Surface acoustic wave signal processing method and system based on NQAM demodulation algorithm

Abstract

The present invention discloses a surface acoustic wave signal processing method and system based on an NQAM demodulation algorithm, the method comprising: obtaining a surface acoustic wave signal, performing interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal; demodulating the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal. The model complexity is controlled while reducing the error, ensuring that stable filtering performance can be provided even under extreme conditions.

Description

Technical Field

[0001] The invention belongs to the technical field of radio frequency identification, and in particular relates to a surface acoustic wave signal processing method and system based on an NQAM demodulation algorithm. Background Art

[0002] In the field of radio frequency identification technology, especially surface acoustic wave (SAW) radio frequency identification technology, there are many technical challenges and problems. Surface acoustic wave technology uses the propagation characteristics of sound waves on piezoelectric substrates to convert electrical signals into acoustic signals through interdigital transducers (IDTs), thereby realizing signal extraction and processing. SAW tags have various encoding methods, including on-off keying, pulse position modulation, and phase modulation, which rely on the amplitude of the reflected echo, the envelope peak position, and the carrier phase.

[0003] Surface acoustic wave technology is a technology that uses the characteristics of sound waves propagating on the surface of solid media to process signals. It has a wide range of applications in the field of radio frequency identification (RFID), especially in harsh environments. The existing process of surface acoustic wave signal processing is usually: first, the surface acoustic wave is excited on the surface of the piezoelectric material through the interdigital transducer to propagate along the solid surface; then, the surface acoustic wave carries information during the propagation process and interacts with the material through a specific path to achieve signal sampling and transformation; then, the receiving transducer is used to detect the propagated surface acoustic wave signal and convert it into an electrical signal; finally, these electrical signals are demodulated and processed to extract useful information and data.

[0004] In the prior art, although the demodulation of the surface acoustic wave junction signal has been optimized to a certain extent, the signal filtering and demodulation algorithms have not been well improved, resulting in poor filtering effect. Summary of the invention

[0005] The present invention provides a surface acoustic wave signal processing method and system based on an NQAM demodulation algorithm, which are used to solve the technical problem of poor filtering effect.

[0006] In a first aspect, the present invention provides a surface acoustic wave signal processing method based on an NQAM demodulation algorithm, comprising:

[0007] Acquire a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal;

[0008] The target surface acoustic wave signal is demodulated according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0009] In a second aspect, the present invention provides a surface acoustic wave signal processing system based on an NQAM demodulation algorithm, comprising:

[0010] A processing module is configured to obtain a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal;

[0011] The demodulation module is configured to demodulate the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0012] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the surface acoustic wave signal processing method based on the NQAM demodulation algorithm of any embodiment of the present invention.

[0013] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the surface acoustic wave signal processing method based on the NQAM demodulation algorithm of any embodiment of the present invention.

[0014] The surface acoustic wave signal processing method and system based on the NQAM demodulation algorithm of the present application adopts the ILMS adaptive filtering algorithm to achieve self-interference elimination. The adaptive filtering algorithm realizes efficient elimination of self-interference in the echo signal through a composite filter structure and high-order error correction, combined with dynamic step size adjustment and global optimization strategy. The time-dependent parameter adjustment in the algorithm enhances the stability and robustness of the system, while the integration of the historical behavior of the signal improves the processing capability of delayed echoes. In addition, through the high-order dynamic adjustment mechanism and multi-objective optimization of the third-order gradient, the algorithm controls the model complexity while reducing the error, ensuring stable filtering performance under extreme conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flow chart of a surface acoustic wave signal processing method based on an NQAM demodulation algorithm provided by an embodiment of the present invention;

[0017] Figure 2 A structural block diagram of a surface acoustic wave signal processing system based on an NQAM demodulation algorithm provided by an embodiment of the present invention;

[0018] Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figure 1 , which shows a flow chart of a surface acoustic wave signal processing method based on an NQAM demodulation algorithm of the present application.

[0021] like Figure 1 As shown, the surface acoustic wave signal processing method based on the NQAM demodulation algorithm specifically includes the following steps:

[0022] Step S101 : acquiring a surface acoustic wave signal, and performing interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal.

[0023] In this step, a surface acoustic wave signal is obtained, and the expression of the surface acoustic wave signal is:

[0024] ,

[0025] In the formula, is the surface acoustic wave signal, is the original signal, is the time-dependent echo coefficient, Delayed for the original signal The value after the time unit, For noise, is the echo delay;

[0026] The surface acoustic wave signal is input into the composite adaptive filter and the weight coefficient vector For the input signal vector Perform weighted summation to obtain the output of the composite adaptive filter , the expression is:

[0027] ,

[0028] In the formula, To conjugate transpose a complex matrix, is a positive integer that determines the number of filters working in parallel in the composite filter. is the input signal vector, is the conjugate transpose of a complex weight coefficient vector;

[0029] According to the output of the composite adaptive filter and the SAW signal Determining the error signal , the error signal The expression is:

[0030] ,

[0031] In the formula, For a time-dependent and echo delay The function of For in time The filter output signal at time t;

[0032] Update the weight coefficient vector according to the preset adaptive mechanism , until the error signal When it is less than the preset threshold, the output is the final composite adaptive filter output , that is, the target surface acoustic wave signal, expressed as:

[0033] ,

[0034] In the formula, is the number of iterations, is the conjugate transpose of the weight coefficient vector of the k-th filter at the T-th iteration;

[0035] The adaptive mechanism updates the weight coefficient vector The expression is:

[0036] ,

[0037] In the formula, is the weight coefficient vector at time t+1, is the update amount of the weight coefficient vector at time t, is a time-dependent coefficient, To express the Lagrangian, is the third-order derivative of the function with respect to the variable w.

[0038] It should be noted that the calculation The expression is:

[0039] ,

[0040] In the formula, is the adaptive step size, is the input signal vector, is the complex conjugate of the error signal e(t), is the regularization parameter or high-order correction term, is the input signal vector The conjugate transpose of ;

[0041] calculate The expression is:

[0042] ,

[0043] In the formula, For in time The expected signal or target signal at the moment, is the conjugate transpose of the weight coefficient vector of the kth filter at time t, is the input signal vector of the kth filter at time t, is a positive integer exponent that specifies the norm of the error term, is a regularization parameter used to control the strength of the regularization term. is the weight coefficient vector of the kth filter at time t, is another positive integer exponent that specifies the norm of the weight coefficient norm term.

[0044] In this embodiment, the ILMS adaptive filtering algorithm is used to eliminate the self-interference problem. The adaptive filtering algorithm achieves efficient elimination of self-interference in the echo signal through a composite filter structure and high-order error correction, combined with dynamic step size adjustment and global optimization strategy. The time-dependent parameter adjustment in the algorithm enhances the stability and robustness of the system, while the integration of the signal history behavior improves the processing capability of delayed echoes. In addition, through the high-order dynamic adjustment mechanism and multi-objective optimization of the third-order gradient, the algorithm controls the model complexity while reducing the error, ensuring stable filtering performance under extreme conditions.

[0045] Step S102: demodulate the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0046] In this step, it is assumed that the function expression of the target surface acoustic wave signal is:

[0047] ,

[0048] In the formula, is the amplitude, is the signal frequency, is the phase;

[0049] make ,but ;

[0050] The sampling frequency generated by AD is The sampling signal is used to sample the target surface acoustic wave signal to obtain the digital expression of the target surface acoustic wave signal. for:

[0051] ,

[0052] In the formula, is the amplitude signal, is the signal frequency, is the sampling frequency, is the phase signal;

[0053] Expressed as two orthogonal signals, we get:

[0054] ,

[0055] In the formula, is the discrete time index, is the value of the in-phase component at discrete time point i, is the value of the orthogonal component at discrete time point i;

[0056] Will and The multiplication results in a signal defined as The same-direction branch signal is expressed as:

[0057] ,

[0058] The high-frequency components in the same-direction branch signal are filtered out using a low-pass filter, and the expression is:

[0059] ,

[0060] Will and The multiplied signal is defined as The orthogonal branch signal is expressed as:

[0061] ,

[0062] The high-frequency components in the orthogonal branch signal are filtered out using a low-pass filter, and the expression is:

[0063] ,

[0064] according to and get After digital IQ demodulation, the complex number representation of the IQ quadrature branch is:

[0065] ,

[0066] In the formula, is the complex number representation of the signal at discrete time point i, is an imaginary unit;

[0067] Calculate the envelope signal composed of IQ orthogonal branches Amplitude information , the expression is:

[0068] ,

[0069] Will minus ,get:

[0070] ,

[0071] Will and Differentiate them respectively, and the differential expressions are:

[0072] ,

[0073] ,

[0074] In the formula, In-phase component The time derivative, is the time derivative of the phase, that is, the rate of change of the phase, is the orthogonal component Derivative with respect to time;

[0075] Will and Adding them together, we get:

[0076] ,

[0077] Will Divide by ,get:

[0078] ,

[0079] right Integrate to obtain the phase information of the target surface acoustic wave signal .

[0080] In this embodiment, the DC component in the signal is eliminated by subtracting two orthogonal signals and taking their derivatives respectively, and then the measured signal is obtained by dividing and integrating. The influence of the change of the DC component of the signal caused by the external environment can be ignored and the DC component can be completely eliminated.

[0081] In summary, the method of the present application obtains accurate demodulation data through the IMS adaptive filtering algorithm. The adaptive filtering algorithm realizes efficient elimination of self-interference in the echo signal through a composite filter structure and high-order error correction, combined with dynamic step size adjustment and global optimization strategy. The time-dependent parameter adjustment in the algorithm enhances the stability and robustness of the system, while the integration of the historical behavior of the signal improves the processing capability of delayed echoes. In addition, through the high-order dynamic adjustment mechanism and multi-objective optimization of the third-order gradient, the algorithm controls the model complexity while reducing the error, ensuring stable filtering performance under extreme conditions. The echo signal read by the reader is more resistant to interference and more accurate. The NQAM demodulation algorithm uses the method of subtracting two orthogonal signals and taking derivatives separately to eliminate the DC component in the signal, and then divides and integrates to obtain the signal to be measured. This algorithm does not need to consider the influence of the change of the DC component of the signal caused by the external environment, and completely eliminates the DC component.

[0082] See also Figure 2 , which shows a structural block diagram of a surface acoustic wave signal processing system based on an NQAM demodulation algorithm of the present application.

[0083] like Figure 2 As shown, the surface acoustic wave signal processing system 200 includes a processing module 210 and a demodulation module 220 .

[0084] Among them, the processing module 210 is configured to obtain a surface acoustic wave signal, perform interference removal processing on the surface acoustic wave signal based on the IMS adaptive filtering strategy, and obtain a target surface acoustic wave signal; the demodulation module 220 is configured to demodulate the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0085] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects are also applicable to Figure 2 The modules in it will not be described in detail here.

[0086] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the surface acoustic wave signal processing method based on the NQAM demodulation algorithm in any of the above method embodiments;

[0087] As an implementation mode, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0088] Acquire a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal;

[0089] The target surface acoustic wave signal is demodulated according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0090] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data created according to the use of the surface acoustic wave signal processing system based on the NQAM demodulation algorithm, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the surface acoustic wave signal processing system based on the NQAM demodulation algorithm via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0091] Figure 3 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3In the example, the connection through the bus is taken as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, the surface acoustic wave signal processing method based on the NQAM demodulation algorithm of the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the surface acoustic wave signal processing system based on the NQAM demodulation algorithm. The output device 340 may include display devices such as display screens.

[0092] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0093] As an implementation mode, the electronic device is applied to a surface acoustic wave signal processing system based on an NQAM demodulation algorithm, and is used for a client, and includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can:

[0094] Acquire a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an IMS adaptive filtering strategy to obtain a target surface acoustic wave signal;

[0095] The target surface acoustic wave signal is demodulated according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal.

[0096] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A surface acoustic wave signal processing method based on NQAM demodulation algorithm, characterized in that: include: Acquire a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an ILMS adaptive filtering strategy to obtain a target surface acoustic wave signal, wherein the acquiring a surface acoustic wave signal, and performing interference removal processing on the surface acoustic wave signal based on an ILMS adaptive filtering strategy to obtain a target surface acoustic wave signal comprises: A surface acoustic wave signal is obtained, wherein the expression of the surface acoustic wave signal is: ， In the formula, is the surface acoustic wave signal, is the original signal, is the time-dependent echo coefficient, Delayed for the original signal The value after the time unit, For noise, is the echo delay; The surface acoustic wave signal is input into the composite adaptive filter and the weight coefficient vector For the input signal vector Perform weighted summation to obtain the output of the composite adaptive filter , the expression is: ， In the formula, To conjugate transpose a complex matrix, is a positive integer that determines the number of filters working in parallel in the composite filter. is the input signal vector, is the conjugate transpose of a complex weight coefficient vector; According to the output of the composite adaptive filter and the SAW signal Determining the error signal , the error signal The expression is: ， In the formula, For a time-dependent and echo delay The function of is the filter output signal at time τ; Update the weight coefficient vector according to the preset adaptive mechanism , until the error signal When it is less than the preset threshold, the output is the final composite adaptive filter output , that is, the target surface acoustic wave signal, expressed as: ， In the formula, is the number of iterations, is the conjugate transpose of the weight coefficient vector of the k-th filter at the T-th iteration; The adaptive mechanism updates the weight coefficient vector The expression is: ， In the formula, is the weight coefficient vector at time t+1, is the update amount of the weight coefficient vector at time t, is a time-dependent coefficient, To express the Lagrangian, is the third-order derivative of the function with respect to the variable w; Demodulating the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal, wherein demodulating the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal includes: The sampling frequency generated by AD is The sampling signal is used to sample the target surface acoustic wave signal to obtain the digital expression of the target surface acoustic wave signal. for: ， In the formula, is the amplitude signal, is the signal frequency, is the sampling frequency, is the phase signal; Expressed as two orthogonal signals, we get: ， In the formula, is the discrete time index, is the value of the in-phase component at discrete time point i, is the value of the orthogonal component at discrete time point i; Will and The multiplication results in a signal defined as The same-direction branch signal is expressed as: ， The high-frequency components in the same-direction branch signal are filtered out using a low-pass filter, and the expression is: ， Will and The multiplied signal is defined as The orthogonal branch signal is expressed as: ， The high-frequency components in the orthogonal branch signal are filtered out using a low-pass filter, and the expression is: ， according to and get After digital IQ demodulation, the complex number representation of the IQ quadrature branch is: ， In the formula, is the complex number representation of the signal at discrete time point i, is an imaginary unit; Calculate the envelope signal composed of IQ orthogonal branches Amplitude information , the expression is: ， Will minus ,get: ， Will and Differentiate them respectively, and the differential expressions are: ， ， In the formula, In-phase component The time derivative, is the time derivative of the phase, that is, the rate of change of the phase, is the orthogonal component Derivative with respect to time; Will and Adding them together, we get: ， Will Divide by ,get: ， right Integrate to obtain the phase information of the target surface acoustic wave signal .

2. The method for processing surface acoustic wave signals based on NQAM demodulation algorithm according to claim 1, characterized in that: in, calculate The expression is: ， In the formula, is the adaptive step size, is the input signal vector, is the complex conjugate of the error signal e(t), is the regularization parameter or high-order correction term, is the input signal vector The conjugate transpose of .

3. The method for processing surface acoustic wave signals based on NQAM demodulation algorithm according to claim 1, characterized in that: calculate The expression is: ， In the formula, For in time t The expected signal or target signal at the moment, is the conjugate transpose of the weight coefficient vector of the kth filter at time t, is the input signal vector of the kth filter at time t, is a positive integer exponent that specifies the norm of the error term, is a regularization parameter used to control the strength of the regularization term. is the weight coefficient vector of the kth filter at time t, is another positive integer exponent that specifies the norm of the weight coefficient norm term.

4. A surface acoustic wave signal processing system based on NQAM demodulation algorithm, characterized in that: include: The processing module is configured to obtain a surface acoustic wave signal, and perform interference removal processing on the surface acoustic wave signal based on an ILMS adaptive filtering strategy to obtain a target surface acoustic wave signal, wherein the obtaining of the surface acoustic wave signal, and performing interference removal processing on the surface acoustic wave signal based on an ILMS adaptive filtering strategy to obtain a target surface acoustic wave signal comprises: A surface acoustic wave signal is obtained, wherein the expression of the surface acoustic wave signal is: ， In the formula, is the surface acoustic wave signal, is the original signal, is the time-dependent echo coefficient, Delayed for the original signal The value after the time unit, For noise, is the echo delay; The surface acoustic wave signal is input into the composite adaptive filter and the weight coefficient vector For the input signal vector Perform weighted summation to obtain the output of the composite adaptive filter , the expression is: ， In the formula, To conjugate transpose a complex matrix, is a positive integer that determines the number of filters working in parallel in the composite filter. is the input signal vector, is the conjugate transpose of a complex weight coefficient vector; According to the output of the composite adaptive filter and the SAW signal Determining the error signal , the error signal The expression is: ， In the formula, For a time-dependent and echo delay The function of is the filter output signal at time τ; Update the weight coefficient vector according to the preset adaptive mechanism , until the error signal When it is less than the preset threshold, the output is the final composite adaptive filter output , that is, the target surface acoustic wave signal, expressed as: ， In the formula, is the number of iterations, is the conjugate transpose of the weight coefficient vector of the kth filter at time T; The adaptive mechanism updates the weight coefficient vector The expression is: ， In the formula, is the weight coefficient vector at time t+1, is the update amount of the weight coefficient vector at time t, is a time-dependent coefficient, To express the Lagrangian, is the third-order derivative of the function with respect to the variable w; A demodulation module is configured to demodulate the target surface acoustic wave signal according to a preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal, wherein the demodulation of the target surface acoustic wave signal according to the preset NQAM demodulation algorithm to obtain phase information and amplitude information corresponding to the target surface acoustic wave signal includes: The sampling frequency generated by AD is The sampling signal is used to sample the target surface acoustic wave signal to obtain the digital expression of the target surface acoustic wave signal. for: ， In the formula, is the amplitude signal, is the signal frequency, is the sampling frequency, is the phase signal; Expressed as two orthogonal signals, we get: ， In the formula, is the discrete time index, is the value of the in-phase component at discrete time point i, is the value of the orthogonal component at discrete time point i; Will and The multiplication results in a signal defined as The same-direction branch signal is expressed as: ， The high-frequency components in the same-direction branch signal are filtered out using a low-pass filter, and the expression is: ， Will and The multiplied signal is defined as The orthogonal branch signal is expressed as: ， The high-frequency components in the orthogonal branch signal are filtered out using a low-pass filter, and the expression is: ， according to and get After digital IQ demodulation, the complex number representation of the IQ quadrature branch is: ， In the formula, is the complex number representation of the signal at discrete time point i, is an imaginary unit; Calculate the envelope signal composed of IQ orthogonal branches Amplitude information , the expression is: ， Will minus ,get: ， Will and Differentiate them respectively, and the differential expressions are: ， ， In the formula, In-phase component The time derivative, is the time derivative of the phase, that is, the rate of change of the phase, is the orthogonal component Derivative with respect to time; Will and Adding them together, we get: ， Will Divide by ,get: ， right Integrate to obtain the phase information of the target surface acoustic wave signal .

5. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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