High dynamic digital receiver adaptive interference rejection detection threshold determination system and method

Abstract

This invention relates to an adaptive anti-interference detection threshold determination system and method for a high dynamic range digital receiver, aiming to solve the problem of poor adaptability in existing traditional anti-interference detection threshold determination methods. The adaptive anti-interference detection threshold determination system for a high dynamic range digital receiver includes: a data buffer module, a Fourier transform processing module, a singular value decomposition module, and a detection threshold determination module; the data buffer module is connected to the Fourier transform processing module, the Fourier transform processing module is connected to the singular value decomposition module, and the singular value decomposition module is connected to the detection threshold determination module; the data buffer module is used to buffer received discrete data; the Fourier transform processing module is used to perform windowing processing and Fourier transform processing on the buffered data; the singular value decomposition module is used to perform singular value decomposition on the frequency domain data matrix after Fourier transform processing; and the detection threshold determination module is used to determine the adaptive anti-interference detection threshold.

Description

Technical Field

[0001] This invention relates to the field of anti-interference detection threshold determination technology, and specifically to an adaptive anti-interference detection threshold determination system and method for a high dynamic digital receiver. Background Technology

[0002] High dynamic range digital receivers require digital processing of received signals to recover the original information. When the power of narrowband interference signals is much greater than that of normal signals, relying solely on the system's processing gain to suppress narrowband interference is insufficient to achieve good performance. Therefore, anti-interference methods are needed to suppress narrowband interference, and the determination of the anti-interference detection threshold directly affects the anti-interference capability of the digital receiver. Traditional methods for determining the anti-interference detection threshold use a fixed spectral line detection threshold, i.e., selecting a fixed spectral line detection threshold based on measured values. This method is simple to implement but has poor adaptability. Therefore, a new method for determining the anti-interference detection threshold is urgently needed. Summary of the Invention

[0003] This invention provides an adaptive anti-interference detection threshold determination system and method for high dynamic digital receivers, aiming to solve the problem of poor adaptability of traditional anti-interference detection threshold determination methods in the prior art.

[0004] On the one hand, a high dynamic digital receiver adaptive anti-interference detection threshold determination system is provided, characterized in that it includes:

[0005] The system includes a data caching module, a Fourier transform processing module, a singular value decomposition module, and a detection threshold determination module; the data caching module is connected to the Fourier transform processing module, the Fourier transform processing module is connected to the singular value decomposition module, and the singular value decomposition module is connected to the detection threshold determination module.

[0006] The data caching module is used to: cache discrete data of the received signal;

[0007] The Fourier transform processing module is used to: perform windowing processing and Fourier transform processing on the cached data;

[0008] The singular value decomposition module is used to perform singular value decomposition on the frequency domain data matrix after Fourier transform processing.

[0009] The detection threshold determination module is used to determine the adaptive anti-interference detection threshold based on the singular values.

[0010] On the other hand, a method for determining the adaptive anti-interference detection threshold of a high dynamic digital receiver is provided, characterized by comprising:

[0011] The data buffer module buffers the discrete data of the received signal;

[0012] The Fourier transform processing module performs windowing and Fourier transform processing on the cached data.

[0013] The singular value decomposition module performs singular value decomposition on the frequency domain data matrix after Fourier transform processing;

[0014] The detection threshold determination module determines the adaptive anti-interference detection threshold based on the singular values.

[0015] The present invention provides an adaptive anti-interference detection threshold determination system and method for high dynamic digital receivers, which uses the singular values ​​of the frequency domain data matrix as a reference, and provides an effective adaptive anti-interference detection threshold determination system. Through the detection threshold determination system provided by the present invention, the anti-interference detection threshold can be adaptively determined based on discrete data pairs, and the determined adaptive anti-interference detection threshold value is accurate, thereby improving the anti-interference capability of the digital receiver. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of a high dynamic digital receiver adaptive anti-interference detection threshold determination system according to an embodiment of the present invention;

[0017] Figure 2 This is a flowchart illustrating the implementation of the adaptive anti-interference detection threshold determination method for a high dynamic digital receiver according to an embodiment of the present invention. Detailed Implementation

[0018] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Specific details such as particular system structures, models, and technical parameters mentioned in the following description are merely illustrative of the specific embodiments and not intended to limit the scope of protection of the present invention. Furthermore, content that should be known and understood by those skilled in the art will not be repeated here.

[0019] Additionally, it should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of the embodiments of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein.

[0020] In this embodiment of the invention, the problem of poor adaptability of traditional anti-interference detection threshold methods is solved, and an adaptive anti-interference detection threshold determination system is provided.

[0021] Based on the above description, this embodiment of the invention provides an adaptive anti-interference detection threshold determination system for a high dynamic digital receiver, characterized in that it includes: a data buffer module 11, a Fourier transform processing module 12, a singular value decomposition module 13, and a detection threshold determination module 14; the data buffer module functions to buffer discrete data of the received signal; the Fourier transform processing module functions to perform Fourier transform processing on the windowed data; the singular value decomposition module functions to perform singular value decomposition on the frequency domain data matrix; and the detection threshold determination module functions to determine the adaptive anti-interference detection threshold.

[0022] The system includes a data caching module, a Fourier transform processing module, a singular value decomposition module, and a detection threshold determination module; the data caching module is connected to the Fourier transform processing module, the Fourier transform processing module is connected to the singular value decomposition module, and the singular value decomposition module is connected to the detection threshold determination module.

[0023] The data caching module is used to: cache discrete data of the received signal;

[0024] The Fourier transform processing module is used to: perform windowing processing and Fourier transform processing on the cached data;

[0025] The singular value decomposition module is used to perform singular value decomposition on the frequency domain data matrix after Fourier transform processing.

[0026] The detection threshold determination module is used to determine the adaptive anti-interference detection threshold based on the singular values.

[0027] In practical implementation, the data caching module receives discrete data signals transmitted from external devices and caches the discrete data of the received signals. Specifically, it extracts cached data x(m), m = 1 to M / 4, forming data 1: x1(n); extracts cached data x(m), m = M / 4 + 1 to M / 2, forming data 2: x2(n); extracts cached data x(m), m = M / 2 + 1 to 3M / 4, forming data 3: x3(n); extracts cached data x(m), m = 3M / 4 + 1 to M, forming data 4: x4(n), where n is the data point index value of data 1 to data 4, n = 1 to N, N is the data length of data 1 to data 4, N = M / 4. Where m is the cached data point index value, m = 1 to M; M is the cached data length, M = f s ·τ,f s For data rate, f s Selection principle: f s ≥4f0, where f0 is the highest frequency of the received signal and τ is the duration of the buffered data.

[0028] In practice, the Fourier transform processing module performs time-domain multiplication operations on data 1 to data 4 with the Hamming window function w(n) respectively to obtain windowed data 1 to windowed data 4: The expression for the Hamming window function w(n) is: w(n) = 0.54 - 0.46cos[2π·(n+1) / N]. Then, the Fourier transform processing module performs Fourier transform processing on windowed data 1 to windowed data 4 respectively, obtaining... Frequency domain data X1(k), Frequency domain data X2(k), Frequency domain data X3(k) and The frequency domain data X4(k), X1(k), X2(k), X3(k) and X4(k) are all complex sequences, where k is the index value of the frequency domain data point, k = 1 to N.

[0029] In practical implementation, the singular value decomposition module defines vectors 1 to 4: α1 to α4 based on X1(k), X2(k), X3(k), and X4(k), where |·| represents the modulo operation of complex numbers. Vectors 1 to 4 are shown in the following equation:

[0030]

[0031]

[0032] The singular value decomposition module defines matrix A based on vectors 1 to 4: Matrix A is a 4×N matrix. Perform singular value decomposition on matrix A: A = UΣV T The singular values ​​σ1,σ2,…,σ of matrix A are obtained. L , where σ1>σ2>…>σ L >0, where L is the rank of matrix A. Here, U is a 4×N matrix, V is an N×N matrix, and Σ is an N×N diagonal matrix.

[0033] In practice, the detection threshold determination module uses a point-by-point comparison method to perform data rejection processing on |X1(k)|, |X2(k)|, |X3(k)|, and |X4(k)| respectively. Specifically, if |X1(k)|>1.2P0, the frequency domain data corresponding to the current frequency domain data point index value is rejected; if |X1(k)|<0.8P1, the frequency domain data corresponding to the current frequency domain data point index value is rejected; otherwise, X1(k) is not processed.

[0034] If |X2(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X2(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X2(k) is not processed.

[0035] If |X3(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X3(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X3(k) is not processed.

[0036] If |X4(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X4(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X4(k) is not processed. Here, P0 is the amplitude spectrum value of the signal with the maximum power when there is no interference, and P1 is the amplitude spectrum value of the signal with the minimum power when there is no interference. Both P0 and P1 can be obtained through theoretical calculation.

[0037] Polynomial curve fitting was performed on the four sets of frequency domain data after the removal process. The polynomial degree was set to m to obtain fitting curve 1 to fitting curve 4: f1(t) to f4(t), where t is the time parameter. Data was extracted at N points at equal intervals from f1(t) to f4(t) to obtain fitting data 1 to fitting data 4: g1(n) to g4(n).

[0038] Take the mean of all data in g1(n) to get mean 1: T1; take the mean of all data in g2(n) to get mean 2: T2; take the mean of all data in g3(n) to get mean 3: T3; take the mean of all data in g4(n) to get mean 4: T4;

[0039] Determine the adaptive anti-interference detection threshold ε: η is the attenuation coefficient, which can be taken as η = 0.732.

[0040] In summary, according to the embodiments of the present invention, by performing windowing and Fourier transform processing on the discrete signal, then performing singular value decomposition on the frequency domain data matrix after Fourier transform processing, and finally determining the adaptive anti-interference detection threshold, an accurate adaptive anti-interference detection threshold value can be determined, thereby improving the adaptability of the anti-interference detection threshold method.

[0041] Based on the above description, embodiments of the present invention provide a method for determining an adaptive anti-interference detection threshold for a high dynamic digital receiver, comprising:

[0042] S21. The data buffer module buffers the discrete data of the received signal.

[0043] In practical implementation, the data caching module receives discrete data signals transmitted from external devices and caches the discrete data of the received signals. Specifically, it extracts cached data x(m), m = 1 to M / 4, forming data 1: x1(n); extracts cached data x(m), m = M / 4 + 1 to M / 2, forming data 2: x2(n); extracts cached data x(m), m = M / 2 + 1 to 3M / 4, forming data 3: x3(n); extracts cached data x(m), m = 3M / 4 + 1 to M, forming data 4: x4(n), where n is the data point index value of data 1 to data 4, n = 1 to N, N is the data length of data 1 to data 4, N = M / 4. Where m is the cached data point index value, m = 1 to M; M is the cached data length, M = f s ·τ,f s For data rate, f s Selection principle: f s ≥4f0, where f0 is the highest frequency of the received signal and τ is the duration of the buffered data.

[0044] S22. The Fourier transform processing module performs windowing processing and Fourier transform processing on the cached data.

[0045] In practice, the Fourier transform processing module performs time-domain multiplication operations on data 1 to data 4 with the Hamming window function w(n) respectively to obtain windowed data 1 to windowed data 4: The expression for the Hamming window function w(n) is: w(n) = 0.54 - 0.46cos[2π·(n+1) / N]. Then, the Fourier transform processing module performs Fourier transform processing on windowed data 1 to windowed data 4 respectively, obtaining... Frequency domain data X1(k), Frequency domain data X2(k), Frequency domain data X3(k) and The frequency domain data X4(k), X1(k), X2(k), X3(k) and X4(k) are all complex sequences, where k is the index value of the frequency domain data point, k = 1 to N.

[0046] S23. The singular value decomposition module performs singular value decomposition on the frequency domain data matrix after Fourier transform processing.

[0047] In practical implementation, the singular value decomposition module defines vectors 1 to 4: α1 to α4 based on X1(k), X2(k), X3(k), and X4(k), where |·| represents the modulo operation of complex numbers. Vectors 1 to 4 are shown in the following equation:

[0048]

[0049]

[0050] The singular value decomposition module defines matrix A based on vectors 1 to 4: Matrix A is a 4×N matrix. Perform singular value decomposition on matrix A: A = UΣV T The singular values ​​σ1,σ2,…,σ of matrix A are obtained. L , where σ1>σ2>…>σ L >0, where L is the rank of matrix A. Here, U is a 4×N matrix, V is an N×N matrix, and Σ is an N×N diagonal matrix.

[0051] S24. The detection threshold determination module determines the adaptive anti-interference detection threshold based on the singular values.

[0052] In practice, the detection threshold determination module uses a point-by-point comparison method to perform data rejection processing on |X1(k)|, |X2(k)|, |X3(k)|, and |X4(k)| respectively. Specifically, if |X1(k)|>1.2P0, the frequency domain data corresponding to the current frequency domain data point index value is rejected; if |X1(k)|<0.8P1, the frequency domain data corresponding to the current frequency domain data point index value is rejected; otherwise, X1(k) is not processed.

[0053] If |X2(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X2(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X2(k) is not processed.

[0054] If |X3(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X3(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X3(k) is not processed.

[0055] If |X4(k)|>1.2P0, discard the frequency domain data corresponding to the current frequency domain data point index value; if |X4(k)|<0.8P1, discard the frequency domain data corresponding to the current frequency domain data point index value; otherwise, X4(k) is not processed. Here, P0 is the amplitude spectrum value of the signal with the maximum power when there is no interference, and P1 is the amplitude spectrum value of the signal with the minimum power when there is no interference. Both P0 and P1 can be obtained through theoretical calculation.

[0056] Polynomial curve fitting was performed on the four sets of frequency domain data after the removal process. The polynomial degree was set to m to obtain fitting curve 1 to fitting curve 4: f1(t) to f4(t), where t is the time parameter. Data was extracted at N points at equal intervals from f1(t) to f4(t) to obtain fitting data 1 to fitting data 4: g1(n) to g4(n).

[0057] Take the mean of all data in g1(n) to get mean 1: T1; take the mean of all data in g2(n) to get mean 2: T2; take the mean of all data in g3(n) to get mean 3: T3; take the mean of all data in g4(n) to get mean 4: T4;

[0058] Determine the adaptive anti-interference detection threshold ε: η is the attenuation coefficient, which can be taken as η = 0.732.

[0059] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A high dynamic range digital receiver adaptive interference rejection detection threshold determination system, characterized by, The method comprises the following steps: The data buffering module is connected with the Fourier transform processing module, the Fourier transform processing module is connected with the singular value decomposition module, and the singular value decomposition module is connected with the detection threshold determination module; The data buffering module is used for buffering discrete data of a received signal; The Fourier transform processing module is used for performing windowing processing and Fourier transform processing on the buffered data; The singular value decomposition module is used for performing singular value decomposition on the frequency domain data matrix after the Fourier transform processing; The detection threshold determination module is used for determining an adaptive anti-interference detection threshold according to singular values; The data buffering module is specifically used for: The data buffering module extracts buffered data x(m) according to a set buffered data point index value m, to generate first buffered data x(m1), second buffered data x(m2), third buffered data x(m3), and fourth buffered data x(m4); Wherein, m1=1~M, m2=M / 4+1~M / 2, m3=M / 2+1~3M / 4, m4=3M / 4+1~M, M is the length of the cache data, M=f s ·τ, f s Data rate, f s ≥4f0, f0 is the highest frequency of the received signal τ is the length of the cache data duration; The Fourier transform processing module is specifically used for: The Fourier transform processing module performs time domain multiplication operation on the first buffered data, the second buffered data, the third buffered data, and the fourth buffered data respectively with a Hamming window function to generate first windowed data, second windowed data, third windowed data, and fourth windowed data, wherein the expression of the Hamming window function w(n) is w(n)=0.54-0.46cos[2π·(n+1) / N], n is a data point index value of the windowed data, and N is the data length of the windowed data; The Fourier transform processing module performs Fourier transform processing on the first windowed data, the second windowed data, the third windowed data, and the fourth windowed data respectively to generate first frequency domain data X1(k), second frequency domain data X2(k), third frequency domain data X3(k), and fourth frequency domain data X4(k), wherein k is a frequency domain data point index value, and k=1~N; The singular value decomposition module is specifically used for: The singular value decomposition module defines a first vector α1, a second vector α2, a third vector α3, and a fourth vector α4 according to the first frequency domain data X1(k), the second frequency domain data X2(k), the third frequency domain data X3(k), and the fourth frequency domain data X4(k); The singular value decomposition module defines a matrix A: wherein the matrix A is a 4 x N matrix; The singular value decomposition module performs singular value decomposition on the matrix A: A = U∑V T where U is a 4 x N matrix, V is an N x N matrix, and ∑ is an N x N diagonal matrix; where σ1, σ2,..., σ L are singular values of the matrix A, σ1> σ2>... > σ L > 0, where L is the rank of the matrix A.

2. The system of claim 1, wherein, The detection threshold determination module is specifically used for The detection threshold determination module judges the first frequency domain data X1(k), the second frequency domain data X2(k), the third frequency domain data X3(k), and the fourth frequency domain data X4(k) respectively: If |X1(k)|>1.2P0, the frequency domain data corresponding to the first frequency domain data index value is removed; if |X1(k)|<0.8P1, the frequency domain data corresponding to the first frequency domain data index value is removed; otherwise, X1(k) is not processed; wherein |·| represents a complex modulus operation, P0 is the amplitude spectrum line value of the maximum power signal without interference, and P1 is the amplitude spectrum line value of the minimum power signal without interference. If |X2(k)|>1.2P0, the frequency domain data corresponding to the second frequency domain data point index value is eliminated; if |X2(k)|<0.8P1, the frequency domain data corresponding to the second frequency domain data point index value is eliminated; otherwise, X2(k) is not processed; If |X3(k)|>1.2P0, the frequency domain data corresponding to the third frequency domain data point index value is eliminated; if |X3(k)|<0.8P1, the frequency domain data corresponding to the third frequency domain data point index value is eliminated; otherwise, X3(k) is not processed; If |X4(k)|>1.2P0, the frequency domain data corresponding to the fourth frequency domain data point index value is eliminated; if |X4(k)|<0.8P1, the frequency domain data corresponding to the fourth frequency domain data point index value is eliminated; otherwise, X4(k) is not processed; The detection threshold determination module performs polynomial curve fitting on the four groups of frequency domain data after the elimination processing, and the polynomial degree is set to m, to generate a first fitting curve f1(t), a second fitting curve f2(t), a third fitting curve f3(t), and a fourth fitting curve f4(t), wherein t is a time parameter; The detection threshold determination module performs N-point equidistant data extraction on the first fitting curve f1(t), the second fitting curve f2(t), the third fitting curve f3(t), and the fourth fitting curve f4(t) respectively, to generate first fitting data g1(n), second fitting data g2(n), third fitting data g3(n), and fourth fitting data g4(n); The detection threshold determination module takes the mean of all data in the first fitting data g1(n) to obtain a first mean T1, takes the mean of all data in the second fitting data g2(n) to obtain a second mean T2, takes the mean of all data in the third fitting data g3(n) to obtain a third mean T3, and takes the mean of all data in the fourth fitting data g4(n) to obtain a fourth mean T4; and the adaptive anti-interference detection threshold is determined according to the first, second, third and fourth means wherein η is a coefficient of attenuation, η = 0.

732.

3. A method for determining an adaptive interference rejection test threshold for a high dynamic range digital receiver, characterized in that, It comprises: The data buffer module buffers the discrete data of the received signal; The Fourier transform processing module performs windowing and Fourier transform processing on the buffered data; The singular value decomposition module performs singular value decomposition on the frequency domain data matrix after Fourier transform processing; The detection threshold determination module determines the adaptive anti-interference detection threshold according to the singular value; The data buffer module buffers the discrete data of the received signal, and specifically comprises: The data buffer module extracts the buffered data x(m) according to the set buffer data point index value m, to generate first buffered data x(m1), second buffered data x(m2), third buffered data x(m3), and fourth buffered data x(m4); Wherein, m1=1~M, m2=M / 4+1~M / 2, m3=M / 2+1~3M / 4, m4=3M / 4+1~M, M is the length of cache data, M=f s ·τ, f s Data rate, f s ≥4f0, f0 is the highest frequency of the received signal τ is the length of cache data duration; The Fourier transform processing module performs windowing and Fourier transform processing on the buffered data, and specifically comprises: The Fourier transform processing module performs time domain multiplication operation on the first buffered data, the second buffered data, the third buffered data, and the fourth buffered data with a Hamming window function respectively, to generate first windowed data, second windowed data, third windowed data, and fourth windowed data, wherein the expression of the Hamming window function w(n) is: w(n)=0.54-0.46cos[2π·(n+1) / N], n is the data point index value of the windowed data, and N is the data length of the windowed data. The Fourier transform processing module performs Fourier transform processing on the first windowed data, the second windowed data, the third windowed data, and the fourth windowed data respectively to generate first frequency domain data X1(k), second frequency domain data X2(k), third frequency domain data X3(k), and fourth frequency domain data X4(k), where k is a frequency domain data point index value, and k=1~N; The singular value decomposition module performs singular value decomposition on the frequency domain data matrix after Fourier transform processing, and specifically includes: The singular value decomposition module defines a first vector α1, a second vector α2, a third vector α3, and a fourth vector α4 according to the first frequency domain data X1(k), the second frequency domain data X2(k), the third frequency domain data X3(k), and the fourth frequency domain data X4(k); The singular value decomposition module defines a matrix A: wherein the matrix A is a 4 x N matrix; The singular value decomposition module performs singular value decomposition on the matrix A: A = U∑V T where U is a 4 x N matrix, V is an N x N matrix, and ∑ is an N x N diagonal matrix; where σ1, σ2,..., σ L are singular values of the matrix A, σ1> σ2>... > σ L > 0, where L is the rank of the matrix A.

4. The method of claim 3, wherein, The detection threshold determination module determines the adaptive anti-interference detection threshold according to the singular value, and specifically includes: The detection threshold determination module judges the first frequency domain data X1(k), the second frequency domain data X2(k), the third frequency domain data X3(k), and the fourth frequency domain data X4(k) respectively: If |X1(k)|>1.2P0, the frequency domain data corresponding to the first frequency domain data index value is removed; if |X1(k)|<0.8P1, the frequency domain data corresponding to the first frequency domain data index value is removed; otherwise, X1(k) is not processed; where |·| represents a complex modulus operation, P0 is the amplitude spectrum line value of the maximum power signal without interference, and P1 is the amplitude spectrum line value of the minimum power signal without interference; If |X2(k)|>1.2P0, the frequency domain data corresponding to the second frequency domain data point index value is removed; if |X2(k)|<0.8P1, the frequency domain data corresponding to the second frequency domain data point index value is removed; otherwise, X2(k) is not processed; If |X3(k)|>1.2P0, the frequency domain data corresponding to the third frequency domain data point index value is removed; if |X3(k)|<0.8P1, the frequency domain data corresponding to the third frequency domain data point index value is removed; otherwise, X3(k) is not processed; If |X4(k)|>1.2P0, the frequency domain data corresponding to the fourth frequency domain data point index value is removed; if |X4(k)|<0.8P1, the frequency domain data corresponding to the fourth frequency domain data point index value is removed; otherwise, X4(k) is not processed; The detection threshold determination module performs polynomial curve fitting on the four groups of frequency domain data after the removal processing respectively, and sets the polynomial degree to m to generate a first fitting curve f1(t), a second fitting curve f2(t), a third fitting curve f3(t), and a fourth fitting curve f4(t), where t is a time parameter; The detection threshold determination module performs polynomial curve fitting on the four groups of frequency domain data after the removal processing respectively, and sets the polynomial degree to m to generate a first fitting curve f1(t), a second fitting curve f2(t), a third fitting curve f3(t), and a fourth fitting curve f4(t), where t is a time parameter; The detection threshold determination module respectively performs N-point equidistant data extraction on the first fitting curve f1(t), the second fitting curve f2(t), the third fitting curve f3(t), and the fourth fitting curve f4(t), to generate first fitting data g1(n), second fitting data g2(n), third fitting data g3(n), and fourth fitting data g4(n); The detection threshold determination module takes the mean of all data in the first fitting data g1(n) to obtain a first mean T1, takes the mean of all data in the second fitting data g2(n) to obtain a second mean T2, takes the mean of all data in the third fitting data g3(n) to obtain a third mean T3, and takes the mean of all data in the fourth fitting data g4(n) to obtain a fourth mean T4; and the adaptive anti-interference detection threshold is determined according to the first, second, third and fourth means wherein η is a coefficient of attenuation, η = 0.732.

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