A method, system, device and medium for detecting non-circularity of complex-valued signals

Abstract

The present invention belongs to the field of communication technology, and discloses a method, system, device and medium for testing the non-circularity of a complex-valued signal, including: obtaining a sampling signal of a receiving antenna, calculating a sampling coherence matrix of the sampling signal; constructing a separation function according to the sampling coherence matrix; calculating test statistic data based on the expression of the separation function; setting a threshold value, comparing and analyzing the test statistic data and the threshold value, and judging the characteristics of the sampling signal based on the comparison result. The technical solution of the present invention can make full use of the statistical difference between circular signals and non-circular signals in the compensation covariance matrix, can accurately detect the non-circularity of the signal, and has low computational complexity.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a method, system, device and medium for detecting the non-circularity of a complex-valued signal. Background Art

[0002] Signal processing algorithms in existing literature, such as spectrum sensing and direction of arrival positioning, usually assume that the signal to be processed is a circular signal. However, in many practical application scenarios, the assumption of circular signals is unreasonable. For example, modulation signals such as binary phase shift keying (BPSK), offset quadrature phase shift keying (OQPSK), Gaussian minimum shift keying (GMSK) and amplitude shift keying (ASK) all exhibit non-circular characteristics, that is, their compensation covariance is not zero; in this case, using the feature of non-zero compensation covariance for algorithm design can significantly improve the performance of signal processing algorithms. On the other hand, if an algorithm for non-circular signals is used in the process of circular signal processing, the convergence speed of the algorithm will become very slow or even fail. Therefore, an important prerequisite for designing a robust algorithm is to determine whether the signal to be processed has non-circular characteristics, which can be achieved through statistical tests of the non-circularity of complex-valued signals.

[0003] At present, the algorithms used to test the non-circularity of signals mainly include GLRT (Generalized likelihood ratio test), LMPIT (Locally most powerful invariant test) and RT (Roy's test). The GLRT method is the most popular statistic for detecting the non-circularity of signals, but the complexity is too high due to the need for eigenvalue decomposition. The LMPIT algorithm suffers from performance degradation when the non-circularity of the signal is large, while the RT algorithm is suitable for the case where there is only one transmitted signal. Summary of the invention

[0004] The purpose of the present invention is to provide a method, system, device and medium for detecting the non-circularity of a complex-valued signal, so as to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above object, the present invention provides a method for detecting the non-circularity of a complex-valued signal, comprising:

[0006] Step 1: Obtain a sampling signal from a receiving antenna and calculate a sampling coherence matrix of the sampling signal;

[0007] Step 2: construct a separation function according to the sampled coherence matrix; calculate the test statistic data based on the expression of the separation function;

[0008] Step three: setting a threshold value, performing comparative analysis on the test statistic data and the threshold value, and judging the characteristics of the sampled signal based on the comparison result.

[0009] Optionally, the sampling signal is specifically:

[0010]

[0011] Where H0 indicates that the received signal is a circular signal, H1 indicates that the received signal is a non-circular signal; x(n) represents the signal vector received by the receiving antenna n at the sampling time, u(n) represents the non-circular signal vector sent by the transmitting antenna n at the sampling time, w(n) represents the noise vector at the sampling time n, n = 1, 2, ···, N is the number of sampling points; H represents the channel gain coefficient matrix, u = [u1, u2, ···, u P ] represents P non-circular signals sent by the transmitting antenna.

[0012] Optionally, calculating a sampling coherence matrix of the sampled signal specifically includes:

[0013] Calculate the sampling standard covariance matrix and the sampling compensation covariance matrix of the sampled signal; calculate the sampling coherence matrix of the sampled signal based on the sampling standard covariance matrix and the sampling compensation covariance matrix; wherein the specific calculation formula for calculating the sampling coherence matrix of the sampled signal is:

[0014]

[0015] In the formula, is the sampling coherence matrix, is the sampling standard covariance matrix, is the sampling compensation covariance matrix.

[0016] Optionally, a separation function is constructed according to the sampling coherence matrix, and the specific calculation formula is:

[0017]

[0018] In the formula, J g is the separation function, g(·) is a one-dimensional monotonically increasing or monotonically decreasing function, λ i (i=1,2,···,M) is the sampling coherence matrix The typical correlation coefficient is , where M is the number of receiving antennas.

[0019] Optionally, the test statistic data is calculated based on the expression of the separation function, and the specific calculation formula is:

[0020]

[0021] In the formula, is the sampling coherence matrix, the superscript (·) Η represents the conjugate transpose symbol, tr(·) is the rank of the matrix; T is the test statistic data, M is the number of receiving antennas, g(·) is a one-dimensional monotonically increasing or monotonically decreasing function, J g is the separation function, λ i (i=1,2,···,M) is the sampling coherence matrix The typical correlation coefficient is , where M is the number of receiving antennas.

[0022] Optionally, the step three specifically includes:

[0023] When the test statistic data is greater than the threshold value, the sampled signal is a non-circular signal; when the test statistic data is less than the threshold value, the sampled signal is a circular signal.

[0024] A complex-valued signal non-circularity detection system, comprising:

[0025] A signal acquisition module, used to obtain a sampling signal from a receiving antenna and calculate a sampling coherence matrix of the sampling signal;

[0026] A statistics calculation module, used to construct a separation function according to a sampled coherence matrix; and calculate test statistics data based on an expression of the separation function;

[0027] The characteristic judgment module is used to set a threshold value, compare and analyze the test statistic data with the threshold value, and judge the characteristic of the sampled signal based on the comparison result.

[0028] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute a method for detecting non-circularity of a complex-valued signal.

[0029] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for detecting the non-circularity of a complex-valued signal is implemented.

[0030] The technical effect of the present invention is as follows: the inspection method of the present invention comprises obtaining a sampling signal of a receiving antenna, calculating a sampling coherence matrix of the sampling signal; constructing a separation function according to the sampling coherence matrix; calculating inspection statistic data based on the expression of the separation function; setting a threshold value, comparing and analyzing the inspection statistic data and the threshold value, and judging the characteristics of the sampling signal based on the comparison result. The present invention makes full use of the statistical difference between circular signals and non-circular signals in the compensation covariance matrix, can accurately detect the non-circularity of the signal, and has low computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0033] Figure 1 A comparison diagram of detection probabilities of various inspection methods under different signal-to-noise ratios in an embodiment of the present invention;

[0034] Figure 2 It is a comparison diagram of ROC curves of various test methods in the embodiments of the present invention;

[0035] Figure 3 4 is a flow chart of signal non-circularity inspection in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0037] It should be understood that the terms described in the present invention are only for describing special embodiments and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0038] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art generally understood by the present invention. Although the present invention describes only preferred methods, any method similar or equivalent to that described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0039] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present application description and examples are exemplary only.

[0040] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0041] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0042] Embodiment 1

[0043] like Figure 1 - Figure 3 As shown, this embodiment provides a method, system, device and medium for testing the non-circularity of a complex-valued signal, including: obtaining a sampling signal from a receiving antenna, and calculating a sampling coherence matrix of the sampling signal; constructing a separation function according to the sampling coherence matrix; calculating test statistic data based on the expression of the separation function; setting a threshold value, performing comparative analysis on the test statistic data and the threshold value, and judging the characteristics of the sampling signal based on the comparison result.

[0044] In order to make up for the shortcomings of the existing methods, this embodiment proposes a complex-valued signal non-circularity statistical test method based on the framework of the separation function estimation test (SFET), which specifically includes: obtaining the sampling signal of the receiving antenna, calculating the sampling coherence matrix of the sampling signal; constructing a separation function according to the sampling coherence matrix; calculating the test statistic data based on the expression of the separation function; comparing the test statistic with the detection threshold, if the statistic is less than the detection threshold, the signal is a circular signal, otherwise, the signal is considered to be non-circular, thereby completing the detection process. Experimental results show that this embodiment makes full use of the statistical differences between circular signals and non-circular signals in the compensation covariance matrix, can accurately detect the non-circularity of the signal, and has low computational complexity.

[0045] This embodiment makes full use of the statistical difference between circular signals and non-circular signals in the compensation covariance matrix, can accurately detect the non-circularity of the signal, and has low computational complexity. The specific implementation process is as follows:

[0046] Step 1, obtaining a sampling signal from a receiving antenna, and calculating a sampling coherence matrix of the sampling signal;

[0047] Step 2, constructing a separation function according to the sampled coherence matrix; calculating test statistic data based on the expression of the separation function;

[0048] Step 3, compare the test statistic with the detection threshold. If the statistic is less than the detection threshold, the signal is a circular signal. Otherwise, the signal is considered to be non-circular, thus completing the detection process.

[0049] The sampled signal described in step 1 can be expressed as:

[0050]

[0051] Where H0 indicates that the received signal is a circular signal, H1 indicates that the received signal is a non-circular signal; x(n) represents the signal vector received by the receiving antenna n at the sampling time, u(n) represents the non-circular signal vector sent by the transmitting antenna n at the sampling time, w(n) represents the noise vector at the sampling time n, which obeys the standard complex Gaussian distribution (circular signal), n=1,2,···,N is the number of sampling points; represents the channel gain coefficient matrix, u=[u1,u2,···,u P ] represents P non-circular signals sent by the transmitting antenna, and the i-th (i=1, 2, ···, P) signal obeys the zero-mean complex Gaussian distribution, where the signal power λ i =E(|u i | 2 ), κi represents the non-circularity, φ i ∈[-π,π) represents the non-circular phase of the signal. In addition, M and P represent the number of receiving antennas and transmitting antennas, respectively.

[0052] The sampled coherence matrix described in step 1 is:

[0053]

[0054] Among them, the sampling standard covariance matrix Sampling compensation covariance matrix Superscript (·) Τ Indicates the transposition symbol, superscript (·) Η Represents the conjugate transpose symbol.

[0055] The separation function described in step 2 has the following form:

[0056]

[0057] Among them, J g is the separation function, g(·) is a one-dimensional monotonic (increasing or decreasing) function, λ i (i=1,2,···,M) is the sampling coherence matrix The typical correlation coefficient is , where M is the number of receiving antennas.

[0058] The test statistic described in step 2 is calculated using the following formula:

[0059]

[0060] In the formula, is the sampling coherence matrix, the superscript (·) Η represents the conjugate transpose symbol, tr(·) is the rank of the matrix; T is the test statistic data, M is the number of receiving antennas, g(·) is a one-dimensional monotonically increasing or monotonically decreasing function, J g is the separation function, λ i (i=1,2,···,M) is the sampling coherence matrix The typical correlation coefficient is , where M is the number of receiving antennas.

[0061] The perception process described in step 3 is implemented by the following decision model:

[0062]

[0063] Where η is the detection threshold, that is, T>η means that the assumption H1 is established, that is, the received signal is non-circular, otherwise it means that the assumption H0 is established, that is, the signal is circular.

[0064] The present embodiment is described in detail below through simulation experiments.

[0065] Simulation parameter setting: The simulation experiment assumes a Rayleigh fading channel, that is, the column components of the channel gain matrix H obey an independent and identically distributed standard complex Gaussian distribution. Once generated in the current Monte Carlo experiment, they remain unchanged, and will be randomly generated again in the next Monte Carlo experiment. Without loss of generality, the signal-to-noise ratio of the i-th channel can be defined as SNR i =10log(λ i ). Under the H0 assumption, the primary user signal does not exist; under the H1 assumption, the primary user signal is set as follows: signal non-circularity κ1 = ··· = κ P =1, non-circular phase φ i The uniform distribution is defined in the interval [-π,π). All simulation results are obtained by 10 5 Monte Carlo experiment.

[0066] exist Figure 1 In the figure, the curve of detection probability changing with the signal-to-noise ratio of the second antenna is given. The experimental parameters are set as: number of receiving antennas M = 6, sample length N = 100, number of non-circular signals P = 2, where the power of the first antenna is λ1 = -3dB. It can be found that the SFET algorithm has the highest detection probability and performs better than other detection algorithms.

[0067] exist Figure 2 In the figure, the ROC (Receiver operating characteristic) curve comparison of all the detection algorithms is given. The simulation parameters are set as: number of receiving antennas M = 5, sample length N = 150, number of non-circular signals P = 2, corresponding power λ1 = -3dB, λ2 = -5dB. It is not difficult to see that compared with other comparison algorithms, the ROC curve of the proposed SFET algorithm is higher, that is, the detection performance is better.

[0068] A complex-valued signal non-circularity detection system, comprising:

[0069] A signal acquisition module, used to obtain a sampling signal from a receiving antenna and calculate a sampling coherence matrix of the sampling signal;

[0070] A statistics calculation module, used to construct a separation function according to a sampled coherence matrix; and calculate test statistics data based on an expression of the separation function;

[0071] The characteristic judgment module is used to set a threshold value, compare and analyze the test statistic data with the threshold value, and judge the characteristic of the sampled signal based on the comparison result.

[0072] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute a method for detecting non-circularity of a complex-valued signal.

[0073] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for detecting the non-circularity of a complex-valued signal is implemented.

[0074] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for testing the non-circularity of complex-valued signals. It is characterized in that include: Step 1: Obtain a sampling signal from a receiving antenna and calculate a sampling coherence matrix of the sampling signal; Calculating the sampling coherence matrix of the sampled signal specifically includes: Calculate the sampling standard covariance matrix and the sampling compensation covariance matrix of the sampled signal; calculate the sampling coherence matrix of the sampled signal based on the sampling standard covariance matrix and the sampling compensation covariance matrix; wherein the specific calculation formula for calculating the sampling coherence matrix of the sampled signal is: ； In the formula, is the sampling coherence matrix, is the sampling standard covariance matrix, is the sampling compensation covariance matrix; Step 2: construct a separation function according to the sampled coherence matrix; calculate the test statistic data based on the expression of the separation function; The separation function is constructed according to the sampling coherence matrix. The specific calculation formula is: ； In the formula, is the separation function, is a one-dimensional monotonically increasing or monotonically decreasing function, is the sampling coherence matrix The typical correlation coefficient of , is the number of receiving antennas; The test statistic data is calculated based on the expression of the separation function. The specific calculation formula is: ； In the formula, , superscript represents the conjugate transpose symbol, is the rank of the matrix; is the test statistic data; Step three: setting a threshold value, performing comparative analysis on the test statistic data and the threshold value, and judging the characteristics of the sampled signal based on the comparison result.

2. A method for detecting non-circularity of a complex-valued signal according to claim 1, It is characterized in that The sampling signal is specifically: ； In the formula, Indicates that the received signal is a circular signal. Indicates that the received signal is a non-circular signal; Indicates that at the sampling time The signal vector received by the receiving antenna, Indicates that at the sampling time The non-circular signal vector sent by the transmitting antenna, Indicates that at the sampling time The noise vector is , N is the number of sampling points; represents the channel gain coefficient matrix, Indicates the transmission antenna A non-circular signal.

3. The method for detecting the non-circularity of a complex-valued signal according to claim 1, It is characterized in that The step three specifically includes: When the test statistic data is greater than the threshold value, the sampled signal is a non-circular signal; when the test statistic data is less than the threshold value, the sampled signal is a circular signal.

4. A complex-valued signal non-circularity test system, It is characterized in that include: A signal acquisition module, used to obtain a sampling signal from a receiving antenna and calculate a sampling coherence matrix of the sampling signal; Calculating the sampling coherence matrix of the sampled signal specifically includes: Calculate the sampling standard covariance matrix and the sampling compensation covariance matrix of the sampled signal; calculate the sampling coherence matrix of the sampled signal based on the sampling standard covariance matrix and the sampling compensation covariance matrix; wherein the specific calculation formula for calculating the sampling coherence matrix of the sampled signal is: ； In the formula, is the sampling coherence matrix, is the sampling standard covariance matrix, is the sampling compensation covariance matrix; A statistics calculation module, used to construct a separation function according to a sampled coherence matrix; and calculate test statistics data based on an expression of the separation function; The separation function is constructed according to the sampling coherence matrix. The specific calculation formula is: ； In the formula, is the separation function, is a one-dimensional monotonically increasing or monotonically decreasing function, is the sampling coherence matrix The typical correlation coefficient of , is the number of receiving antennas; The test statistic data is calculated based on the expression of the separation function. The specific calculation formula is: ； In the formula, , superscript represents the conjugate transpose symbol, is the rank of the matrix; is the test statistic data; The characteristic judgment module is used to set a threshold value, compare and analyze the test statistic data with the threshold value, and judge the characteristic of the sampled signal based on the comparison result.

5. An electronic device, It is characterized in that It comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform a method for detecting non-circularity of a complex-valued signal according to any one of claims 1 to 3.

6. A computer-readable storage medium, It is characterized in that The device stores a computer program, which, when executed by a processor, implements a method for detecting non-circularity of a complex-valued signal as described in any one of claims 1 to 3.

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