Method and device for detecting known signals through PSER based on matrix partitioning

Abstract

The embodiment of this specification discloses a method and device for detecting known signals through PSER based on matrix partitioning. The method includes: determining the frequency band of interest of the known signal to be detected according to the frequency domain distribution of the known signal to be detected; the known signal is a signal that determines the time domain and frequency domain characteristics; predicting the noise variance of the known signal to be detected to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands; generating an M matrix according to the various levels of items in the cumulative distribution function; determining the numerical calculation range of the M matrix according to a preset partitioning method and a preset error control limit; obtaining the values ​​of various levels of items within the numerical calculation range according to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands, and accumulating the values ​​of various levels of items within the numerical calculation range to obtain the detection rate of the known signal; adjusting the frequency band of interest according to the detection rate to obtain the best detection rate, and using the frequency band corresponding to the best detection rate as the detection sub-band to realize the detection of the known signal.

Description

Technical Field

[0001] The present specification relates to the field of signal detection technology, and in particular to a method and device for detecting a known signal through PSER based on matrix partitioning. Background Art

[0002] With the development of information technology and society, corresponding results can be obtained through signal detection for various monitoring aspects such as equipment fault monitoring and earthquake monitoring. Therefore, signal detection constitutes an important and inevitable link in production and life.

[0003] For monitoring signals such as sensor signals and vibration signals, they generally have the characteristics of high sensitivity, complex noise components, and large data volume. When conventional signal detection methods such as energy detection method, matched filter detection method, cyclostationary feature detection method, and wavelet detection method are used to detect signals, due to the uncertainty of the noise in the signal, the fluctuation rate of the detection rate is large, the detection accuracy is poor, and the detection time is long. In order to solve the problems existing in conventional detection methods, the power spectrum sub-band energy ratio (Power spectrum Sub-band Energy Ratio, referred to as PSER) is currently used to detect signals. This method can reduce the fluctuation of the detection rate relative to other methods under the condition of noise uncertainty. However, since PSER obeys the double non-central beta distribution, its cumulative distribution function has no analytical form, and its probability can only be calculated by numerical calculation. The existing methods based on direct calculation and Laguerre polynomial calculation require the accumulation of infinite technology, which makes it impossible to guarantee both numerical accuracy and operation time, thereby consuming a large amount of computing resources and computing time in the signal detection process.

[0004] Therefore, a signal detection method that improves signal detection accuracy and signal detection speed is needed. Summary of the invention

[0005] One or more embodiments of the present specification provide a method for detecting a known signal through PSER based on matrix partitioning, which is used to solve the following technical problem: how to provide a signal detection method that improves signal detection accuracy and signal detection speed.

[0006] One or more embodiments of this specification adopt the following technical solutions:

[0007] One or more embodiments of the present specification provide a method for detecting a known signal through a PSER based on matrix partitioning, the method comprising:

[0008] Determine the frequency band of interest of the known signal to be detected according to the frequency domain distribution of the known signal to be detected; wherein the known signal is a signal with predetermined time domain and frequency domain characteristics;

[0009] Predicting the noise variance of the detection environment in which the known signal to be detected is located, so as to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands;

[0010] Generate an M matrix according to the number of items at each level in the cumulative distribution function of the preset sub-band energy proportion;

[0011] Determine the numerical calculation range of the M matrix according to a preset division method and a preset error control limit;

[0012] According to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, the value of each series item in the numerical calculation range of the M matrix is ​​obtained, and the value of each series item in the numerical calculation range is accumulated to obtain the detection rate of the known signal;

[0013] According to the detection rate, the frequency band of interest is repeatedly adjusted, and the best detection rate of the known signal is calculated to obtain the best detection rate, so as to realize signal detection of the known signal according to the frequency band corresponding to the best detection rate as the detection sub-frequency band.

[0014] Optionally, in one or more embodiments of the present specification, predicting the noise variance of the detection environment in which the known signal to be detected is located to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands specifically includes:

[0015] If the noise variance of the detection environment of the known signal to be detected is predicted to be σ 2 , and obtain the energy of the noise-free signal as E, the energy occupied by the sub-band as E1, the energy occupied by other spectral lines as E2, and the number of spectral lines as L;

[0016] The ratio of the energy of the effective signal in the sub-band of interest to the noise energy of a spectral line in the remaining band is taken as the signal-to-noise ratio δ1 in the band of interest; wherein δ1=E1 / (Lσ 2 ),

[0017] The ratio of the energy of the remaining signal after removing the effective signal of the sub-band of interest to the noise energy of a spectral line in the remaining band is taken as the signal-to-noise ratio δ2 of the remaining band; wherein δ2=E2 / (Lσ 2 ).

[0018] Optionally, in one or more embodiments of the present specification, generating an M matrix according to the number of items at each level in the cumulative distribution function of the preset sub-band energy proportion specifically includes:

[0019] Represent each series term based on a preset series term formula, and use the sum of each said series term as the cumulative distribution function of the preset sub-band energy ratio; wherein, the preset series term formula is:

[0020]

[0021] where L j,l is the series term of the cumulative distribution function, a and b are integers greater than 0, j and l are integers greater than or equal to 0, x represents the probability density function when the signal exists and 0 < x ≤ 1; δ1 ≥ 0, δ2 ≥ 0; the probability distribution of the signal to be detected is a double non-central beta distribution; the cumulative distribution function is: B(x; a, b; δ1, δ2); I x is the regular beta function, N is the number of spectral lines, and d is the region of interest;

[0022] Use the subscript j of each series term L j,l in the cumulative distribution function as the row subscript, and the subscript l as the column subscript, so as to construct each said series term L j,l into the M matrix.

[0023] Optionally, in one or more embodiments of this specification, determining the numerical calculation range of the M matrix according to the preset partitioning method and the preset error control limit specifically includes:

[0024] Partition the M matrix according to the preset partitioning method to obtain a preset number of matrix sub-regions;

[0025] Determine the numerical calculation range of the M matrix according to the preset error control limit of the preset number of matrix sub-regions;

[0026] Among them, partitioning the M matrix according to the preset partitioning method to obtain a preset number of matrix sub-regions specifically includes:

[0027] Partition the region related to the numerical calculation of the cumulative distribution function into initial matrix sub-regions;

[0028] Determine the boundary row and boundary column of the initial matrix sub-region, and based on the boundary column, determine the preset column outside the column where the initial matrix sub-region is located as the boundary between the initial matrix sub-region and the first matrix sub-region, determine the series terms in the boundary and in the same row as the initial sub-matrix, and use the region formed by these series terms as the first matrix sub-region;

[0029] Based on the boundary row, determine the coverage area of the row where the initial matrix sub-region is located, and use the series terms outside the coverage area as the second matrix sub-region.

[0030] Optionally, in one or more embodiments of the present specification, determining the numerical calculation range of the M matrix according to a preset division method and a preset error control limit specifically includes:

[0031] The first cumulative sum of the series items in the preset fixed row is determined according to the preset first formula and the preset second formula; wherein the preset first formula is: x (a,b-1) x (a, b)≤1, the preset second formula is:

[0032] Based on the first cumulative sum, the sum of the series terms included in the delimiting row and after the delimiting row is determined as the upper limit of the error of each series term in the second matrix sub-region; wherein the upper limit of the error of each series term in the second matrix sub-region is less than the preset error control limit ε 1，2 ;

[0033] According to the error upper limit of the second matrix sub-region and the preset error control limit ε 1，2 , determine the number of the boundary rows;

[0034] A plurality of series items in the M matrix are intercepted, and the sum of the plurality of series items is obtained, so as to determine the upper limit of the error of each row in the first matrix sub-region according to the preset theoretical value, the sum of the plurality of series items and the preset first formula; wherein the upper limit of the error of each row in the first matrix sub-region is less than the preset error control limit ε 1，1 ;

[0035] The boundaries of each row are determined according to the upper error limits of each row, and the coverage range formed by the number of the boundary rows and the boundaries of each row is used as the numerical calculation range of the M matrix.

[0036] Optionally, in one or more embodiments of the present specification, obtaining the value of each of the series items within the numerical calculation range of the M matrix according to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands specifically includes:

[0037] The signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands are input into the preset series term formula to obtain the value of each of the series terms within the numerical calculation range of the M matrix.

[0038] Optionally, in one or more embodiments of the present specification, the dividing the M matrix according to a preset division method to obtain a preset number of matrix sub-regions M matrix further includes:

[0039] Dividing a region associated with data calculation of the cumulative distribution function into initial matrix sub-regions; ​

[0040] Determine the boundary row and the boundary column of the initial matrix sub-region, and determine the coverage area of ​​the column where the initial matrix sub-region is located based on the boundary column, and form a first matrix region based on the number of items at all levels outside the coverage area;

[0041] Based on the demarcation row, a preset row outside the row where the initial matrix sub-region is located is determined, and the series items in the same column as the initial sub-matrix, and the area formed by the series items is used as the second matrix sub-region; wherein the preset rows of each column in the second matrix sub-region are different.

[0042] Optionally, in one or more embodiments of the present specification, determining the numerical calculation range of the M matrix according to a preset division method and a preset error control limit specifically includes:

[0043] The second cumulative sum of each of the series items in the preset fixed column is determined according to a preset third formula; wherein the preset third formula is: x (a,b)>I x (a+1,b);

[0044] According to the preset first formula and the second cumulative sum, the third cumulative sum of the series items of the preset column and after the preset column is determined, and the third cumulative sum is used as the upper limit of the error of the items at each level in the first matrix sub-region; wherein the upper limit of the error of the items at each level in the first matrix sub-region is less than the preset control limit ε 2，1 ;

[0045] According to the error upper limit of the second matrix sub-region and the preset control limit ε 2，1 Searching the number of columns in sequence to determine the number of the preset columns;

[0046] A plurality of series items in the preset fixed columns in the M matrix are intercepted, and the sum of the plurality of series items is obtained, so as to determine the upper limit of the error of each column in the second matrix sub-region according to the preset theoretical value, the sum of the plurality of series items and the preset third formula; wherein the upper limit of the error of each column in the second matrix sub-region is less than the preset error control limit ε 2，2 ;

[0047] According to the upper limit of the error of each column in the second matrix sub-region, the boundary of each column is determined, and the boundary of each column and the number of the preset columns are combined to determine the numerical calculation range of the M matrix.

[0048] Optionally, in one or more embodiments of the present specification, repeatedly adjusting the frequency band of interest according to the detection rate, and calculating and obtaining the best detection rate of the known signal, so as to implement signal detection for the known signal according to the frequency band corresponding to the best detection rate as a detection sub-frequency band, specifically includes:

[0049] Sampling the known signal to be detected to obtain a sampled signal, and acquiring a power spectrum of the sampled signal;

[0050] Determine the detection threshold of the known signal to be detected according to the spectral lines corresponding to the preset frequency band of interest, the number of spectral lines in the power spectrum, the preset signal false detection rate and the preset detection threshold formula of the signal to be detected;

[0051] The initial detection rate of the detected known signal is obtained based on a preset detection rate formula; wherein the preset detection rate formula is: Among them, P d represents the initial detection rate, η PSER represents the detection threshold, N represents the number of spectral lines in the power spectrum, k represents the starting spectral line of the frequency band of interest, d represents the ending spectral line of the frequency band of interest, and B d,N (k) represents the cumulative distribution function of the frequency band of interest, and H1 indicates the presence of a signal;

[0052] The frequency band of interest is adjusted to obtain an updated detection rate. If the updated detection rate is greater than the initial detection rate, the updated detection rate is used as the optimal detection rate, and the frequency band corresponding to the optimal detection rate is used as the detection sub-band to achieve signal detection for the known signal.

[0053] One or more embodiments of the present specification provide a device for detecting a known signal through a PSER based on matrix partitioning, including:

[0054] at least one processor; and,

[0055] a memory communicatively connected to the at least one processor; wherein,

[0056] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0057] Obtain the series term of the cumulative distribution function of the signal to be detected under the probability distribution of the corresponding sub-band energy proportion;

[0058] Based on each of the series items, an M matrix of a cumulative distribution function under a probability distribution of a sub-band energy proportion corresponding to the signal to be detected is generated;

[0059] Based on a preset division method, the M matrix is ​​divided to obtain a preset number of matrix sub-regions;

[0060] Determining an upper error limit of the cumulative distribution function according to series items within the preset number of matrix sub-regions, so as to obtain a calculation accuracy of the cumulative distribution function based on the upper error limit;

[0061] A PSER cumulative distribution function matching the preset monitoring accuracy of the signal to be detected is selected according to the calculation accuracy, so as to monitor the power spectrum sub-band energy proportion of the signal to be detected based on the PSER cumulative distribution function to obtain a monitoring result of the signal to be detected.

[0062] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0063] In the embodiment of the present specification, the M matrix is ​​divided by obtaining the series term of the cumulative distribution function under the probability distribution of the sub-band energy proportion. After setting the control limit of the first matrix sub-region and the error control limit of the second matrix sub-region, the control of the upper limit of the overall error of the M matrix can be achieved by controlling the error control limit of the first matrix sub-region and the error control limit of the second matrix sub-region, thereby achieving the control of the calculation range of the PSER cumulative distribution function. It avoids the waste of calculation cost and time cost caused by first calculating an infinite series and then determining the calculation range in the prior art. The power spectrum sub-band energy proportion of the signal to be detected is monitored by the PSER cumulative distribution function, so as to quickly and accurately obtain the detection result of the signal to be detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0065] Figure 1 A flowchart of a method for detecting a known signal through PSER based on matrix partitioning provided in an embodiment of this specification;

[0066] Figure 2 A schematic diagram of matrix sub-region division of an M matrix provided in an embodiment of this specification;

[0067] Figure 3 A schematic diagram of matrix sub-region division of another M matrix provided in an embodiment of this specification;

[0068] Figure 4A schematic diagram of the internal structure of a device for detecting known signals through PSER based on matrix partitioning provided in an embodiment of this specification. DETAILED DESCRIPTION

[0069] The embodiments of this specification provide a method and device for detecting a known signal through a PSER based on matrix partitioning.

[0070] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0071] like Figure 1 As shown, the embodiment of this specification provides a schematic flow chart of a method for detecting known signals through PSER based on matrix partitioning. In the scenario of monitoring signals, the embodiment of this application is applied to execute the solution in this specification through the server or each execution unit in each scenario.

[0072] like Figure 1 As shown, the method comprises the following steps:

[0073] S101: Determine a frequency band of interest of the known signal to be detected according to the frequency domain distribution of the known signal to be detected; wherein the known signal is a signal with predetermined time domain and frequency domain characteristics.

[0074] Existing signal detection methods include time domain energy detection method, full spectrum energy detection method, local spectrum energy detection method, matched filtering method, cyclostationary characteristic method, covariance absolute method, etc. The current time domain energy monitoring method takes the least time to detect, but its detection performance is poor, it is greatly affected by noise uncertainty, and it needs to pre-estimate the noise variance. The local spectrum energy method takes more time to detect, but its detection performance is average, it is less affected by noise uncertainty, and it requires more prior information. Not only does it need to estimate the noise variance, but it also needs to know the sub-band of the signal to be measured. The matched filtering method takes the least time to detect and has the best detection performance, but its detection performance is greatly affected by noise uncertainty and requires more prior information. The cyclostationary characteristic method does not require prior information, is less affected by noise uncertainty, and has better detection performance, but it requires the most detection time. The covariance absolute value method does not require prior information, and its detection performance is average, but it takes more time to detect and is greatly affected by noise uncertainty. Therefore, none of the above methods in the prior art have the characteristics of good detection performance, applicability to noise uncertainty, low signal-to-noise ratio environment without much prior information, and short detection time.

[0075] PSER is the ratio of the energy of a partial power spectrum to the energy of the entire power spectrum. Its numerator and denominator can partially offset the influence of the noise variance. Therefore, in a noise uncertain environment, the detection performance of the signal based on PSER fluctuates less than other signal detection methods in the prior art. However, since PSER obeys the non-central beta distribution under the condition of a signal, its cumulative distribution function has no analytical form, and its probability can only be calculated by numerical calculation. In the existing method, the cumulative distribution function of the double non-central beta is calculated by direct calculation or by using Laguerre polynomials. Both methods in the prior art require cumulative calculation of infinite series. Since the actual calculation cannot be performed infinitely, determining the range of calculation is a prerequisite for numerical calculation. The direct solution method requires predetermining the number of rows and columns involved in the calculation, while the Laguerre polynomial needs to determine the value range of j. If the preset calculation range is too small, the calculation result will be too small, and if it is too large, it will waste computing resources. In order to automatically determine the calculation range and perform calculations according to the calculation accuracy requirements in the embodiments of this specification, firstly, since there is a close relationship between the spectrum, power spectrum and PSER, the statistical characteristics of the spectrum are the basis for obtaining the statistical characteristics of the power spectrum, and the statistical characteristics of the power spectrum are the basis for studying the statistical characteristics of the PSER. Therefore, the frequency domain distribution of the signal to be detected is first obtained to predict the noise power of the signal to be detected. Taking Gaussian white noise as an example, the spectrum of Gaussian white noise is for:

[0076]

[0077] The power spectrum p(k) is: According to the frequency domain distribution of the known signal to be detected, the d spectral lines starting from the kth spectral line are determined as the frequency band region of interest, so as to perform subsequent analysis and processing based on the frequency band region of interest. It should be noted that the known signal is a signal with predetermined time domain and frequency domain characteristics, such as the above-mentioned Gaussian white noise.

[0078] S102: predicting the noise variance of the detection environment in which the known signal to be detected is located, so as to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands.

[0079] Since the signal-to-noise ratio affects the detection performance of the signal, in order to facilitate the analysis of the signal, in one or more embodiments of the present specification, the noise variance of the detection environment in which the known signal to be detected is located is first predicted to obtain the signal-to-noise ratio within the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands.

[0080] In one or more embodiments of the present specification, predicting the noise variance of the detection environment in which the known signal to be detected is located to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio of the remaining frequency bands specifically includes the following steps:

[0081] If the noise variance of the detection environment where the known signal to be detected is located is predicted as σ 2 , and the energy of the noise-free signal is obtained as E, the energy occupied by the sub-band is E1, the energy occupied by other spectral lines is E2, and the number of spectral lines is L, then the ratio of the energy of the effective signal in the sub-band of interest to the noise energy of one spectral line in the remaining band is used as the signal-to-noise ratio δ1 in the band of interest; it should be noted that: δ1 = E1 / (Lσ 2 ), after removing the effective signal in the sub-band of interest, the ratio of the energy of the remaining signal to the noise energy of one spectral line in the remaining band is used as the signal-to-noise ratio δ2 of the remaining band; among them, it should be noted that δ2 = E2 / (Lσ 2 ).

[0082] S103: Generate the M matrix according to each series term in the cumulative distribution function of the preset sub-band energy ratio. In order to avoid pre-determining the number of rows and columns involved in the calculation in the existing method, in this application, the M matrix is generated according to each series term in the cumulative distribution function of the preset sub-band energy ratio, so as to automatically determine the calculation range corresponding to the accuracy based on the division of the M matrix in the subsequent process. In one or more embodiments of this specification, generating the M matrix according to each series term in the cumulative distribution function of the preset sub-band energy ratio specifically includes the following steps:

[0083] Represent each series term based on the preset series term formula, and use the sum of each series term as the cumulative distribution function of the preset sub-band energy ratio; among them, the preset series term formula is:

[0084] Among them, it should be noted that: L j,l represents the series term of the cumulative distribution function, a and b represent the real part and the imaginary part of the spectral line of the spectrum, and a and b are integers greater than 0, j and l are integers greater than or equal to 0, x represents the probability density function when the signal exists and 0 < x ≤ 1; δ1 ≥ 0, δ2 ≥ 0; the known signal to be detected has a double non-central beta distribution in the corresponding probability distribution, I x is the regular beta function, the cumulative distribution function is: B(x; a, b; δ1, δ2); N is the number of spectral lines, d is the region of interest; use the subscript j of each series term L j,l in the cumulative distribution function as the row subscript, and the subscript l as the column subscript, so as to construct each series term L j,l into the M matrix.

[0085] According to representing each series term, sum each series term to obtain the cumulative sum of the series terms, and use the cumulative sum as the cumulative distribution function; among them, the cumulative distribution function is: The terms L at all levels in the cumulative distribution function j,l The subscript j is used as the row subscript and the subscript l is used as the column subscript, so that the number of items L at each level j,l Constructed into an M matrix. That is, the M matrix It can be understood that the cumulative distribution function obtained by the preset summation formula is the cumulative sum of all elements in the M matrix. Theoretically, there are infinite elements in the M matrix, which means that the M matrix is ​​an infinite matrix. To calculate the result in a limited time, the number of rows and columns involved in the calculation must be limited. That is, determining the range of the M matrix involved in the cumulative calculation is the key to numerical calculation.

[0086] S104: Determine the numerical calculation range of the M matrix according to a preset division method and a preset error control limit.

[0087] As can be seen from the above step S103, this specification defines the M matrix. Since theoretically, the M matrix, i.e., the elements of the M matrix, are infinite, in order to obtain the calculation results within a limited time, it is necessary to limit the number of rows and columns involved in the calculation, that is, it is necessary to determine the range of the matrix involved in the calculation. As can be seen from the above step S101, the existing methods based on direct calculation and Laguerre calculation need to first perform cumulative calculations on infinite series. If the preset calculation range is too small, the calculation result will be too small, resulting in low accuracy and large errors in subsequent signal detection, while too large a range will waste computing resources. In order to solve the above problems, the embodiment of this specification divides the M matrix based on a preset division method to obtain a preset number of matrix sub-regions, and automatically determines the range that needs to be calculated in combination with the preset error control limits of the matrix sub-regions.

[0088] Specifically, the numerical calculation range of the M matrix is ​​determined according to the preset division method and the preset error control limit, including the following process: first, the M matrix is ​​divided according to the preset division method to obtain a preset number of matrix sub-regions. Then, the numerical calculation range of the M matrix is ​​determined according to the preset error control limits of the preset number of matrix sub-regions.

[0089] It should be noted that, Figure 2 As shown, in one embodiment of the present specification, dividing the M matrix according to a preset division method to obtain a preset number of matrix sub-regions includes the following process:

[0090] First, the area related to the numerical calculation of the cumulative distribution function is divided into initial matrix sub-regions, and the boundary rows and boundary columns of the initial matrix sub-regions are determined. Based on the boundary columns, a preset column outside the column where the initial matrix sub-region is located is determined as the boundary between the initial matrix sub-region and the first matrix sub-region. The series items within the boundary and in the same row as the initial sub-matrix are determined, and the area formed by the series items is taken as the first matrix sub-region; the coverage area of ​​the row where the initial matrix sub-region is located is determined based on the boundary rows, and the series items outside the coverage area are taken as the second matrix sub-region.

[0091] Specifically, Figure 2 As shown, in this specification, in a preset division method, the M matrix is ​​divided to obtain three matrix sub-regions. Figure 2 As shown, the initial matrix sub-region 0 is the region involved in the numerical calculation analysis, and the first matrix sub-region 1 is composed of the series terms discarded in each row of the initial matrix sub-region 0. The second matrix sub-region 2 is composed of all the discarded rows of the initial matrix sub-region 0. It should be noted that the boundary between the initial matrix sub-region 0 and the first matrix sub-region 1 is not a fixed column but a variable preset column, that is, the boundary column of each row is different. The sum of all series terms in the initial matrix sub-region 0, the first matrix sub-region 1, and the second matrix sub-region 2 are S0, S1, and S2 respectively. Then S0 is the approximate value of the cumulative distribution function of the double non-central beta distribution, and S1+S2 is its calculation error. The exact values ​​of S1 and S2 are difficult to calculate, but their upper limits can be found. Assume that S2 is less than a predetermined control limit ε 1,2 . Let ε 1,1 is the control limit for the cumulative sum of all series terms in each row of region 1. If j1 is determined, then j1ε 1,1 is the control limit of S1, that is, S1 <j1ε 1,1 Obviously S1+S2 <j1ε 1,1 +ε 1,2 , that is, the calculation accuracy of the cumulative distribution function can be calculated by ε 1,1 and ε 1,2 The upper limit of the error in this specification is between the actual error and the control limit (S1+S2 and j1ε 1,1 +ε 1,2 )between.

[0092] like Figure 3As shown, in another embodiment of the present specification, a second matrix division method is provided, that is, in one embodiment of the present specification, the M matrix is ​​divided according to a preset division method to obtain a preset number of matrix sub-regions, which specifically includes the following steps: first, the area related to the data calculation of the cumulative distribution function is divided into initial matrix sub-regions, the boundary rows and boundary columns of the initial matrix sub-regions are determined, and the coverage area of ​​the column where the initial matrix sub-region is located is determined based on the boundary columns, and the preset columns outside the coverage area are used as the boundary of the first matrix sub-region, and the series items within the boundary are determined to constitute the first matrix region. According to the determined first matrix sub-region, the series items outside the row where the initial matrix sub-region is located and in the same column as the initial sub-matrix are determined based on the boundary rows, and the area constituted by the series items is used as the second matrix sub-region. Specifically, as Figure 3 As shown, the second matrix partitioning method divides the M matrix, i.e., the M matrix, into three regions, wherein the initial matrix sub-region 0 is the region involved in the numerical calculation, and the first matrix sub-region 1 is the first matrix sub-region starting from the l1th column, which is composed of the columns discarded after the initial matrix sub-region 0. The boundaries of each column in the second matrix sub-region 2 and the initial matrix sub-region are different. It should be noted that the sum of all series items in the initial matrix sub-region, the first matrix sub-region, and the second matrix sub-region are S0, S1, and S2, respectively.

[0093] After the M matrix is ​​divided into matrix sub-regions based on the above steps, in order to automatically obtain the calculation range for subsequent signal analysis based on the sub-band energy ratio, the accuracy and efficiency of signal recognition are improved. In one or more embodiments of this specification, the numerical calculation range of the M matrix is ​​determined according to the preset division method and the preset error control limit, which specifically includes the following process:

[0094] The first cumulative sum of the items at each level in the preset fixed row is determined according to the preset first formula and the preset second formula; it should be noted that: the preset first formula is: I x (a,b-1) x (a,b)≤1, the second preset formula is: Then, according to the generated first cumulative sum, the sum of the series items included in the preset row and after the preset row is determined as the upper limit of the error of the series items at each level in the second matrix sub-region; wherein the upper limit of the error of the series items at each level in the second matrix sub-region is less than the preset control limit ε 1，2 According to the error upper limit of the second matrix sub-region and the preset control limit ε 1，2 ​, determine the number of demarcation rows. It should be noted that it is very difficult to directly obtain the number of demarcation rows based on the formula of the upper limit of error, and it is determined by searching the value of j from 0, 1... in sequence. Then intercept several series items in the M matrix, and obtain the sum of several series items, so as to determine the upper limit of error of each row in the first matrix sub-region according to the preset theoretical value and the sum of several series items and the preset first formula. Then sum the upper limit of error of each row, and determine the upper limit of error of the first matrix sub-region based on the number of rows of the preset row and the upper limit of error of each row in the first matrix sub-region. Determine the boundaries of each row according to the upper limit of error of each row, and use the coverage formed by the number of rows of the boundary row and the boundaries of each row as the numerical calculation range of the M matrix.

[0095] As can be seen from the above, based on the first division method, in one or more embodiments of the present specification, according to a preset number of matrix sub-regions, the upper limit of the error of the cumulative distribution function under the probability distribution of the sub-band energy proportion corresponding to the signal to be detected is determined as follows: first determine the upper limit of the cumulative sum of all series items in the second matrix sub-region, and determine the boundary row j1. Then analyze the upper limit of the cumulative sum of all series items in each row of the first matrix sub-region, and finally determine the overall error upper limit, that is, the accuracy, based on the two upper limits. It should be noted that: according to the preset first formula and the preset second formula, the first cumulative sum R of each of the series items in the preset fixed row is determined. j for:

[0096]

[0097] Then, according to the generated first cumulative sum, the sum of the series items included in the preset row and after the preset row is determined, that is, the sum S2 of the series items in the second matrix sub-region is:

[0098]

[0099] Based on the above, the sum S2 of the number of levels in the second matrix sub-region is the upper limit of all levels in the second matrix sub-region, and the upper limit is pre-set as ε for the second matrix sub-region. 1，2 , the boundary line can be automatically searched and obtained by: After obtaining the error upper limit and the boundary line of the second matrix sub-region, several series items in the M matrix are intercepted and the sum of the several series items is obtained. According to the preset theoretical value, the sum of the several series items and the preset first formula I x (a,b-1) x (a,b)≤1, determine the upper limit of the error of each row in the first matrix sub-region. The specific process is:

[0100] Suppose we take the first n rows of the jth row of the M matrix. j The sum of the series terms is:​

[0101] Then e j is the residual error of the jth row, that is, the difference between the theoretical value and the calculated value, then:

[0102] According to the preset first formula I x (a,b-1) x (a,b)≤1, we can know that:

[0103]

[0104] therefore,

[0105] If the residual error of the jth row is less than the control limit ε preset in the first matrix subregion 1,1 ,Right now Then it means that the calculation error of the jth row can be controlled by the control limit ε 1,1 Therefore, the calculation accuracy of each row in the initial matrix sub-region 0 is determined by the number of items n that are intercepted. j , the preset column of each row can be obtained by automatic numerical search through the determined error upper limit. The error upper limit S1 of the first matrix sub-region is:

[0106] In one or more embodiments of the present specification, the calculation accuracy of the cumulative distribution function is determined based on the upper error limit, specifically including: determining the overall upper error limit of the cumulative distribution function according to the upper error limit of the first matrix sub-region and the upper error limit of the second matrix sub-region, and using the overall upper error limit of the cumulative distribution function as the calculation accuracy of the cumulative distribution function. After the upper error limit of the matrix sub-region is determined in the first division method and the upper error limit of the second matrix sub-region, the upper error limit in the second matrix sub-region is less than ε 1，2 , and the upper limit of the error in the first matrix sub-region is less than ε 1,1 Then, the upper limit of the overall error is the difference between the actual value and the calculated value:

[0107]

[0108] in, That is, the upper limit of the overall error of the first division method for dividing the M matrix, that is, the calculation accuracy of the cumulative distribution function.

[0109] ​In another embodiment of the present specification, the M matrix is ​​divided based on the second division method in the above steps, and then the calculation range of the M matrix is ​​determined according to the preset error control limits of the preset number of matrix sub-regions, including the following steps:

[0110] First, the second cumulative sum of the series items in the preset fixed column is determined according to a preset third formula; wherein the preset third formula is: x (a,b)>I x (a+1,b). Then, according to the preset first formula and the second cumulative sum, the third cumulative sum of the items at all levels after the preset column is determined, and the third cumulative sum is used as the upper limit of the error of the items at all levels in the first matrix sub-region. It should be noted that the upper limit of the error of the items at all levels in the first matrix sub-region is less than the preset control limit ε 2，1 Then, according to the error upper limit of the second matrix sub-region and the preset control limit ε 2，1 Search the number of columns in sequence to determine the number of columns of the preset columns. Intercept several series items in the M matrix and obtain the sum of these several series items, so as to determine the upper limit of the error of each column in the second matrix sub-region according to the preset theoretical value and the sum of several series items and the third preset formula. Sum the upper limit of the error of each column, and determine the upper limit of the error of the second matrix sub-region based on the number of rows of the preset row and the upper limit of the error of each row in the first matrix sub-region. According to the upper limit of the error of each column in the second matrix sub-region, determine the boundary of each column, and determine the numerical calculation range of the M matrix by combining the boundary of each column with the number of columns of the preset column.

[0111] That is to say, in another embodiment of the present specification, when the division is performed based on the second division method, the first matrix sub-region is first analyzed, that is, Figure 3 The upper limit of the cumulative sum of all series terms in region 1; then analyze the second matrix sub-region, that is Figure 3 The upper limit of the cumulative sum of all series items in each column in region 2. Finally, the calculation accuracy of this method is determined according to the two upper limits. It should be further explained that: the second cumulative sum of each series item in the preset fixed column is determined according to the preset third formula, which specifically includes the following process: the sum of all series items in the preset fixed column l in the first partition matrix is ​​C l (x; a, b; δ1, δ2), then according to the preset third formula I x (a,b)>I x (a+1,b) can be obtained:

[0112]

[0113] Then according to the preset first formula I x (a,b-1) x ​(a,b)≤1, the sum S1 of all series terms after the delimiter column is:

[0114]

[0115] So This is the upper limit of the error of the first matrix sub-region. 2,1 When , the boundary column can be based on the upper error limit of the second matrix sub-region and the control limit ε of the first matrix sub-region. 2,1 Obtain, that is, obtain the value of the boundary column l1 by searching the following formula from 0, 1... in sequence:

[0116] After obtaining the upper limit of the error of the first matrix sub-region, a number of series items in the preset fixed columns of the M matrix are intercepted, and the sum of the number of series items is obtained, so as to determine the upper limit of the error of each column in the second matrix sub-region according to the preset theoretical value, the sum of the number of series items and the third preset formula. In the first application scenario of this specification, the process is specifically as follows: first, the first m columns of the lth column are obtained. l Item series, first m in column l l Sum of series for:

[0117] Then e l is the residual error of the lth row, that is, the difference between the theoretical value and the actual calculated value, that is:

[0118]

[0119] According to the preset third formula I x (a,b)>I x (a+1,b) obtains:

[0120] So at this time e l for:

[0121]

[0122] If the residual error in column l is less than the control limit ε2 preset in the second matrix sub-region ,2 ,Right now Then it means that the calculation error of the lth column can be controlled by the control limit ε 2,2 At this time, the upper limit S2 of the error in the second matrix sub-region is:

[0123]

[0124] After determining the upper error limit of the first matrix sub-region and the upper error limit of the second matrix sub-region, the upper error limit of the cumulative distribution function under the probability distribution of the sub-band energy proportion corresponding to the signal to be detected is determined according to the upper error limit of the first matrix sub-region and the upper error limit of the second matrix sub-region. It should be noted that the sum of the delimiting column and all series terms after the delimiting column in the M matrix is ​​less than the preset control limit ε of the first matrix sub-region 2,1 , and the calculation error of each column from 0 to the column before the boundary column l1-1 is less than the preset control limit ε of the second matrix sub-region 2,2 At this time, the actual value B(x; a, b; δ1, δ2) is different from the approximate value The difference is:

[0125] in,

[0126] It is the upper limit of the overall error of the M matrix, that is, the calculation accuracy of the PSER cumulative distribution function.

[0127] Based on the above, it can be known that in the first or second division method provided in the embodiments of this specification, after setting the control limits of the first matrix sub-region and the control limits of the second matrix sub-region, the control limits of the first matrix sub-region and the control limits of the second matrix sub-region can be used to determine the calculation range of the PSER cumulative distribution function, thereby avoiding the waste of calculation cost and time cost caused by determining the calculation range through infinite series calculation in the prior art, and improving the detection speed and accuracy when performing signal detection based on PSER.

[0128] S105: According to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, the values ​​of the items at each level within the numerical calculation range of the M matrix are obtained, and the values ​​of the items at each level within the numerical calculation range are accumulated to obtain the detection rate of the known signal.

[0129] In one or more embodiments of the present specification, according to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, obtaining the values ​​of the numerical items at various levels within the numerical calculation range of the M matrix specifically includes: inputting the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands into a preset series term formula to obtain the values ​​of the numerical items at various levels within the numerical calculation range of the M matrix. By first obtaining the values ​​of the numerical items at various levels within the calculation numerical range, the computing resources and time consumed by calculating the infinite series are avoided, thereby improving the efficiency and accuracy of the detection.

[0130] S106: According to the detection rate, the frequency band of interest is adjusted, and the best detection rate of the known signal is calculated to achieve signal detection of the known signal using the frequency band corresponding to the best detection rate as a detection sub-frequency band.

[0131] In one or more embodiments of the present specification, according to the detection rate, the frequency band of interest is adjusted, and the best detection rate of the known signal is calculated to achieve signal detection of the known signal according to the frequency band corresponding to the best detection rate as the detection sub-frequency band, which specifically includes the following process:

[0132] First, the known signal to be detected is sampled to obtain a sampled signal, and then the power spectrum of the sampled signal is obtained. The method of obtaining the power spectrum of the sampled signal is not limited here. According to the spectral lines corresponding to the preset frequency band of interest, the number of spectral lines in the power spectrum, the preset signal false detection rate and the preset detection threshold formula of the signal to be detected, the detection threshold η of the known signal to be detected is determined. PSER It should be noted that the preset detection threshold formula is: η PSER =I -1 (1-P f ; d, Nd). The initial detection rate of the known signal to be detected is obtained according to the preset detection rate formula.

[0133] It should be noted that the preset detection rate formula is:

[0134] Among them, P d represents the initial detection rate, η PSER represents the detection threshold, N represents the number of spectral lines in the power spectrum, k represents the starting spectral line of the frequency band of interest, d represents the ending spectral line of the frequency band of interest, and B d,N (k) represents the cumulative distribution function of the frequency band of interest, H1 indicates the presence of a signal; I -1 (x; a, b) is the incomplete beta function I x The inverse function of (a,b).

[0135] From the above detection rate formula, it can be seen that in order to improve the detection rate of the signal, the updated detection rate can be obtained by adjusting the frequency band of interest. If the updated detection rate is greater than the initial detection rate, the updated detection rate is used as the optimal detection rate, and the frequency band corresponding to the optimal detection rate is used as the detection sub-band to achieve signal detection for the known signal. For example: Assuming that the known signal to be detected contains N spectral lines, the detection sub-band corresponding to the optimal detection rate, that is, the d spectral lines starting from the kth spectral line, is used as the region of interest for detection, and the PSER value of the detection sub-band area is recorded as B d,N (k). Assume that the detection threshold of the known signal to be detected is η PSER , then when B d,N When (k) is greater than the detection threshold, it can be considered that a signal has appeared; when B d,N When (k) is less than the detection threshold, it is considered that no signal appears, thereby achieving the detection of the signal at the best detection rate. That is:

[0136] H0 means no signal appears, H1 means a signal appears;

[0137] According to the constant false alarm criterion, the false detection rate at this time is:

[0138]

[0139] Detection threshold η PSER for:

[0140] η PSER =I -1 (1-P f ; d, Nd); where I -1 (x; a, b) is the incomplete beta function I x The inverse function of (a,b).

[0141] Its detection rate is

[0142]

[0143] In the embodiments of the present specification, the optimal detection rate of the signal to be detected can be obtained by adjusting the region of interest, thereby achieving the detection rate of the signal detected by controlling the sub-band energy ratio based on the calculation accuracy of the cumulative distribution function, ensuring the accuracy of the detection result of the signal to be detected and improving the detection efficiency.

[0144] like Figure 4 As shown, the embodiment of this specification provides a schematic diagram of the internal structure of a device for detecting known signals through PSER based on matrix partitioning. The device includes a memory for storing computer program instructions and a processor for executing program instructions, Figure 4 It can be known that the device includes: at least one processor 401; and a memory 402 in communication with the at least one processor 401; wherein the memory 402 stores executable instructions of the at least one processor 401, so that the at least one processor 401 can:

[0145] Determine the frequency band of interest of the known signal to be detected according to the frequency domain distribution of the known signal to be detected; wherein the known signal is a signal with predetermined time domain and frequency domain characteristics;

[0146] Predicting the noise variance of the detection environment in which the known signal to be detected is located, so as to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands;

[0147] Generate an M matrix according to the number of items at each level in the cumulative distribution function of the preset sub-band energy proportion;

[0148] Determine the numerical calculation range of the M matrix according to a preset division method and a preset error control limit;

[0149] According to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, the value of each series item in the numerical calculation range of the M matrix is ​​obtained, and the value of each series item in the numerical calculation range is accumulated to obtain the detection rate of the known signal;

[0150] According to the detection rate, the frequency band of interest is repeatedly adjusted, and the best detection rate of the known signal is calculated to obtain the best detection rate, so as to realize signal detection of the known signal according to the frequency band corresponding to the best detection rate as the detection sub-frequency band.

[0151] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0152] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0153] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for detecting known signals by PSER based on matrix partitioning, characterized in that: The method comprises: Determine the frequency band of interest of the known signal to be detected according to the frequency domain distribution of the known signal to be detected; wherein the known signal is a signal with predetermined time domain and frequency domain characteristics; Predicting the noise variance of the detection environment in which the known signal to be detected is located, so as to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands; Generate an M matrix according to the number of items at each level in the cumulative distribution function of the preset sub-band energy proportion; Determine the numerical calculation range of the M matrix according to a preset division method and a preset error control limit; According to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, the value of each series item in the numerical calculation range of the M matrix is ​​obtained, and the value of each series item in the numerical calculation range is accumulated to obtain the detection rate of the known signal; According to the detection rate, repeatedly adjusting the frequency band of interest, and calculating and obtaining the best detection rate of the known signal, so as to realize signal detection of the known signal according to the frequency band corresponding to the best detection rate as the detection sub-frequency band; Determining the numerical calculation range of the M matrix according to the preset division method and the preset error control limit specifically includes: Dividing the M matrix according to a preset division method to obtain a preset number of matrix sub-regions; Determining a numerical calculation range of the M matrix according to preset error control limits of the preset number of matrix sub-regions; The step of dividing the M matrix according to a preset division method to obtain a preset number of matrix sub-regions specifically includes: Dividing a region associated with the numerical calculation of the cumulative distribution function into initial matrix sub-regions; Determine a boundary row and a boundary column of the initial matrix sub-region, and determine a preset column other than the column where the initial matrix sub-region is located as a boundary between the initial matrix sub-region and the first matrix sub-region based on the boundary column, determine series items within the boundary and in the same row as the initial matrix sub-region, and use the area formed by the series items as the first matrix sub-region; The coverage area of ​​the row where the initial matrix sub-region is located is determined based on the boundary row, and the items of each level outside the coverage area are used as the second matrix sub-region.

2. The method for detecting known signals by PSER based on matrix partitioning according to claim 1, characterized in that: The predicting of the noise variance of the detection environment in which the known signal to be detected is located, so as to obtain the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands, specifically includes: If the noise variance of the detection environment of the known signal to be detected is predicted to be , and obtain the energy of the noise-free signal as , the energy occupied by the sub-band is , the energy occupied by other spectral lines is , the number of spectral lines is L; The ratio of the energy of the effective signal in the sub-band of interest to the noise energy of a spectral line in the remaining band is taken as the signal-to-noise ratio in the sub-band of interest. ;in, The ratio of the energy of the remaining signal after removing the effective signal of the sub-band of interest to the noise energy of a spectral line in the remaining frequency band is used as the signal-to-noise ratio of the remaining frequency band. ;in, .

3. The method for detecting known signals by PSER based on matrix partitioning according to claim 2, characterized in that: The generating of the M matrix according to the number of items at each level in the cumulative distribution function of the preset sub-band energy proportion specifically includes: The various levels of the series are represented based on a preset series formula, and the sum of the series terms is used as a cumulative distribution function of the preset sub-band energy proportion; wherein the preset series formula is: ； in, is the series term of the cumulative distribution function, and is an integer greater than 0, j and l are integers greater than or equal to 0, x represents the probability density function when the signal exists and ; , ; The corresponding probability distribution of the signal to be detected is a double non-central beta distribution; the cumulative distribution function is: ; is the regular beta function, ;N is the number of spectral lines, d is the region of interest; The number of terms at each level in the cumulative distribution function The subscript j is used as the row subscript and the subscript l is used as the column subscript, so that each of the series terms Construct the M matrix.

4. The method for detecting known signals by PSER based on matrix partitioning according to claim 1, characterized in that: Determining the numerical calculation range of the M matrix according to the preset division method and the preset error control limit specifically includes: The first cumulative sum of the series items in the preset fixed row is determined according to the preset first formula and the preset second formula; wherein the preset first formula is: , the preset second formula is: ; Based on the first cumulative sum, the sum of the series terms included in the delimiting row and after the delimiting row is determined as the upper limit of the error of each series term in the second matrix sub-region; wherein the upper limit of the error of each series term in the second matrix sub-region is less than the preset error control limit ; According to the error upper limit of the second matrix sub-region and the preset error control limit , determine the number of the delimiting rows; A plurality of series items in the M matrix are intercepted, and the sum of the plurality of series items is obtained, so as to determine the upper limit of the error of each row in the first matrix sub-region according to the preset theoretical value, the sum of the plurality of series items and the preset first formula; wherein the upper limit of the error of each row in the first matrix sub-region is less than the preset error control limit ; The boundaries of each row are determined according to the upper error limits of each row, and the coverage range formed by the number of the boundary rows and the boundaries of each row is used as the numerical calculation range of the M matrix.

5. The method for detecting known signals by PSER based on matrix partitioning according to claim 3, characterized in that: The step of obtaining the value of each series item within the numerical calculation range of the M matrix according to the signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands specifically includes: The signal-to-noise ratio in the frequency band of interest and the signal-to-noise ratio in the remaining frequency bands are input into the preset series term formula to obtain the value of each of the series terms within the numerical calculation range of the M matrix.

6. The method for detecting known signals by PSER based on matrix partitioning according to claim 1, characterized in that: The step of dividing the M matrix according to a preset division method to obtain a preset number of matrix sub-regions M matrices also includes: Dividing a region associated with data calculation of the cumulative distribution function into initial matrix sub-regions; Determine the boundary row and the boundary column of the initial matrix sub-region, and determine the coverage area of ​​the column where the initial matrix sub-region is located based on the boundary column, and form a first matrix region based on the number of items at all levels outside the coverage area; Based on the demarcation row, a preset row outside the row where the initial matrix sub-region is located is determined, and the series items in the same column as the initial sub-matrix, and the area formed by the series items is used as the second matrix sub-region; wherein the preset rows of each column in the second matrix sub-region are different.

7. The method for detecting known signals by PSER based on matrix partitioning according to claim 6, characterized in that: Determining the numerical calculation range of the M matrix according to the preset division method and the preset error control limit specifically includes: The second cumulative sum of the series items in the preset fixed column is determined according to a preset third formula; wherein the preset third formula is: ; According to the preset first formula and the second cumulative sum, a third cumulative sum of the series items of the preset column and after the preset column is determined, and the third cumulative sum is used as the upper limit of the error of the items at each level in the first matrix sub-region; wherein the upper limit of the error of the items at each level in the first matrix sub-region is less than the preset control limit ; According to the error upper limit of the second matrix sub-region and the preset control limit Searching the number of columns in sequence to determine the number of the preset columns; A plurality of series items in the preset fixed columns in the M matrix are intercepted, and the sum of the plurality of series items is obtained, so as to determine the upper limit of the error of each column in the second matrix sub-region according to the preset theoretical value, the sum of the plurality of series items and the preset third formula; wherein the upper limit of the error of each column in the second matrix sub-region is less than the preset error control limit ; According to the upper limit of the error of each column in the second matrix sub-region, the boundary of each column is determined, and the boundary of each column and the number of the preset columns are combined to determine the numerical calculation range of the M matrix.

8. The method for detecting known signals by PSER based on matrix partitioning according to claim 1, characterized in that: The repeatedly adjusting the frequency band of interest according to the detection rate, and calculating and obtaining the best detection rate of the known signal, so as to implement signal detection for the known signal according to the frequency band corresponding to the best detection rate as a detection sub-frequency band, specifically includes: Sampling the known signal to be detected to obtain a sampled signal, and acquiring a power spectrum of the sampled signal; Determine the detection threshold of the known signal to be detected according to the spectral lines corresponding to the preset frequency band of interest, the number of spectral lines in the power spectrum, the preset signal false detection rate and the preset detection threshold formula of the signal to be detected; The initial detection rate of the detected known signal is obtained based on a preset detection rate formula; wherein the preset detection rate formula is: ;in, represents the initial detection rate, represents the detection threshold, N represents the number of spectral lines in the power spectrum, k represents the starting spectral line of the frequency band of interest, d represents the ending spectral line of the frequency band of interest, represents the cumulative distribution function of the frequency band of interest, Indicates that a signal has appeared; The frequency band of interest is adjusted to obtain an updated detection rate. If the updated detection rate is greater than the initial detection rate, the updated detection rate is used as the optimal detection rate, and the frequency band corresponding to the optimal detection rate is used as the detection sub-band to achieve signal detection for the known signal.

9. A device for detecting known signals by PSER based on matrix partitioning, characterized in that: The device comprises a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to execute the method according to any one of claims 1 to 8.

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