tunable multi-channel radio frequency unit, enabling multiple tags entering the sensing area to simultaneously obtain differentiated energy distribution and feedback resonance characteristics; the feedback resonance characteristics are processed by an adaptive protocol parsing engine to generate a spatial distribution map of the tag type, and the spatial distribution map is driven by an asymmetric time division multiple access scheduling mechanism to drive each antenna unit to exchange data with the tag according to priority.

[0064] S200: The dynamic energy field is captured by the tag resonance feedback to obtain an original response set containing time domain overlapping signals, the original response set is extracted by parallel demodulation based on deep learning signal separation to obtain a physical layer feature vector of each tag, and the physical layer feature vector is converted into a unified structured instruction set by cross-protocol semantic translation;

[0065] S300: The structured instruction set is processed by a bidirectional authentication pipeline to complete multi-tag security key negotiation, a distributed read-write operation is performed on the negotiated secure channel by a block chain data aggregation engine, and an anti-interference communication result set is finally generated by reconstructing the operation result by a redundancy check matrix.

[0066] The working principle and beneficial effects of the above technical solution are: first, the chip generates a dynamic energy field in three-dimensional space through a phase-adjustable multi-path radio frequency unit, so that multiple tags entering the induction area simultaneously obtain differentiated energy distribution and feedback resonance characteristics; the spatial distribution map of the tag type is generated by processing the feedback resonance characteristics through an adaptive protocol analysis engine, and each antenna unit exchanges data with the tag according to the priority driven by the asymmetric time division multiple access scheduling mechanism; second, the dynamic energy field is captured by the tag resonance feedback to obtain an original response set containing time domain overlapping signals, the original response set is extracted by parallel demodulation based on deep learning signal separation to obtain a physical layer feature vector of each tag, and the physical layer feature vector is converted into a unified structured instruction set by cross-protocol semantic translation; finally, the structured instruction set is processed by a bidirectional authentication pipeline to complete multi-tag security key negotiation, a distributed read-write operation is performed on the negotiated secure channel by a block chain data aggregation engine, and an anti-interference communication result set is finally generated by reconstructing the operation result by a redundancy check matrix (the specific principle is shown in Figure 2 The above scheme realizes concurrent communication and data integration of high-density NFC tag groups through a multi-level cooperative processing mechanism; the three-dimensional dynamic energy field constructed by the phase-adjustable multi-path radio frequency unit realizes spatial differentiation of electromagnetic energy distribution, combined with the spatial distribution map generated by the adaptive protocol analysis engine, forming the spatial addressing basis of physical layer multi-tag identification; the asymmetric time division multiple access scheduling mechanism expands the time slice allocation of traditional TDMA to the space-time two-dimensional scheduling domain, realizing parallel communication access control of multiple tags. The deep separation architecture of time domain overlapping signals extracts the physical layer feature vector, solving the signal aliasing problem in dense tag environment; the cross-protocol semantic translation layer establishes a normalization processing pipeline for heterogeneous tag protocols, eliminating the influence of protocol differences of multiple manufacturers' tags on system-level operations. The bidirectional authentication pipeline realizes distributed negotiation of multi-tag keys, and the block chain data aggregation engine guarantees the atomicity of multi-tag operations through the fragmentation-recombination mechanism; the redundancy check matrix is based on the principle of forward error correction coding, and the integrity of the distributed read-write result is reconstructed to form an anti-interference communication closed-loop protection system.

[0067] In summary, the dynamic energy field of the embodiment provides a physical layer multiple access foundation, establishes a spatial logical topology through adaptive protocol analysis, realizes signal separation through parallel demodulation, completes protocol unification through semantic translation, guarantees communication reliability through a security pipeline, and realizes distributed operation collaboration through a data aggregation engine. The embodiment provides a full-stack solution covering the whole process from radio frequency signal processing to application layer data integration, and significantly improves the multi-tag processing capacity and communication reliability of the NFC system. When communicating with an NFC tag, the chip automatically identifies the type of the tag and selects a corresponding protocol for interaction. For example, when a tag conforming to the ISO / IEC 14443 Type A standard is detected, the chip transmits and receives data according to the physical layer and data link layer protocols specified in the standard. The communication process is as follows: first, the chip transmits a 13.56 MHz radio frequency carrier signal to the surrounding space through the activated antenna. When an NFC tag enters the antenna sensing area, the tag obtains energy through electromagnetic induction and is activated. After the tag is activated, it sends its UID (unique identifier) to the chip. After receiving the UID, the chip verifies the accuracy of the data through CRC check and other methods. Subsequently, the chip and the tag exchange data according to the command set specified in the protocol, such as reading the data stored in the tag, writing data to the tag, and other operations. In the data exchange process, Manchester encoding and other methods are used to encode and decode the data to ensure the accuracy and reliability of data transmission.

[0068] Embodiment 2: As shown in the embodiment 1, on the basis of the embodiment 1, the process of driving each antenna unit to exchange data with the tag according to the priority provided by the embodiment of the application comprises the following steps: Figure 3

[0069] S101: Feedback resonance characteristics are processed through multi-dimensional electromagnetic signature decomposition to obtain a medium spectrum characteristic tensor containing resonance frequency deviation and quality factor gradient. The medium spectrum characteristic tensor is processed through a protocol fingerprint convolutional neural network to generate a protocol type probability matrix with spatiotemporal correlation;

[0070] S102: The protocol type probability matrix is processed through near-field beamforming inversion to calculate a spatial distribution map finally outputting a labeled three-dimensional coordinate and protocol cluster mapping relationship. The spatial distribution map is processed through communication entropy weight distribution to obtain an urgency degree and power consumption coefficient evaluation value of each tag node. The evaluation value is processed through a nonlinear time slot planning algorithm to generate a frame structure template with conflict avoidance characteristics;

[0071] S103: The frame structure template is driven through an adaptive beam control interface to execute a hierarchical wake-up and data exchange sequence according to the principle of optimal energy efficiency.

[0072] ​The working principle and beneficial effects of the technical solution are: first, the feedback resonance characteristics are processed by multi-dimensional electromagnetic signature decomposition to obtain a medium spectrum characteristic tensor containing resonance frequency deviation and quality factor gradient; the medium spectrum characteristic tensor is processed by a protocol fingerprint convolutional neural network to generate a protocol type probability matrix with space-time correlation; second, the protocol type probability matrix is calculated by near-field beamforming inversion to finally output a spatial distribution map of the mapping relationship between the labeled three-dimensional coordinates and the protocol cluster; the spatial distribution map is processed by communication entropy weight allocation to obtain the urgency and power consumption coefficient evaluation value of each label node; the evaluation value is processed by a nonlinear time slot planning algorithm to generate a frame structure template with conflict avoidance characteristics; finally, the frame structure template is driven by an adaptive beam control interface to execute a hierarchical wake-up and data exchange sequence according to the energy efficiency optimization principle. The feedback resonance characteristics are converted into a medium spectrum characteristic tensor through multi-dimensional electromagnetic signature decomposition, and the tensor contains resonance frequency deviation and quality factor gradient characteristics; the medium spectrum characteristic tensor is processed by a protocol fingerprint convolutional neural network to output a protocol type probability matrix with space-time correlation, which captures the feature distribution mode of different protocol clusters in the spatial domain through dynamic learning. The protocol type probability matrix is calculated by near-field beamforming inversion to generate a spatial distribution map, which clearly marks the mapping relationship between the three-dimensional coordinates and the protocol cluster; the spatial distribution map is processed by communication entropy weight allocation to quantify the urgency and power consumption coefficient of each label node, forming a dynamic evaluation value; the evaluation value is input into a nonlinear time slot planning algorithm to output a frame structure template with conflict avoidance characteristics, which integrates time domain resource efficiency optimization and spatial interference minimization constraints. The frame structure template is parsed by an adaptive beam control interface and converted into a hierarchical wake-up sequence of multiple antenna units; the wake-up sequence dynamically adjusts the radiation mode of each antenna according to the energy efficiency optimization principle, realizes a high-concurrency label data exchange process under the premise of maintaining a stable three-dimensional energy field, and follows the physical characteristics reflected by the medium spectrum characteristic tensor and the communication priority determined by the protocol type probability matrix.

[0073] In the process of generating a frame structure template with conflict avoidance characteristics by a nonlinear time slot planning algorithm based on the evaluation value provided in Embodiment 2, the following steps are included:

[0074] S1021: The protocol type probability matrix is processed by field strength gradient reverse mapping to obtain an interference feature set containing multi-dimensional phase parameters; the interference feature set is processed by vector superposition to generate an electromagnetic field strength distribution model with spatial resolution; the electromagnetic field strength distribution model is processed by motion trajectory compensation to obtain a three-dimensional field strength topology map eliminating relative displacement errors; and the three-dimensional field strength topology map is converted by coordinate mapping to generate a dynamic field strength distribution map containing spatial position and protocol type at the same time.

[0075] S1022: The dynamic field intensity distribution map is subjected to energy spectrum density clustering processing to obtain a protocol cluster distribution feature vector, and the distribution feature vector is subjected to adaptive weight distribution to generate a communication entropy optimization scheme based on energy utilization efficiency;

[0076] S1023: The communication entropy optimization scheme is subjected to multi-objective decision processing to obtain a node priority evaluation parameter, and an evaluation value matrix of emergency degree and power consumption coefficient containing timeliness constraints is obtained by state transition from the evaluation parameter; the evaluation value matrix is subjected to chaotic sequence generation processing to obtain a time slot allocation basic sequence with pseudo-random characteristics, and the basic sequence is subjected to window constraint optimization to generate a variable frame structure template containing a conflict awareness mechanism.

[0077] The working principle and beneficial effects of the above technical solution are as follows: firstly, the protocol type probability matrix is subjected to field intensity gradient reverse mapping processing to obtain an interference feature set containing multi-dimensional phase parameters, and the interference feature set is subjected to vector superposition to generate an electromagnetic field intensity distribution model with spatial resolution; the electromagnetic field intensity distribution model is subjected to motion trajectory compensation processing to obtain a three-dimensional field intensity topology map eliminating relative displacement errors, and the three-dimensional field intensity topology map is subjected to coordinate mapping conversion to generate a dynamic field intensity distribution map containing spatial position and protocol type; secondly, the dynamic field intensity distribution map is subjected to energy spectrum density clustering processing to obtain a protocol cluster distribution feature vector, and the distribution feature vector is subjected to adaptive weight distribution to generate a communication entropy optimization scheme based on energy utilization efficiency; finally, the communication entropy optimization scheme is subjected to multi-objective decision processing to obtain a node priority evaluation parameter, and an evaluation value matrix of emergency degree and power consumption coefficient containing timeliness constraints is obtained by state transition from the evaluation parameter; the evaluation value matrix is subjected to chaotic sequence generation processing to obtain a time slot allocation basic sequence with pseudo-random characteristics, and the basic sequence is subjected to window constraint optimization to generate a variable frame structure template containing a conflict awareness mechanism. The multi-dimensional radio frequency feature analysis and dynamic field intensity modeling of the above scheme: through field intensity gradient reverse mapping and vector superposition processing, the protocol type probability matrix is converted into an electromagnetic field intensity distribution model with spatial resolution; and then through motion trajectory compensation and coordinate mapping conversion, a three-dimensional dynamic field intensity distribution map accurately reflecting the tag distribution is generated, ensuring accurate modeling of the radio frequency environment. Protocol cluster energy optimization and adaptive scheduling: the dynamic field intensity distribution map is subjected to energy spectrum density clustering to extract a protocol cluster feature vector, and a communication entropy optimization scheme is generated by combining adaptive weight distribution; the allocation of radio frequency resources is efficiently matched with the protocol characteristics and energy demand of the tag in a multi-protocol environment, improving the energy utilization efficiency in a multi-protocol environment. Conflict avoidance and time slot intelligent planning: the communication entropy optimization scheme is subjected to multi-objective decision processing to output a node priority evaluation parameter, and an evaluation value matrix is formed by state transition; and finally, a variable frame structure template is constructed by combining chaotic sequence generation and window constraint optimization, ensuring that the time slot allocation has dynamic conflict avoidance capability while meeting timeliness and power consumption constraints.

[0078] In summary, the embodiment realizes closed-loop optimization from protocol identification to dynamic energy field regulation, to intelligent time slot scheduling, and finally achieves high concurrency, low interference, and energy-efficient radio frequency identification and data exchange in a multi-tag environment.

[0079] In the embodiment 3, the embodiment of the application provides a process for generating a communication entropy optimization scheme based on energy utilization efficiency, which comprises the following steps:

[0080] S10221: The dynamic field strength distribution map is subjected to spatial energy differential operation processing to obtain a field strength gradient field reflecting the energy distribution change rate, and the field strength gradient field is subjected to regional energy aggregation degree analysis to generate protocol sensitive area division with obvious energy concentration characteristics;

[0081] S10222: The protocol sensitive area division is subjected to energy threshold determination processing to obtain a set of minimum energy boundary values required for maintaining communication in each area, and the set of minimum energy boundary values is subjected to electromagnetic wave interference effect analysis to generate an energy multiplexing efficiency parameter reflecting the multi-region energy superposition effect;

[0082] S10223: The energy multiplexing efficiency parameter is subjected to multi-round boundary condition adjustment processing to obtain a minimum energy distribution scheme meeting the energy requirements of each region, and the minimum energy distribution scheme is subjected to energy efficiency balance operation to generate a weight configuration matrix realizing overall energy optimal distribution;

[0083] S10224: The weight configuration matrix is subjected to communication capacity maximization processing to obtain an energy scheduling strategy ensuring simultaneous communication of multiple protocols, and the energy scheduling strategy is subjected to real-time efficiency monitoring and correction to generate a communication optimization scheme finally reaching the optimal state of energy utilization.

[0084] The working principle and beneficial effects of the technical solution are as follows: first, the dynamic field intensity distribution map is subjected to spatial energy differential operation processing to obtain a field intensity gradient field reflecting the energy distribution change rate, and the field intensity gradient field is subjected to regional energy aggregation degree analysis to generate a protocol sensitive area division with obvious energy concentration characteristics; second, the protocol sensitive area division is subjected to energy threshold determination processing to obtain a minimum energy boundary value set required for each area to maintain communication, and the minimum energy boundary value set is subjected to electromagnetic wave interference effect analysis to generate an energy multiplexing efficiency parameter reflecting the multi-region energy superposition effect; then, the energy multiplexing efficiency parameter is subjected to multi-round boundary condition adjustment processing to obtain a minimum energy allocation scheme meeting the energy demand of each region, and the minimum energy allocation scheme is subjected to energy efficiency balance operation to generate a weight configuration matrix realizing optimal overall energy distribution; finally, the weight configuration matrix is subjected to communication capacity maximization processing to obtain an energy scheduling strategy ensuring simultaneous communication of multiple protocols, and the energy scheduling strategy is subjected to real-time efficiency monitoring and correction to generate a communication optimization scheme finally reaching an optimal energy utilization state. The above scheme identifies energy aggregation areas by analyzing electromagnetic field energy distribution change characteristics, calculates energy superposition effect by using electromagnetic wave interference characteristics, finds a minimum energy allocation scheme by using multi-round boundary adjustment, and formulates an energy scheduling strategy based on the maximum communication capacity principle, thereby realizing energy optimized allocation based on the physical nature of electromagnetic fields.

[0085] Embodiment 5: As shown in the embodiment 1, on the basis of the embodiment 1, the process of extracting the physical layer feature vector of each tag provided by the embodiment of the application comprises the following steps: Figure 4

[0086] S201: The original response set uses the tag type prior information extracted from the spatial distribution map to construct a deep convolutional separation base network for frequency-spatial joint perception, and performs hierarchical feature decoupling on the time domain overlapping signals mixed in the original response set; the decoupling result generates a group of intermediate signal segment clusters with spatiotemporal resolution characteristics;

[0087] S202: The intermediate signal segment cluster dynamically allocates attention weights according to the tag communication priority sequence provided by the asymmetric time division multiple access scheduling mechanism to selectively strengthen and weaken the segment cluster; the strengthened segment cluster extracts the transient resonance mode and steady-state oscillation profile of each tag through a cross-scale correlation mining engine;

[0088] ​S203: The transient resonance mode and the steady-state oscillation profile are processed by a double-flow feature encoder to generate a time-varying feature sequence and a frequency domain representation vector, respectively; the two types of features are cross-mapped and complementarily enhanced by a nonlinear collaborative fusion module to form a preliminary label physical layer signature; the preliminary label physical layer signature is compared with the pre-stored differential energy distribution mode in the dynamic energy field generation stage to eliminate the pseudo feature components caused by multipath interference; and the checked preliminary label physical layer signature is extracted by a multi-dimensional feature distillation network to obtain a high-purity physical layer feature vector.

[0089] The working principle and beneficial effects of the above technical solution are as follows: first, the original response set uses the label type prior information extracted from the spatial distribution map to construct a frequency-space joint perception deep convolution separation base network, and the original response set is hierarchically decoupled from the time domain overlap signal; the decoupled result generates a group of intermediate signal segment clusters with space-time resolution characteristics; second, the intermediate signal segment cluster dynamically allocates attention weight according to the label communication priority sequence provided by the asymmetric time division multiple access scheduling mechanism to selectively strengthen and weaken the segment cluster; the strengthened segment cluster extracts the transient resonance mode and the steady-state oscillation profile of each label through a cross-scale correlation mining engine; finally, the transient resonance mode and the steady-state oscillation profile are processed by a double-flow feature encoder to generate a time-varying feature sequence and a frequency domain representation vector; the two types of features are cross-mapped and complementarily enhanced by a nonlinear collaborative fusion module to form a preliminary label physical layer signature; the preliminary label physical layer signature is compared with the pre-stored differential energy distribution mode in the dynamic energy field generation stage to eliminate the pseudo feature components caused by multipath interference; and the checked preliminary label physical layer signature is extracted by a multi-dimensional feature distillation network to obtain a high-purity physical layer feature vector. The above scheme uses a frequency-space joint perception deep convolution separation base network to hierarchically decouple the mixed signals in the original response set, generates intermediate signal segment clusters with space-time resolution characteristics, and ensures the accuracy and anti-interference ability of signal separation. Based on the priority sequence provided by the asymmetric time division multiple access scheduling mechanism, the attention weight is adaptively adjusted to selectively strengthen the key signal segments, and the cross-scale correlation mining engine is used to extract the transient resonance mode and the steady-state oscillation profile, thereby improving the robustness of feature extraction. The time-varying feature sequence and the frequency domain representation vector are cross-mapped by a nonlinear collaborative fusion module to form a preliminary label physical layer signature; and the pre-stored energy distribution mode is used to eliminate the multipath interference pseudo features, thereby ensuring the high credibility of the features. Finally, a multi-dimensional feature distillation network is used for further optimization to extract a high-purity physical layer feature vector, which provides high-precision input for subsequent signal recognition and label discrimination.

[0090] In summary, the embodiment realizes the complete extraction of high-purity feature vectors from mixed signal decoupling to dynamic weight optimization, feature fusion and interference suppression, thereby ensuring the accurate characterization of physical layer features in a complex radio frequency environment.

[0091] Embodiment 6: Based on embodiment 5, the process of hierarchical feature decoupling of the time domain overlapping signals in the original response set provided by the application embodiment contains the following steps:

[0092] S2011: The resonance fingerprints of different label types coded in the spatial distribution map and the estimated spatial orientation are input into the topology generator; a frequency-space search template defining the initial probe direction of the network is output by the topology generator; a deep convolutional separation base network construction unit initializes a group of tunable filter units according to the feature frequency interval of different label types in the frequency-space search template; the bandwidth and center frequency of the tunable filter unit group are dynamically shaped according to the energy response characteristics of the corresponding label type in the frequency-space template; the first processing layer of the base network, called the spectrum sensing layer, is formed by the initialized tunable filter unit group;

[0093] S2012: The spectrum sensing layer processes the original response set to generate a group of primary response signals filtered of out-of-band noise; the primary response signals are sent to the spatial feature conjugation layer, which convolves the signal of each filter channel with the spatial probability distribution of the corresponding label type extracted from the spatial distribution map, strengthens the signal components from the most likely orientation of the label, and suppresses the interference signals of the same frequency but different orientations; the primary response feature plane carrying both frequency and spatial domain labels is output by the spatial feature conjugation layer;

[0094] S2013: The primary response feature plane is then input into the hierarchical decoupling engine, which is composed of multiple cascaded signal disentangling modules; the first signal disentangling module analyzes the primary response feature plane, identifies the strong signal components with significant energy and distinct features, and generates their corresponding signal masks; the first layer of strong signal components identified by the signal mask is subtracted from the primary response feature plane to obtain a residual response plane;

[0095] S2014: The residual response plane is sent to the second signal disentangling, from which the signal components with weaker energy or higher feature overlap are separated; it uses the next priority label information predicted from the asymmetric time division multiple access scheduling mechanism to adjust its internal parameters and focus on extracting signals from a specific spatial orientation and frequency range; the second group of signal components and the updated residual response plane are output;

[0096] S2015: The iterative subtraction and focusing process continues until all label signal components predicted by the spatial distribution map are preliminarily separated or the residual response is below the predetermined threshold; finally, the signal components output by all hierarchical decoupling engines are recombined and aligned to generate a group of intermediate signal segment clusters with spatial and temporal resolution characteristics.

[0097] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the resonant fingerprints and estimated spatial orientations of different tag types are encoded in the spatial distribution map and input to the topology generator; the topology generator outputs a frequency-space search template that defines the initial exploration direction of the network; the base network construction units are separated by deep convolution according to the characteristic frequency ranges of different tag types in the frequency-space search template; a set of tunable filter units are initialized, and the bandwidth and center frequency are dynamically shaped according to the energy response characteristics of the corresponding tag type in the frequency-space template; the initialized tunable filter unit group forms the first-level processing layer of the base network, called the spectrum sensing layer; the spectrum sensing layer processes the original response set and generates a set of primary response signals that filter out out-of-band noise; the primary response signals are sent to the spatial feature concatenation layer, where the signal of each filter channel is convolved with the spatial probability distribution of the corresponding tag type extracted from the spatial distribution map, strengthening the signal components from the most likely location of the tag and suppressing interference signals of the same frequency but different locations; the spatial feature concatenation layer outputs a set of signals that simultaneously carry frequency and spatial domain information. The primary response feature plane is labeled with domains. This primary response feature plane is then input to a hierarchical decoupling engine, which consists of multiple cascaded signal deentanglement modules. The first signal deentanglement module analyzes the primary response feature plane, identifies strong signal components with significant energy and distinct features, and generates their corresponding signal masks. The strong signal components identified in the first layer are subtracted from the primary response feature plane using the signal masks, resulting in a residual response plane. This residual response plane is then fed into a second signal deentanglement module, which separates signal components with weaker energy or higher feature overlap. This module utilizes the next priority label information predicted from the asymmetric time-division multiple access scheduling mechanism to adjust its internal parameters, focusing on extracting signals from specific spatial orientations and frequency ranges. A second set of signal components and an updated residual response plane are output. Finally, the iterative subtraction and focusing process continues until all labeled signal components predicted by the spatial distribution map are initially separated or the residual response is below a predetermined threshold. Ultimately, the signal components output by all hierarchical decoupling engines are recombined and aligned to generate a cluster of intermediate signal fragments with spatiotemporal resolution characteristics. The above scheme is not a fixed, universal separation network, but a dynamic processing structure with clear physical orientation shaped in real time by the current spatial distribution map. It deeply integrates frequency filtering in the radio frequency domain, orientation screening in the spatial domain, and iterative decomposition in the signal processing layer, so that the separation capability of deep learning is effectively guided and constrained within the solution space determined by the front-end physical state, thereby achieving higher precision and efficiency in feature decoupling.

[0098] Example 7: As Figure 5 As shown, based on Example 1, the process for generating an anti-interference communication result set provided in this embodiment of the invention includes the following steps:

[0099] S301: Extract the cryptographic hash values of the physical layer feature vectors of each tag from the unified structured instruction set, and combine the spatial distribution map to generate a set of temporary identity credentials with spatial correlation;

[0100] S302: The temporary identity credential set and the physical layer feature vector are processed by the dynamic physically unclonable function engine. The engine generates a dynamic challenge sequence according to the historical state parameters of the dynamic energy field, and generates a one-time variable encryption authentication evidence stream. After the encryption authentication evidence stream passes through the consensus verification based on fuzzy matching, the asynchronous key agreement mechanism is triggered, and the initial link of the block chain data aggregation engine is used to interleave and aggregate the key shares of each tag, forming a shared master key chain and deriving an independent secure channel;

[0101] Among them, the engine integrates the physical layer feature vectors of the tags, such as radio frequency fingerprints, hardware process deviations and other inherent characteristics as entropy sources, and combines the historical state sequence of the dynamic energy field, such as channel state information, environmental noise and other time-varying parameters, to generate a dynamic challenge-response pair through a configurable chaotic mapping algorithm; The engine uses a lightweight cryptography module inside to realize the one-way transformation of the response value, ensuring that the encryption evidence stream generated in each authentication process has unpredictability and unclonability, while supporting a state synchronization mechanism based on historical parameters;

[0102] S303: The original operation results generated by the distributed read-write operation of the independent secure channel are processed by the space-time encoder to embed the instantaneous state of the dynamic energy field and the real-time spatial coordinates of the tag at the time of the operation, and output the original result vector set with complete space-time marks. The original result vector set is processed by the redundancy check matrix constructor to dynamically generate an optimal check dimension according to the number of communication channels, spatial density and historical interference mode, and construct an anti-tamper multi-dimensional check tensor that introduces the shared master key chain as a randomization seed;

[0103] S304: The original result vector set with space-time marks is executed by the multi-dimensional check tensor to generate a strengthened result set with strong encryption check codes. The strengthened result set is finally processed by the consistency reconstructor to perform cross-validation and error correction using the anti-tamper multi-dimensional check tensor, and to repair and restore the historical data of the dynamic energy field corresponding to the space-time marks of the data unit that fails the check, and aggregate to generate a high-integrity anti-interference communication result set.

[0104] The working principle and beneficial effects of the above technical solution are: firstly, the present embodiment first separates the cryptographic hash values of each label physical layer feature vector reserved by the pre-sequence flow from the unified structured instruction set, and generates a set of temporary identity credentials with spatial correlation in combination with the label space topology information provided by the spatial distribution map; secondly, the temporary identity credential set and the physical layer feature vector are processed by the dynamic physically unclonable function engine, which generates a dynamic challenge sequence according to the historical state parameters of the dynamic energy field to generate a one-time variable encrypted authentication evidence stream; after the encrypted authentication evidence stream passes through the consensus verification based on fuzzy matching, the asynchronous key agreement mechanism is triggered, the initial link of the block chain data aggregation engine is used to interleave and aggregate the key shares of each label, forming a shared master key chain and deriving an independent secure channel; then the original operation results generated by the distributed read-write operation of the independent secure channel are processed by the space-time encoder, embedding the instantaneous state of the dynamic energy field and the real-time spatial coordinates of the label at the time of the operation, and outputting the original result vector set with complete space-time marks; the original result vector set is processed by the redundancy check matrix constructor, an optimal check dimension is dynamically generated according to the number of communication channels, the spatial density and the historical interference mode, and an anti-tamper multi-dimensional check tensor is constructed, which introduces the shared master key chain as a randomization seed; finally, the original result vector set with space-time marks is executed by the multi-dimensional check tensor to generate a strengthened result set attached with strong encryption check codes; the strengthened result set is finally processed by the consistency reconstructor, which uses the check tensor for cross-validation and error correction, and calls the dynamic energy field historical data corresponding to the space-time mark of the data unit for repair and restoration when the check fails, and aggregates to generate an anti-interference communication result set with high integrity. The above scheme embodies the technical fusion of multi-layer security protection and dynamic self-adaptation; by combining the cryptographic hash of the physical layer feature vector with the spatial topology information, an identity credential set with spatial constraints is constructed; the dynamic physically unclonable function engine introduces the dynamic energy field parameter to generate a time-varying challenge sequence, realizing the dynamic binding of device authentication and channel characteristics; a shared master key chain is formed through asynchronous key agreement to ensure that a key isolated channel based on physical layer randomness is established between communication entities. The original operation result is embedded with the dynamic energy field state and real-time coordinates by the space-time encoder to form a data vector with space-time traceability; by dynamically constructing a redundancy check matrix, an anti-tampering check tensor is generated by taking the shared master key chain as a randomization seed, realizing data integrity protection and strong correlation of channel physical characteristics. When the multi-dimensional check tensor performs parallel redundancy calculation, the check code generation process is constrained by the master key chain and the space-time mark; the consistency reconstructor realizes cross-validation across dimensions through the check tensor, and repairs the data using the historical energy field data indexed by the space-time mark, forming an elastic recovery capability against instantaneous interference.

[0105] In summary, the embodiment realizes the following core features through four layers of protection of physical layer feature binding, dynamic key derivation, space-time signature embedding, and multi-dimensional redundancy check: dynamic association of communication entity authentication and physical environment parameters, time and space verifiable data integrity protection, adaptive optimization of check mechanism according to channel state, and interference detection and repair based on multi-dimensional consensus mechanism. The communication system significantly improves the protection capability against physical layer interference, man-in-the-middle attack, data tampering and other threats, while maintaining dynamic adaptability of topology.

[0106] Embodiment 8: Based on embodiment 7, the application provides a process for constructing an anti-tamper multi-dimensional check tensor that introduces a shared master key chain as a randomization seed, including the following steps:

[0107] S3031: The number of communication channels this time, the spatial density of the label derived from the spatial distribution map, and the statistical features of the historical interference mode extracted from the historical anti-interference communication result set are input into the check strategy fusion program; the spatial density and the historical interference mode are convolved to generate a spatial weighted interference probability distribution map; the spatial weighted interference probability distribution map is multiplied by the number of communication channels to calculate the minimum redundancy information required to offset the expected interference of this communication; the minimum redundancy information is subjected to a nonlinear transformation to output a dynamic optimal check dimension value;

[0108] S3032: Create a null-based tensor with the dynamic optimal check dimension value as the order; the coordinate offset derived from the shared master key chain is used to initialize the scrambling of each initial element position of the null-based tensor; an initial tensor framework with cryptographic chaos characteristics is formed from the scrambled null-based tensor;

[0109] S3033: Split the key chain into multiple segments, each segment controls the polynomial coefficient of a different section of the null-based tensor; perform modulo operation with the metadata of the original result vector set with space-time signature, the result determines the specific filling algorithm of each cell in the initial tensor framework, which is parity check, cyclic redundancy check or Reed-Solomon encoding variant; an anti-tamper multi-dimensional check tensor that is strongly bound to the session key of this time and has a unique structure is constructed.

[0110] The working principle and beneficial effects of the technical solution are as follows: firstly, the number of communication channels this time, the spatial density of the label derived from the spatial distribution map, and the statistical characteristics of the historical interference mode extracted from the historical anti-interference communication result set are input into the verification strategy fusion program; the spatial density and the historical interference mode are convolved to generate a spatial weighted interference probability distribution map; the spatial weighted interference probability distribution map is multiplied by the number of communication channels to calculate the minimum amount of redundant information required to offset the expected interference of this communication; the minimum amount of redundant information is subjected to a nonlinear transformation to output a dynamic optimal verification dimension value; secondly, an empty base tensor with the dynamic optimal verification dimension value as the order is created; each initial element position of the empty base tensor is initialized and scrambled by the coordinate offset derived from the shared master key chain; an initial tensor framework with a cryptographic chaos characteristic is formed from the scrambled empty base tensor; finally, the key chain is split into multiple segments, and each segment controls the polynomial coefficient of a different section of the empty base tensor; the metadata of the original result vector set with the space-time mark is subjected to a modulo operation, and the result determines that the specific filling algorithm of each cell in the initial tensor framework is parity check, cyclic redundancy check, or Reed-Solomon encoding variant; an anti-tamper multi-dimensional verification tensor that is strongly bound to the session key and has a unique structure is constructed. The dimension of the verification redundancy is no longer fixed or empirical, but a dynamic decision-making result calculated from the real-time physical environment (spatial density) and historical communication quality (interference mode) of this communication; at the same time, the microstructure of the entire verification tensor is deeply penetrated and controlled by the session master key, so that the verification bit itself also has encryption characteristics. Any tampering with the data will cause the verification calculation to fail in the key-controlled chaotic operation, thereby achieving anti-interference and anti-tamper capabilities far superior to traditional methods.

[0111] In the embodiment 8, the process that the generated polynomial coefficient is subjected to a modulo operation with the metadata of the original result vector set with the space-time mark includes the following steps:

[0112] S30331: The spatial coordinate index of the target cell in the initial tensor framework is input into the coordinate-key obfuscator together with a specific key segment of the shared master key chain; the coordinate-key obfuscator performs XOR and cyclic shift operations on the coordinate value and the key segment to generate a temporary cell-specific entropy value; at the same time, the operation sequence identifier, the precise timestamp, and the spatial coordinate hash value corresponding to the data unit verified by the cell are extracted from the metadata of the original result vector set with the space-time mark; and an operation context token strongly related to a specific operation time and place is output.

[0113] S30332: The cell-specific entropy value is concatenated with the context token, and then a different key fragment is used as a selector to extract a byte at a specific position from the concatenated result to generate an intermediate decision seed; the intermediate decision seed is multiplied by the historical bit error rate weight corresponding to the cell space coordinates extracted from the historical interference pattern to generate a unique dynamic decision factor rich in multi-dimensional information;

[0114] S30333: The generated dynamic decision factor is subjected to a modulo operation with a modulus reference value derived from a polynomial coefficient to obtain a normalized algorithm selection index value; the algorithm selection index value is input into an algorithm decision mapping table, the content and size of which are dynamically adjusted by the dynamic optimal check dimension value calculated by the check strategy fusion core; the algorithm decision mapping table outputs a specific algorithm identifier according to the algorithm selection index value, which indicates which one of the parity check, cyclic redundancy check, or Reed-Solomon encoding variant filling algorithm should be used for the cell;

[0115] S30334: The algorithm identifier and the original data content of the current cell are sent to the parameterized algorithm execution unit; a unique check code is calculated for the specific cell, and is filled into the corresponding position of the initial tensor framework to complete the construction of the cell.

[0116] The working principle and beneficial effects of the above technical solution are: firstly, the spatial coordinate index of the target cell in the initial tensor framework is input into the coordinate-key confusion device together with a specific key segment of the shared master key chain; the coordinate-key confusion device performs XOR and cyclic shift operations on the coordinate value and the key segment to generate a temporary cell-specific entropy value; at the same time, the operation sequence identifier, the precise timestamp and the spatial coordinate hash value corresponding to the data unit checked by the cell are extracted from the metadata of the original result vector set with the space-time imprint; an upper and lower context token strongly related to a specific operation time and place is output; secondly, the cell-specific entropy value is spliced with the context token, and then another different key segment is used as a selector to extract the bytes at a specific position from the spliced result to generate an intermediate decision seed; the intermediate decision seed is multiplied with the historical bit error rate weight corresponding to the spatial coordinate of the cell extracted from the historical interference mode to generate a unique dynamic decision factor rich in multi-dimensional information; then the generated dynamic decision factor is subjected to a modulus operation with a modulus reference value derived from a polynomial coefficient to obtain a normalized algorithm selection index value; the algorithm selection index value is input into the algorithm decision mapping table, the content and size of which are dynamically adjusted by the dynamic optimal verification dimension value calculated by the verification strategy fusion core; the algorithm decision mapping table outputs a specific algorithm identifier according to the algorithm selection index value, and the algorithm identifier indicates which one of the parity check, the cyclic redundancy check or the Reed-Solomon encoding variant should be used for the cell; finally, the algorithm identifier and the original data content of the current cell are sent to the parameterized algorithm execution unit; a unique check code is calculated for the specific cell, and is filled into the corresponding position of the initial tensor framework to complete the construction of the cell. The algorithm selection of each verification tensor cell in the above scheme is not pre-specified statically, but is dynamically determined by the spatial position of the cell, the key of this session, the specific space-time background of the data verified by the cell and the historical communication quality. The microstructure of the verification tensor is extremely complex and deeply bound to the context of this communication, so any attempt to tamper with the data or the key will destroy this precise correspondence and be easily detected, achieving strong anti-tampering properties.

[0117] Embodiment 10: Based on embodiment 9, the process of the algorithm decision mapping table outputting a specific algorithm identifier according to the algorithm selection index value provided by the present embodiment comprises the following steps:

[0118] S303331: Check the dynamic optimal verification dimension value calculated by the policy fusion core to perform square operation to obtain a basic mapping space size, define the maximum number of entries that the algorithm decision mapping table can theoretically accommodate; perform bitwise AND operation between the basic mapping space size and a fixed key segment of the shared master key chain to generate an actual mapping table size value, and initialize an empty, to-be-filled mapping table skeleton by the actual mapping table size value;

[0119] S303332: Divide the remaining part of the key chain into multiple cryptographic slices with different lengths, the first slice is used to generate an initial algorithm type distribution weight vector, which defines the preferred proportion of each verification algorithm in the ideal interference-free case; the second and subsequent slices are used to create a nonlinear disturbance program, taking the algorithm selection index value as input, but the disturbance parameters in the program are completely controlled by the key slice; output an original mapping table whose content is preliminarily shaped by the key but has not yet been associated with the current environment by the mapping logic filler;

[0120] S303333: The original mapping table and the error code feature vector for the current spatial coordinates extracted from the historical interference mode are sent to the environment adaptive tuner; the environment adaptive tuner dynamically adjusts the distribution density of the corresponding algorithm identifier in the original mapping table according to the frequency of each type of error in the error code feature vector; in the area where the historical burst error is high, increase the mapping probability of Reed-Solomon encoding variant algorithm; generate an adaptive mapping table optimized by environmental experience;

[0121] S303334: The normalized algorithm selection index value is first processed by the nonlinear disturbance program controlled by the key to generate a final, encrypted and confused lookup key value, which is addressed in the environment experience optimized adaptive mapping table, adopts a fuzzy matching mechanism based on key value range, and the matching interval threshold of the fuzzy matching mechanism is dynamically adjusted by the last few digits of the dynamic optimal verification dimension value; output the specific algorithm identifier that determines the cell by the fuzzy matching mechanism.

[0122] The working principle and beneficial effects of the technical solution are: the embodiment first performs square operation on the dynamic optimal verification dimension value calculated by the strategy fusion core to obtain a basic mapping space size, and defines the maximum number of entries that the algorithm decision mapping table can theoretically accommodate; the basic mapping space size and a fixed key segment of the shared master key chain are subjected to bitwise AND operation to generate an actual mapping table size value, and an empty mapping table skeleton to be filled is initialized by the actual mapping table size value; secondly, the remaining part of the key chain is divided into a plurality of cryptographic slices with different lengths, the first slice is used to generate an initial algorithm type distribution weight vector, and the preferred proportion of each verification algorithm under ideal interference-free conditions is defined; the second and subsequent slices are used to create a nonlinear disturbance program, taking the algorithm selection index value as the input, but the disturbance parameters in the program are completely controlled by the key slice; an original mapping table whose content is preliminarily shaped by the key but has not yet been associated with the current environment is output by the mapping logic filler; then the original mapping table and the error code feature vector extracted from the historical interference mode and directed to the current space coordinates are sent to the environment adaptive tuner; the environment adaptive tuner dynamically adjusts the distribution density of the corresponding algorithm identifier in the original mapping table according to the frequency of each type of error in the error code feature vector; in the area where the historical sudden error is high, the mapping probability of the Reed-Solomon encoding variant algorithm is increased; an environment experience optimized adaptive mapping table is generated; finally, the normalized algorithm selection index value is first subjected to the nonlinear disturbance program controlled by the key to generate a final encrypted and confused lookup key value, and then is addressed in the environment experience optimized adaptive mapping table; a fuzzy matching mechanism based on the key value range is adopted, and the matching interval threshold is dynamically adjusted by the last few digits of the dynamic optimal verification dimension value; the specific algorithm identifier that determines the cell is output by the fuzzy matching mechanism. The algorithm decision mapping table of the above scheme is not a static and unchangeable hardware circuit or software lookup table, but a temporary logical structure dynamically generated and tuned by the key, communication quality requirement and historical interference experience in each communication session; so that the attacker cannot predict its behavior through reverse engineering, greatly enhancing the confidentiality and anti-analysis ability of the entire verification process.

[0123] Embodiment 11: Based on embodiment 10, the process of the fuzzy matching mechanism based on the key value range provided by the application embodiment comprises the following steps:

[0124] S3033341: The last few digits of the dynamic optimal verification dimension value are processed by the numerical feature extractor to separate the parity characteristics and prime factor distribution characteristics to form an initial threshold modulation vector; the initial threshold modulation vector and the randomization factor from the shared master key chain are jointly input into the threshold variation engine to generate a reference floating threshold value through nonlinear transformation;

[0125] S3033342: the benchmark floating threshold is coupled with a current load factor of the adaptive mapping table optimized by environmental experience, wherein the load factor reflects a real-time distribution state of each algorithm identifier in the mapping table; the coupling operation generates a dynamic range radius; the dynamic range radius is added or subtracted with the encrypted and confused lookup key value to determine an upper bound and a lower bound of fuzzy matching, forming a dynamic matching window;

[0126] S3033343: all entries in the dynamic matching window enter a weight evaluation stage, and a spatial error code correlation coefficient extracted from a historical interference mode is used as a weighting factor; the weighting factor is convoluted with an inherent priority of each entry to generate a candidate entry confidence sequence; the confidence sequence is subjected to peak detection and continuity analysis to screen out an optimal matching candidate set;

[0127] S3033344: the optimal matching candidate set adopts a nearest neighbor priority principle based on time decay, and combines a numerical distribution feature of the lookup key value to output a determined algorithm identifier from the optimal matching candidate set.

[0128] The working principle and beneficial effects of the above technical solution are as follows: firstly, the last few digits of the dynamically optimal check dimension value are processed by a numerical feature extractor to separate the parity characteristics and the prime factor distribution features, forming an initial threshold modulation vector; the initial threshold modulation vector and a randomization factor from the shared master key chain are jointly input into a threshold variation engine to generate a benchmark floating threshold through nonlinear transformation; secondly, the benchmark floating threshold is coupled with a current load factor of the adaptive mapping table optimized by environmental experience, wherein the load factor reflects a real-time distribution state of each algorithm identifier in the mapping table; the coupling operation generates a dynamic range radius; the dynamic range radius is added or subtracted with the encrypted and confused lookup key value to determine an upper bound and a lower bound of fuzzy matching, forming a dynamic matching window; then, all entries in the dynamic matching window enter a weight evaluation stage, and a spatial error code correlation coefficient extracted from a historical interference mode is used as a weighting factor; the weighting factor is convoluted with an inherent priority of each entry to generate a candidate entry confidence sequence; the confidence sequence is subjected to peak detection and continuity analysis to screen out an optimal matching candidate set; finally, the optimal matching candidate set adopts a nearest neighbor priority principle based on time decay, and combines a numerical distribution feature of the lookup key value to output a determined algorithm identifier from the optimal matching candidate set. The above scheme realizes adaptive adjustment of the threshold according to the system running state, avoiding the problem of fixed matching sensitivity caused by the static threshold. The matching range can be automatically contracted or expanded according to parameters such as system load pressure and key value distribution density, balancing query accuracy and efficiency. The influence of high-frequency interference modes on the matching result is effectively suppressed, and the robustness under abnormal conditions is improved. Misjudgment caused by single matching fluctuation is avoided; through parameter coupling and data flow in series, elastic range matching under key protection, stable weight calculation in a noisy environment, and optimal decision output under time-varying conditions are realized.

[0129] Embodiment 12: On the basis of Embodiment 11, the process of outputting the determined algorithm identifier from the optimal matching candidate set provided by the application embodiment comprises the following steps:

[0130] S30333441: The optimal matching candidate set uses the time stamp information of the spatial error code correlation coefficient extracted from the historical interference mode to obtain the interval of the historical decision time corresponding to each candidate entry from the current time; the time interval is transformed by a negative exponential function to generate a time decay factor sequence;

[0131] S30333442: The time decay factor sequence and the candidate entry confidence sequence are weighted and fused, wherein the time decay factor is used as a weight coefficient to perform point multiplication operation with the confidence; the point multiplication operation produces a time-sensitive confidence score; the time-sensitive confidence score is normalized to form a priority sequence with time-sensitive characteristics;

[0132] At the same time, the numerical distribution characteristics of the encrypted and confused lookup key value are processed by the distribution analyzer to extract the first derivative and second derivative characteristics of the numerical density function; the derivative characteristics generate a numerical distribution stability index; the numerical distribution stability index and the priority sequence are jointly input into the neighborhood optimization program, and the arrangement order of each candidate entry in the priority sequence is adjusted according to the stability index, the weight of the nearest neighbor principle is enhanced for the numerical distribution area with lower stability, and the original priority order is maintained for the area with higher stability;

[0133] S30333443: The candidate set adjusted by the neighborhood optimization program uses a proximity measurement method based on Mahalanobis distance to obtain the comprehensive distance of each candidate entry from the ideal matching point in combination with the numerical distribution stability index; the distance produces a final matching degree score; the final matching degree score is sorted and selected to output the algorithm identifier corresponding to the highest score as the final decision result.

[0134] The working principle and beneficial effects of the technical solution are as follows: firstly, the optimal matching candidate set uses the timestamp information of the spatial error code correlation coefficient extracted from the historical interference mode to obtain the interval between the historical decision time corresponding to each candidate item and the current time; the time interval is transformed by a negative exponential function to generate a time decay factor sequence; secondly, the time decay factor sequence and the candidate item confidence sequence are weighted and fused, wherein the time decay factor is used as a weight coefficient to multiply the confidence; the multiplication operation generates a timeliness confidence score; the timeliness confidence score is normalized to form a priority sequence with time sensitivity characteristics; at the same time, the numerical distribution characteristics of the encrypted and confused lookup key value are processed by the distribution analyzer to extract the first derivative and second derivative characteristics of the numerical density function; the derivative characteristics generate a numerical distribution stability index; the numerical distribution stability index and the priority sequence are jointly input into the neighborhood optimization program, the arrangement order of each candidate item in the priority sequence is adjusted according to the stability index, the weight of the nearest neighbor principle is enhanced for the numerical distribution area with lower stability, and the original priority order is maintained for the area with higher stability; finally, the candidate set adjusted by the neighborhood optimization program uses the proximity measurement method based on Mahalanobis distance to obtain the comprehensive distance between each candidate item and the ideal matching point in combination with the numerical distribution stability index; the distance generates a final matching degree score; the final matching degree score is sorted and selected, and the algorithm identifier corresponding to the highest score is output as the final decision result. The synergistic effect of the time decay factor and the numerical distribution characteristics makes the matching result meet the short-term timeliness requirement and the long-term distribution rule; the derivative characteristic detects the distribution mutation area to automatically adjust the optimization strategy and improve the robustness of the system to non-stationary key value distribution; the application of Mahalanobis distance effectively eliminates the correlation interference between characteristics to ensure the accuracy of proximity evaluation in high-dimensional space; through the cascade operation of time weight fusion, distribution stability analysis and statistical distance calculation, the anti-noise, self-adaptive and time-sensitive algorithm identifier optimization is finally realized.

[0135] Embodiment 13: as shown in Figure 6 and Figure 7 Based on embodiments 1-12, the single-chip extended multiple NFC antenna label provided by the embodiment of the application contains: a first coil 1, a second coil 2, a riveting position 3, a chip 4, and a defective ink dot 5.

[0136] The chip 4 is connected to the first coil 1 and the second coil 2 through a double-parallel circuit to form a redundancy design, and the riveting position 3 realizes the connection of the first coil 1 and the second coil 2 with the pads of the chip 4; the defective ink dot 5 is printed on the test point of the chip 4 and is detected during automatic testing.

[0137] The working principle and beneficial effects of the above technical solution are: the chip 4 of the embodiment connects the first coil 1 and the second coil 2 through an independent circuit, ensuring that any coil can supply power to the chip and transmit data when working; the riveting position 3 serves as a physical fixation and electrical node, reliably connecting the ends of the two coils to the pads of the chip 4 to form a complete loop; during automated testing, the ink dots 5 printed on the chip test points are detected to determine whether the coil parameters (inductance, Q value, etc.) are qualified, and unqualified ones are marked as disabled.

[0138] The embodiment improves reading reliability, the dual-antenna design reduces direction dependence, and expands the effective reading range; enhances structural stability, riveting ensures long-term reliability of mechanical strength and electrical connection; automated quality control, ink dot marking enables rapid sorting of defective products, ensuring consistency upon leaving the factory.

[0139] The embodiment can meet the wide coverage and efficient application requirements of NFC functions in diversified scenarios, each antenna has an independent matching circuit to achieve multi-point sensing; the chip has excellent radio frequency processing capability and flexible interface configuration, laying a solid foundation for multi-antenna expansion; through the designed peripheral circuit and control logic, the chip realizes time-sharing multiplexing and cooperative work of multiple NFC antennas made of aluminum etching process.

[0140] The tag packaging method of the two coils and one chip of the embodiment realizes the use scenario of multi-pair multi-point reading from the aspects of linear design, scheme logic, product shape, and use scenario, effectively solving the problems of multiple tags, high cost, and stable management of consumable data collection.

[0141] The NFC antenna of the embodiment is made of aluminum etching process, and a specific shape of aluminum coil antenna is formed on an insulating substrate through precise processes such as photoetching and etching; aluminum has good conductivity and cost performance, and the etching process can accurately control the shape, line width, and number of turns of the antenna to meet the requirements of different application scenarios for antenna performance. For example, for scenarios that require a larger sensing range, an antenna with more turns and thicker wire diameter can be designed; for applications with limited space, a compact planar spiral antenna structure is used. The impedance matching circuit of the antenna uses an LC resonance network, which adjusts the capacitance and inductance values to achieve good matching between the antenna and the chip output impedance at a frequency of 13.56 MHz, improving signal transmission efficiency. The chip, as the core of the system, integrates a complete NFC protocol stack inside, supports ISO / IEC14443A standard protocol, has a working frequency of 13.56 MHz, and has low power consumption characteristics, suitable for long-time running application scenarios. The chip has multiple general-purpose input-output pins (GPIO) and SPI communication interfaces, facilitating data interaction and control signal transmission with external circuits.

[0142] The product use scenarios of the embodiment are:

[0143] 1. Intelligent packaging and anti-counterfeiting traceability:

[0144] Scenario description: Deploy antennas on multiple positions (such as bottle caps, bottle bodies, and inner sides of packaging boxes) of packaging boxes / bottle bodies of high-end goods (such as wine and luxury goods). A single chip controls the cooperative work of the antennas. Consumers can read product traceability information by approaching any position with a mobile phone. Value: Solve the identification difficulty caused by hidden position or angle of traditional single-antenna tag; at the same time, improve the security of anti-counterfeiting through multi-antenna cooperative verification, such as different antennas corresponding to different encrypted information, which need to be verified at the same time.

[0145] 2. 3D printing consumable anti-counterfeiting management:

[0146] The whole life cycle information of the product from raw material procurement, production and processing, warehousing and logistics to sales terminal can be stored in the chip or the cloud database associated with the chip in an encrypted manner. The data in the chip can be encrypted by using advanced encryption technology such as AES encryption algorithm to protect the stored product information from being tampered maliciously during transmission and storage.

[0147] Embodiment 14: On the basis of embodiments 1-13, the production process of a single chip extending multiple NFC antenna tags provided by the present application comprises the following steps:

[0148] Step one: the blank flexible substrate is subjected to surface cleaning and plasma activation treatment to obtain a pretreated substrate with uniform surface energy;

[0149] Step two: the pretreated substrate is subjected to a screen printing conductive silver paste or etching copper foil process to obtain an array pattern containing multiple NFC antenna units, and after high-temperature curing or chemical etching post-treatment, a stable conductive antenna network layer is obtained;

[0150] Step three: the antenna network layer is positioned to connect a single NFC chip to the antenna unit through conductive adhesive dispensing or flip-chip bonding process to obtain a primary composite; the primary composite is subjected to heat pressing curing or reflow soldering process to obtain a chip-antenna module with stable electrical performance;

[0151] Step four: the chip-antenna module is subjected to lamination process of covering PET protective film or injection molding epoxy resin to obtain a semi-finished product with a protective structure; the semi-finished product is subjected to die cutting or laser cutting process to obtain independent label units;

[0152] Step five: the label units are subjected to radio frequency performance test screening, and the qualified products enter data burning equipment to write individualized information to obtain identifiable intelligent labels; the intelligent labels are subjected to appearance quality inspection and impedance matching debugging to finally obtain NFC antenna tag finished products meeting industrial standards.

[0153] The working principle and beneficial effects of the technical solution are as follows: the antenna of the embodiment is made by an aluminum etching process, and a specific shape of the aluminum coil antenna is formed on an insulating substrate (such as a polyimide PI film) through precise processes such as photoetching and etching. The aluminum material has good conductivity and cost performance, and the etching process can accurately control the shape, line width and number of turns of the antenna to meet the requirements of different application scenarios for the performance of the antenna.

[0154] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the equivalent technology of the present application, the present application also intends to include these modifications and variations.

Claims

1. A method for extending communication between multiple NFC antenna tags using a single chip, characterized in that, Comprising the following steps: The chip generates a dynamic energy field in three-dimensional space through a phase-adjustable multi-path radio frequency unit, so that multiple tags entering the sensing area simultaneously obtain differentiated energy distribution and feedback resonance characteristics; The spatial distribution map of the tag type is generated by processing the feedback resonance characteristics through an adaptive protocol analysis engine, and the spatial distribution map drives each antenna unit to exchange data with the tag according to the priority through an asymmetric time division multiple access scheduling mechanism; The dynamic energy field is captured through tag resonance feedback to obtain an original response set containing time domain overlapping signals, and the original response set is extracted through parallel demodulation based on deep learning signal separation to obtain the physical layer feature vector of each tag, which is converted into a unified structured instruction set through cross-protocol semantic translation; The structured instruction set is processed through a bidirectional authentication pipeline to complete the multi-tag security key negotiation, and the negotiated security channel is executed through a block chain data aggregation engine to perform distributed read-write operations, and the operation result is reconstructed through a redundancy check matrix to finally generate an anti-interference communication result set; The process of generating an anti-interference communication result set comprises the following steps: The cryptographic hash value of each tag physical layer feature vector reserved by the previous process is extracted from the unified structured instruction set, and combined with the spatial topology information provided by the spatial distribution map to generate a set of temporary identity credentials with spatial correlation; The temporary identity credential set and the physical layer feature vector are processed through a dynamic physically unclonable function engine to generate a dynamic challenge sequence according to the historical state parameters of the dynamic energy field, and generate a one-time variable encrypted authentication evidence stream; After the encrypted authentication evidence stream is verified through consensus based on fuzzy matching, an asynchronous key negotiation mechanism is triggered, and the key shares of each tag are interleaved and aggregated using the initial link of the block chain data aggregation engine to form a shared master key chain and derive an independent security channel; The original operation result generated by the independent security channel executing distributed read-write operations is output as an original result vector set with complete space-time marks; The original result vector set is processed by a redundancy check matrix constructor to dynamically generate an optimal check dimension according to the number of communication channels, spatial density and historical interference mode, and construct an anti-tamper multi-dimensional check tensor that introduces the shared master key chain as a randomization seed; The original result vector set with space-time marks is executed through distributed redundancy calculation by the multi-dimensional check tensor to generate a strengthened result set with strong encryption check codes; The strengthened result set is finally processed by a consistency reconstructor to perform cross-validation and error correction using the check tensor, and to repair and restore the historical data of the dynamic energy field corresponding to the time-space marks of the data unit that fails the check, and to aggregate to generate an anti-interference communication result set with high integrity.

2. The single chip extended multiple NFC antenna tag communication method of claim 1, wherein, The process of constructing an anti-tamper multi-dimensional check tensor that introduces the shared master key chain as a randomization seed comprises the following steps: Convolve the spatial density and the historical interference mode to generate a spatial weighted interference probability distribution map, and perform matrix multiplication with the number of communication channels to calculate the minimum amount of redundant information; Output the dynamic optimal check dimension value; Create an empty base tensor with the dynamic optimal check dimension value as the order; each initial element position of the empty base tensor is initialized and scrambled by the coordinate offset derived from the shared master key chain; form an initial tensor framework with a cryptographic chaos characteristic from the scrambled empty base tensor; Split the key chain into multiple segments, each of which controls the polynomial coefficient of a different section of the empty base tensor; perform a modulo operation on the metadata of the original result vector set with the time-space imprint to construct an anti-tamper multi-dimensional check tensor that is strongly bound to the session key and structurally unique.

3. The single chip extended multiple NFC antenna tag communication method of claim 2, wherein, The process of performing a modulo operation on the polynomial coefficient and the metadata of the original result vector set with the time-space imprint includes the following steps: The spatial coordinate index of the target cell in the initial tensor framework and a specific key segment of the shared master key chain are input into the coordinate-key obfuscator; the coordinate-key obfuscator performs XOR and cyclic shift operations on the coordinate value and the key segment to generate a temporary cell-specific entropy value; at the same time, a context token that is strongly related to the specific operation time and location is output; The cell-specific entropy value and the context token are concatenated, and then another different key segment is used as a selector to extract the bytes at a specific position from the concatenated result to generate an intermediate decision seed; Multiply the historical error rate weight of the intermediate decision seed to generate a dynamic decision factor; Perform a modulo operation on the generated dynamic decision factor and a modulus reference value derived from the polynomial coefficient to obtain a normalized algorithm selection index value; the algorithm decision mapping table outputs a specific algorithm identifier according to the algorithm selection index value, which indicates which one of the parity check, cyclic redundancy check, or Reed-Solomon encoding variant should be used to fill the cell; The algorithm identifier and the original data content of the current cell are sent to the parameterized algorithm execution unit; a unique check code is calculated for the specific cell, and it is filled into the corresponding position of the initial tensor framework to complete the construction of the cell.

4. The single chip extended multiple NFC antenna tag communication method of claim 3, wherein, The process of outputting a specific algorithm identifier according to the algorithm selection index value by the algorithm decision mapping table includes the following steps: Square the dynamic optimal check dimension value calculated by the check strategy fusion core to obtain a basic mapping space size; perform a bitwise AND operation on the basic mapping space size and a fixed key segment of the shared master key chain to generate an actual mapping table size value, which initializes an empty and to-be-filled mapping table skeleton; Split the remaining part of the key chain into multiple cryptographic slices of different lengths, the first slice is used to generate an initial algorithm type distribution weight vector; the second and subsequent slices are used to create a nonlinear disturbance program; output an original mapping table whose content is primarily shaped by the key but not yet associated with the current environment by the mapping logic filler; According to the frequency of each type of error in the error feature vector, the distribution density of the corresponding algorithm identifier in the original mapping table is dynamically adjusted; in the area where the historical burst error is high, the mapping probability of the Reed-Solomon coding variant algorithm is increased; an adaptive mapping table optimized by environmental experience is generated; The normalized algorithm selection index value is first processed by a nonlinear disturbance program controlled by the key to generate a final encrypted and confused lookup key value, and then addressed in the adaptive mapping table optimized by environmental experience using a fuzzy matching mechanism; The specific algorithm identifier that determines the cell is output by the fuzzy matching mechanism.

5. The single chip extended multiple NFC antenna tag communication method of claim 4, wherein, The process of using the fuzzy matching mechanism includes the following steps: The last few digits of the dynamically optimal check dimension value are processed by the numerical feature extractor to separate the parity characteristics and prime factor distribution characteristics, forming an initial threshold modulation vector; the initial threshold modulation vector generates a reference floating threshold through nonlinear transformation; The reference floating threshold is coupled with the current load factor of the adaptive mapping table optimized by environmental experience to perform coupled operation to generate a dynamic range radius; the dynamic range radius is added or subtracted with the encrypted and confused lookup key value to determine the upper and lower bounds of fuzzy matching, forming a dynamic matching window; All entries in the dynamic matching window enter the weight evaluation stage, and the spatial error correlation coefficient extracted from the historical interference mode is used as the weighting factor; The weighting factor and the inherent priority of each entry are convolved to generate a candidate entry confidence sequence; the optimal matching candidate set is screened out; The optimal matching candidate set uses the nearest neighbor priority principle based on time decay to output the determined algorithm identifier from the optimal matching candidate set, combined with the numerical distribution characteristics of the lookup key value.

6. The single chip extended multiple NFC antenna tag communication method of claim 5, wherein, The process of outputting the determined algorithm identifier from the optimal matching candidate set includes the following steps: The optimal matching candidate set uses the timestamp information of the spatial error correlation coefficient extracted from the historical interference mode to obtain the interval between the historical decision time corresponding to each candidate entry and the current time; the time interval is transformed by a negative exponential function to generate a time decay factor sequence; The time decay factor sequence and the candidate entry confidence sequence are weighted and fused, where the time decay factor is used as a weight coefficient to multiply the confidence; the multiplication operation produces a time-sensitive confidence score; the time-sensitive confidence score is normalized to form a priority sequence with time-sensitive characteristics; At the same time, the neighborhood optimization program adjusts the arrangement order of each candidate entry in the priority sequence according to the stability index, and enhances the weight of the nearest neighbor principle for numerical distribution areas with lower stability, and maintains the original priority order for areas with higher stability; The candidate set adjusted by the neighborhood optimization program uses the proximity measurement method based on Mahalanobis distance to obtain the comprehensive distance between each candidate entry and the ideal matching point combined with the numerical distribution stability index; the distance produces a final matching degree score; The final matching degree score is sorted and selected, and the algorithm identifier corresponding to the highest score is output as the final decision result.

7. A single-chip multiple-NFC-antenna tag for implementing the method of claim 1-6, wherein, It includes: a first coil, a second coil, a riveting position, a chip, and a defective ink dot. The chip is connected with the first coil and the second coil through double parallel circuits to form a redundant design, and the riveting position is connected with the pads of the chip; and the defective ink dots are printed on the test points of the chip for detection in the automatic test.

8. A method for producing a single-chip multi-NFC antenna tag according to claim 7, wherein the single-chip multi-NFC antenna tag is produced by the method comprising the steps of: Comprise: ​ Step one, the blank flexible substrate is subjected to surface cleaning and plasma activation treatment to obtain a pretreated substrate with uniform surface energy; Step two, the pretreated substrate is subjected to a screen printing conductive silver paste or etching copper foil process to obtain an array pattern comprising a plurality of NFC antenna units, and is subjected to high-temperature curing or chemical etching post-treatment to obtain a stable conductive antenna network layer; Step three, the antenna network layer is positioned, and a single NFC chip is connected with the antenna unit through conductive adhesive dispensing or flip-chip bonding process to obtain a primary complex; The primary complex is subjected to heat pressing curing or reflow soldering process to obtain a chip-antenna module with stable electrical performance; Step four, the chip-antenna module is subjected to a lamination process of covering PET protective film or injection molding epoxy resin to obtain a semi-finished product with a protective structure; the semi-finished product is subjected to die cutting or laser cutting process to obtain independent label units; Step five, the label units are subjected to radio frequency performance test screening, and the qualified products are subjected to data burning equipment to write personalized information to obtain identifiable intelligent labels; the intelligent labels are subjected to appearance quality inspection and impedance matching debugging to finally obtain NFC antenna label finished products meeting industrial standards.

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