Spread spectrum coding method and system with error correction function and application

Abstract

The invention discloses a spread spectrum coding method with an error correction function, which can solve the problems of small capacity, low error-tolerant rate and low safety of a conventional coding mode. The system comprises a set of coding system composed of a data coding module, a data spread spectrum module, a data filling module and a data scrambling module. The data encoding module and the data spread spectrum module encode to-be-encoded data into effective information and error correction code information, and the effective information and the error correction code information are in one-to-one correspondence with the Hadamard matrixes to realize spread spectrum; the data filling module blocks and fills the data to form a square spreading code, expands the data and converts the data into 256-system data, so that the influence of geometric scaling on decoding is reduced, and the security of the decoding is improved; and finally, scrambling the data position by using a random seed, thereby reducing the condition that the spreading code region is obvious in rule and improving the randomness of the spreading code. The method has the advantages that the error detection and correction capability and secrecy performance are high, the information storage capacity and the error-tolerant rate are flexible and adjustable, and more choices are provided for digital image information hiding, storage and anti-counterfeiting.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and relates to a spread spectrum coding method, system and application with error correction function. Background Art

[0002] With the development of computer network technologies and digital communication technologies, the exchange, transmission and replication of data have become relatively simple. However, there is also an adverse side, that is, the tampering and copying of works are easier. Therefore, how to implement effective copyright protection has become an imminent practical problem. Coding is to consciously hide some secret information to prove the ownership of the original author of the work, or as evidence for identifying piracy and infringement. Spread spectrum communication technology is a way of information transmission, and the bandwidth occupied by its signal is much larger than the minimum bandwidth required for the transmitted information; the expansion of the bandwidth is completed through an independent code sequence, and is achieved by coding and modulation methods, which has nothing to do with the transmitted information data; at the receiving end, the same code is used for correlation synchronization reception, despreading and restoring the transmitted information data.

[0003] There have been various related applications of spread spectrum coding in the prior art. Spread spectrum coding is a commonly used technical means in the fields of communication, data transmission and information security. It encodes the original signal through a spread spectrum code, thereby broadening the signal in the frequency domain, and improving the anti-interference ability and security of the signal.

[0004] However, traditional spread spectrum coding methods have some deficiencies to a certain extent. The error correction function of conventional spread spectrum coding itself is to add redundant information to each spread spectrum code during coding to provide error correction function, but the fault tolerance robustness is poor. This coding requires that each individual spread spectrum code must be completely decoded, and there is also a problem of low security. In some scenarios, especially for situations with high requirements for data integrity and security, these problems have become bottlenecks restricting the application of spread spectrum coding. Summary of the Invention

[0005] In order to solve the deficiencies of the prior art, the purpose of the present invention is to provide a spread spectrum coding method and system with error correction function, adding the error correction code coding idea into the spread spectrum code, not requiring each spread spectrum code to be completely decoded, and being able to completely restore some partially incorrect spread spectrum codes according to the error correction code, so as to achieve a spread spectrum coding with high security and high fault tolerance rate, solve the problems that conventional spread spectrum coding cannot correct errors by itself, has a low fault tolerance rate and low security, realize a high-security and high-fault tolerance spread spectrum coding method with error correction function, bring new ideas and methods for the development of spread spectrum coding technology, and expand its application prospects in the fields of communication, data storage, etc.

[0006] The most core innovation of the present invention lies in adding an error-correcting code to the spreading code, thereby realizing a spreading coding scheme with error-correcting function. The present invention makes the encoded data have strong error-correcting and error-detecting capabilities by adding an error-correcting code to the valid information.

[0007] The present invention provides a spreading coding method with error-correcting function, and the method includes the following steps:

[0008] Step 1, read the information to be encoded, where the information to be encoded includes valid information and error-correcting code information, and encode the information to obtain encoded data;

[0009] The encoding refers to jointly encoding the valid information and the error-correcting code information into 256 - base data; the valid information includes meta - information data and valid data; the meta - information data refers to a set of data used to describe the valid information; the valid data refers to the information content that actually needs to be transmitted or stored, which can be English letters, URL links, numbers, etc.

[0010] Step 2, generate a Hadamard matrix, make the encoded data in Step 1 correspond to the Hadamard matrix to obtain binary data, and perform data spreading;

[0011] Step 3, divide the binary data obtained in Step 2 into blocks, and fill them into the smallest square spreading code, expand the square spreading code, and randomly transform the binary data in the square spreading code;

[0012] Step 4, adjust the data in the square spreading code through a random seed and data position scrambling to achieve signal spreading.

[0013] The present invention also provides a system for implementing the above method, and the system includes a data encoding module, a data spreading module, a data filling module, a data random transformation module, and a data scrambling module.

[0014] The data encoding module further includes a data reading module and an encoding module, which are used to read the valid data, and then combine the meta - information data, and encode through the error - correcting code generated by Reed - Solomon encoding to generate 256 - base encoded data with fault - tolerance function; specifically used to perform the following operation steps:

[0015] Step 1.1, the data reading module reads the information to be encoded, and the valid data in the information to be encoded is input by the user himself, and the valid data includes English letters, URL links, numbers, etc.

[0016] Step 1.2: The encoding module encodes the meta - information data, valid data, and error - correction code information to generate 256 - base encoded data. The length L of the encoded data is determined according to the length of the information to be encoded read and the error tolerance rate. The length of the encoded data is equal to the sum of the lengths of the meta - information data, valid data, and error - correction code information. The meta - information data includes the data encoding method and information length of the valid information. The error - correction code information is generated by Reed - Solomon encoding based on the error tolerance rate and valid information, and can correct errors when the valid information has errors.

[0017] During the determination of the length L of the encoded data, the error tolerance rate needs to be preset before encoding; the formula for the length L of the encoded data is as follows:

[0018]

[0019] where L is the length of the encoded data, L1 is the length of the information read, and α is the error tolerance rate;

[0020] The Reed - Solomon encoding regards the data as a polynomial and calculates the error - correction code based on the polynomial. These error - correction codes are appended to the original data as additional information and can be used to detect and correct errors when the data is damaged, thereby improving the reliability and error tolerance of data transmission.

[0021] The error - correction code can further include a meta - information data error - correction code and a valid data error - correction code, which are stored behind the meta - information data and valid data respectively.

[0022] The data spreading module further includes a Hadamard matrix generation module and a spreading module, which spreads the encoded data using the Hadamard matrix, generating a set of binary data with the length of the encoded data × the dimension size of the Hadamard matrix by corresponding each bit of the encoded data to a specific row of the matrix; specifically, it is used to perform the following operation steps:

[0023] Step 2.1: The Hadamard matrix generation module generates a Hadamard matrix. All numbers in the Hadamard matrix are binary numbers, and each row and each column of the matrix are orthogonal. In a specific embodiment, the size of the Hadamard matrix is 256×256. The 256×256 matrix size is an example in the present invention to illustrate the operation of generating the Hadamard matrix. This example can be adjusted according to specific application scenarios and requirements. In the present invention, the Hadamard matrix is used to correspond to the encoded data to achieve data spreading, improving the security and anti - interference ability of the data, enhancing the reliability of data transmission, and effectively expanding the range and complexity of the original data.

[0024] Step 2.2: The spreading module maps the encoded data to the Hadamard matrix. The mapping method is that each bit in the encoded data corresponds to a specified row of the Hadamard matrix, which ensures that the obtained data set after spreading has high uniqueness, and a binary data set with the length of the encoded data L multiplied by the dimension size of the Hadamard matrix is obtained. For example, if a certain bit in the encoded data is 200, then this data corresponds to the 201st row of the Hadamard matrix. Finally, a group of binary data of L×256 is obtained by the data spreading device, realizing the spreading of the data.

[0025] The Hadamard matrix is a special orthogonal matrix, and each row and each column of the matrix are composed of orthogonal vectors with an inner product of 0. The spreading refers to performing a certain transformation on the encoded data to make it have a wider spectrum characteristic.

[0026] The data filling module further includes a data block module, a filling module, a data expansion module, and a data conversion module. The encoded data is divided into multiple binary matrix blocks with the size of the square root of the Hadamard matrix dimension, filled into a square spreading code, then expanded by n times, and then the binary data in the square spreading code is randomly converted into integers within a preset range. Specifically, it is used to perform the following operation steps:

[0027] Step 3.1: The data block module divides the binary data with the length of the encoded data L multiplied by the dimension size of the Hadamard matrix into L binary matrix blocks. The dimension size of the binary matrix block is the square root of the Hadamard matrix dimension. In a specific embodiment, the binary data of L×256 is divided into L binary matrix blocks of 16×16.

[0028] Step 3.2: The filling module fills these L binary matrix blocks with the dimension of the square root of the Hadamard matrix dimension into the smallest square spreading code. If the data information is 0, it is filled with 0; if the data information is 1, it is filled with 1. For example, if L = 16, it can be filled into a 64×64 square spreading code, which contains 16 binary matrix blocks. If it cannot just form the smallest square, the remaining part is filled with 0.

[0029] Step 3.3: The data expansion module expands the smallest square spreading code by n×n. The purpose is to reduce the influence of the scaling of the spreading code size on decoding during the decoding process and improve the decoding success rate. The side length of the square spreading code is expanded to n times the original. In a specific embodiment, the specific expansion method is that each data in the square spreading code is represented by the same 2×2 data, and finally the side length of the square spreading code is also expanded to 2 times the original.

[0030] Step 3.4: The data conversion module randomly converts the binary data in the square spreading code. The purpose is to improve the randomness of the encoded data and enhance its security. The specific representation method is to randomly convert 0 in the binary to an integer between (56, 105), and 1 to a random number between (106, 156). The purpose of converting to random numbers is to hide the true spreading code group, and the specific selection interval can also be chosen according to actual needs and security requirements.

[0031] The data scrambling module further includes a seed module and a scrambling module, which scramble the data positions of the square spreading code through a user-defined random seed to improve the coding security and randomness, so as to generate the final spreading code map; specifically, it is used to perform the following operation steps:

[0032] Step 4.1: The seed module customizes a string of decimal random seeds for the subsequent scrambling module to scramble the data positions of the square spreading code. The random seeds need to be saved in the decoding program to restore the data positions in the square spreading code. The inserted random seeds are customized by the user without special requirements.

[0033] Step 4.2: The scrambling module scrambles the data positions in the square spreading code. On the one hand, it can enhance the coding security, and on the other hand, it can improve the randomness of the spreading code. The operation processes of the seed module and the scrambling module are integrated, and there is no clear requirement for the order. The two can be implemented in parallel and act together on the data of the square spreading code, taking the scrambled square spreading code as the final output, that is, the spreading code map.

[0034] After the operation of the above process of the present invention, a spreading code map is finally obtained. This spreading code map can decode the data after spreading coding with high security and high fault tolerance that has an error correction function. This data has a certain error detection and correction ability, the storage information volume is flexibly adjustable, and it has strong robustness and security.

[0035] The present invention also provides the application of the above method or system in introducing error correction codes into spreading coding to improve its robustness and security, which can be used for digital image information storage, anti-counterfeiting, or traceability, etc.

[0036] The advantages of the present invention include:

[0037] (1) Error correction codes are added to the valid information, which has a certain error detection and correction ability. The error detection and correction ability is determined during coding and can be set by itself.

[0038] (2) The storage information volume is flexible, and the length of the encoded data and the size of the spreading code can be adjusted according to the storage requirements.

[0039] (3) The spreading code itself can resist a certain degree of image compression and geometric attacks, and has strong robustness.

[0040] (4) High security. By adding a data conversion module and a data scrambling module, the situation where the coding rules are obvious can be effectively avoided.

[0041] (5) It has a wide range of application scenarios and can be used for digital image information storage, hiding, anti-counterfeiting, etc. Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is the flow chart of the present invention.

[0044] Figure 2 It is the arrangement of coded data.

[0045] Figure 3 It is the schematic diagram of spreading code data filling.

[0046] Figure 4 It is the schematic diagram of spreading code data expansion.

[0047] Figure 5 It is the spreading code grayscale image. Detailed Embodiments

[0048] Combined with the following specific embodiments and drawings, the present invention will be further described in detail. The processes, conditions, experimental methods, etc. for implementing the present invention, except for the specifically mentioned content below, are all common knowledge and well-known common sense in the art, and the present invention has no special limiting content.

[0049] The purpose of the present invention is to provide a spread spectrum coding method and system with an error correction function to solve the problems of small capacity, low error tolerance, and low security of conventional coding methods.

[0050] The present invention proposes a spread spectrum coding method with an error correction function, which can solve the problems of small capacity, low error tolerance rate, and low security of conventional coding methods. The present invention includes a coding system composed of a data coding module, a data spread spectrum module, a data filling module, and a data scrambling module. The data coding module and the data spread spectrum module encode the data to be encoded into valid information and error correction code information, and achieve spread spectrum through one-to-one correspondence with the Hadamard matrix; the data filling module divides and fills the data to form a square spread spectrum code, and then expands and converts the data into 256-base data, which reduces the influence of geometric scaling on decoding while improving its security; finally, the data position is scrambled using a random seed to reduce the obvious regularity in the spread spectrum code area and improve the randomness of the spread spectrum code. The present invention has strong error detection and correction capabilities and confidentiality performance, and the information storage capacity and error tolerance rate are flexibly adjustable, which can provide more choices for digital image information hiding, storage, and anti-counterfeiting.

[0051] The present invention realizes a spread spectrum coding method and system with an error correction function through the following technical solutions. The spread spectrum coding system in the present invention includes a data coding module, a data spread spectrum module, a data filling module, and a data scrambling module. The specific implementation process of the spread spectrum coding method of the present invention is as Figure 1 shown.

[0052] Specifically, the entire process is described in combination with the spread spectrum coding system applied in the present invention as follows:

[0053] The data coding module performs the following operation steps:

[0054] (1) The data reading module reads the information to be encoded: it can be English letters, URLs, numbers, etc. Among them, if it is a number, it is directly encoded; if it is an English letter or a URL, it needs to be first converted to its ASCII code value, converted into binary data, and then encoded. The length L of the encoded data depends on the length of the read valid information, error correction code information, and error tolerance rate.

[0055] (2) The coding module encodes to generate 256-base valid information and error correction code information. The error correction code information can correct errors when there are errors in the valid information. The valid information part consists of two parts: meta-information data and valid data. The meta-information data contains the coding method and information length of the valid information data. After the meta-information data, the valid information data is stored. The arrangement of the encoded data is as Figure 2 shown. Both the meta-information and the valid data require their respective error correction code information, namely the meta-information data error correction code and the valid data error correction code. The lengths of the valid information and the error correction code can be adjusted according to the error tolerance rate required in different application scenarios. For example, for an 8-bit valid information data with a 50% error tolerance rate, the actual storage information data length and the error correction code length should both be 4 bits, that is, the length ratio is 1:1.

[0056] The described data spreading module performs the following operating steps:

[0057] (1) A Hadamard matrix of 256×256 is generated by a Hadamard matrix generation module. All the numbers in the Hadamard matrix are binary numbers, and each row and each column of the matrix are orthogonal. The orthogonality of the matrix data can ensure that the 256-dimensional Hadamard matrix data corresponding to each 256-ary encoded data is unique, and can also minimize the error probability if a burst error occurs during subsequent decoding.

[0058] (2) The spreading module corresponds the encoded data to the Hadamard matrix. The corresponding method is that each encoded data corresponds to a specified row of the Hadamard matrix. For example, if a certain bit of the encoded data is 200, then this data corresponds to the 201st row of the Hadamard matrix. Finally, a set of L×256 binary data is obtained by the data spreading device, realizing the spreading of the data.

[0059] The described data filling device performs the following operating steps:

[0060] (1) The L×256 binary data is divided into L binary matrix blocks of 16×16 by a data block division module.

[0061] (2) The filling module fills these L binary matrix blocks of 16×16 into the smallest square spreading code. For example, if L = 16, it can be filled into a 64×64 square spreading code, which contains 16 binary matrix blocks. If it cannot just form the smallest square, the remaining part can be filled with 0. The filling schematic diagram is as Figure 3 shown, where the gray matrix blocks are valid data and the blank matrix blocks are the remaining data filled with 0.

[0062] (3) The square figure is expanded by 2×2 by a data expansion module. The purpose is to reduce the influence of the spreading code size scaling on decoding during the decoding process and improve the decoding success rate. The specific expansion method is that each data in the square spreading code is represented by the same 2×2 data. The expansion schematic diagram is as Figure 4 shown, and finally the side length of the square spreading code is also expanded to twice the original.

[0063] (4) The binary data in the square spreading code is randomly converted by a data conversion module. The purpose is to improve the randomness of the encoded data and improve its security. The specific representation method is to randomly convert 0 in the binary to an integer between (56, 105), and 1 to a random number between (106, 156). The conversion formula is defined as:

[0064]

[0065] where, m(x,y) represents a certain bit of binary data in the spreading code, m r(x, y) represents the spread spectrum code data after random conversion, and randint() represents the function of randomly obtaining integer values.

[0066] The data scrambling module performs the following operation steps:

[0067] (1) The seed module customizes a string of random seeds in decimal for scrambling the data positions in the square spread spectrum code. The random seeds need to be saved in the decoding program to restore the data positions in the square spread spectrum code.

[0068] (2) The scrambling module scrambles the data positions in the square spread spectrum code. On the one hand, it can improve the coding security, and on the other hand, it can increase the randomness of the spread spectrum code. Finally, the spread spectrum code is generated in the form of a grayscale image as Figure 5 shown.

[0069] Superiority compared with the existing technical methods:

[0070] The error tolerance rate is higher. For different sizes of versions, the highest error tolerance rate of the spread spectrum code can reach 50%. For example, in the 20×20 version, both the information code length and the error correction code length are 16, and the error tolerance rate can reach 50%. The information code length is equal to the error correction code length in other versions, and the error tolerance rate reaches 50%.

[0071] The encoded data is more flexible. The encoding information length can also be adjusted according to the storage requirements. By reducing the error correction code and increasing the number of information codes, the encodable information length can be increased. For example, in the 20×20 version, when the error tolerance rate is 50%, the information code length is 16, the error correction code length is 16, and the encodable information length is 39 bits (decimal digits). As the code size decreases, the maximum encodable information length also decreases, but the high error tolerance rate version has a higher error tolerance rate, which can improve the reliability of the data.

[0072] Embodiment 1

[0073] Taking the anti-counterfeiting label of high-value commodities as an example, the spread spectrum coding method of the present invention can be widely applied to the commodity packaging industry. The entire process and implementation of this method specifically include:

[0074] (1) Data reading and encoding. During the production process of the anti-counterfeiting label, first, the information to be encoded needs to be imported into the system. This information can include the commodity name, production date, etc., or relevant URL links, as well as digital information. Digital information can be directly encoded; if it is an English letter or URL, it is first converted into ASCII code values, and then the ASCII code values are converted into binary data (decimal digits). The information data containing valid information and error correction information is obtained.

[0075] (2) Data spreading: A Hadamard matrix of 256×256 is generated by a Hadamard matrix generation module, and each row and each column of the matrix are orthogonal. The orthogonality of the matrix data can ensure that the 256-dimensional Hadamard matrix data corresponding to each 256-ary encoded data is unique, and even if there are sudden errors during subsequent decoding, the error probability can be minimized.

[0076] The spreading module corresponds each encoded data to the Hadamard matrix. The corresponding method is that each encoded data corresponds to a specified row of the Hadamard matrix. For example, if a certain bit of the encoded data is 100, then this data corresponds to the 101st row of the Hadamard matrix. Finally, a set of L×256 binary data is obtained by the data spreading device, realizing the spreading of the data.

[0077] (3) Data filling: In this step, L 16×16 binary matrix blocks are combined into the smallest square spreading code. This can be achieved by filling these blocks into a 64×64 square spreading code, which contains 16 binary matrix blocks. If the smallest square cannot be formed exactly, the remaining part will be filled with 0.

[0078] (4) Data expansion: Further expand the square spreading code by 2×2. The purpose is to reduce the impact of the scaling of the spreading code size on decoding during the decoding process and improve the decoding success rate. In this way, the side length of the expanded square spreading code is also expanded to twice the original.

[0079] (5) Data conversion and scrambling: The binary data in the square spreading code is randomly converted to improve the randomness and security of the encoded data. Each 0 is randomly converted into a certificate between (56, 105), and each 1 is randomly converted into a random number between (106, 156). Then, through a custom random seed key, the data positions in the square spreading code are scrambled, enhancing the security and randomness of the encoding.

[0080] Through the above process, a spread-spectrum encoded anti-counterfeiting label can be obtained, which has high security and robustness and is suitable for protecting the anti-counterfeiting needs of high-value goods.

[0081] Comparative example

[0082] This embodiment is a specific method of a related implementation in the prior art by comparing with the above embodiment.

[0083] Direct-sequence spread-spectrum technology is a modulation technology that realizes signal transmission by multiplying a data sequence by a spreading code. First, a spreading code needs to be selected, usually a pseudo-random binary sequence with a long period. The transmitter performs a bit-by-bit multiplication operation on the original data and the spreading code to expand the data sequence into a high-speed spread-spectrum signal. The receiver uses the same spreading code for despreading to restore the spread-spectrum signal to the original data.

[0084] In the implementation process, it is necessary to ensure that the sending end and the receiving end can synchronously use the same spreading code for encoding and decoding. This can be achieved by the sending end sending the spreading code together, or through other synchronization methods.

[0085] However, direct sequence spread spectrum technology has some limitations, such as poor error correction ability and relatively low utilization efficiency of spectrum resources. The present invention effectively makes up for these limitations of DSSS technology by introducing improvement measures such as error correction codes, data random conversion, and data scrambling modules.

[0086] The protection scope of the present invention is not limited to the above embodiments. Without departing from the spirit and scope of the inventive concept of the present invention, the changes and advantages that can be conceived by those skilled in the art are included in the present invention, and the appended claims are used as the protection scope.

Claims

1. A spread spectrum coding method with error correction function, characterized in that, The spread spectrum coding method includes the following steps: Step 1: Read the information to be coded, and code the information to obtain coded data; Step 2: Generate a Hadamard matrix, map the coded data in Step 1 to the Hadamard matrix to obtain binary data, and perform data spread spectrum; Step 3: Divide the binary data obtained in Step 2 into blocks, fill them into the smallest square spread spectrum code, expand the smallest square spread spectrum code, and randomly transform the binary data in the square spread spectrum code; Step 4: Adjust the data in the square spread spectrum code through a random seed and data position scrambling to achieve signal spread spectrum.

2. The spread spectrum coding method according to claim 1, characterized in that, Step 1 includes the following steps: Step 1.1: Read the meta-information data, valid data, and error correction code information in the information to be coded; Step 1.2: Code according to the meta-information data, valid data, and error correction code information read in Step 1.1 to generate 256-ary coded data; The information to be coded includes valid information and error correction code information. The valid information includes meta-information data and valid data; the coding refers to coding the valid information and error correction code information into 256-ary data; the valid data includes English letters, URL links, and numbers; the length of the coded data is L, which is equal to the sum of the lengths of the meta-information data, valid data, and error correction code information; The length L of the coded data is determined by the length of the information to be coded read and the error tolerance rate, and the error tolerance rate is preset before coding; the formula for the length L of the coded data is: where L is the length of the coded data, L1 is the length of the information to be coded read, and α is the error tolerance rate.

3. The spread spectrum coding method according to claim 1, characterized in that, Step 2 further includes the following steps: Step 2.1: Generate a Hadamard matrix; Step 2.2: Map each bit in the coded data to the specified row of the Hadamard matrix to obtain a set of binary data with the length of the coded data L×the dimension size of the Hadamard matrix, and achieve data spread spectrum; The Hadamard matrix is a special orthogonal matrix, and each row and each column of the matrix are composed of orthogonal vectors with an inner product of 0.

4. The spread spectrum coding method according to claim 1, characterized in that, Step 3 further includes the following steps: Step 3.1: Divide the binary data with the length of the coded data L×the dimension size of the Hadamard matrix into L binary matrix blocks; Step 3.2: Fill the L binary matrix blocks obtained in Step 3.1 into the smallest square spread spectrum code; Step 3.3: Expand the square spread spectrum code; Step 3.4: Randomly transform the binary data in the square spread spectrum code to hide the true spread spectrum code group; The dimension size of the binary matrix block is the square root of the dimension of the Hadamard matrix; In the square spread spectrum code, when the data information is 0, it is filled with 0, and when the data information is 1, it is filled with 1; The expansion means that each data in the square spread spectrum code is represented by the same n×n data, so that the side length of the square spread spectrum code is expanded to n times the original; 5. The spread spectrum coding method according to claim 1, characterized in that, Step 4 further includes the following steps: Step 4.1: Customize a string of decimal random seeds; Step 4.2: Use the random seed obtained in Step 4.1 to scramble the data positions in the square spread spectrum code, and the scrambled square spread spectrum code will be the final output; The step 4.1 and the step 4.2 are executed in parallel; the random seed refers to a string of decimal numbers, which is stored in the decoding program and is used to restore the position of the data in the square spread spectrum code; the scrambling refers to scrambling the data position in the square spread spectrum code through the random seed.

6. The spread spectrum code map obtained by the spread spectrum coding method according to any one of claims 1-5.

7. A spread spectrum coding system for implementing the spread spectrum coding method according to any one of claims 1-5, characterized in that, The spread spectrum coding system comprises: a data coding module, a data spread spectrum module, a data filling module and a data scrambling module; The data encoding module includes a data reading module and an encoding module, which are used to read valid data, and then encode the data by using the error correction code generated by Reed-Solomon coding in combination with the meta-information data to generate 256-based encoded data with fault tolerance function; The data spreading module includes a Hadamard matrix generation module and a spreading module, which spreads the coded data using the Hadamard matrix, and generates a binary data set of the coded data length × the Hadamard matrix dimension size by corresponding each bit of the coded data to a specific row of the matrix; The data filling module includes a data block module, a filling module, a data expansion module, and a data random conversion module, which are used to divide the coded data into a plurality of binary matrix blocks of the size of the square root of the Hadamard matrix dimension, fill them into square spread spectrum codes, and then expand them by n times, and then randomly convert the binary data in the square spread spectrum codes into integers within a preset range; The data scrambling module includes a seed module and a scrambling module, which is used to scramble the data position of the square spread spectrum code through a user-defined random seed to generate a final spread spectrum code map.

8. The spread spectrum coding method according to any one of claims 1-5, or the application of the spread spectrum coding system according to claim 7 in introducing an error correction code into spread spectrum coding to realize digital image information storage, anti-counterfeiting or traceability.

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