Method and system for improving signal-to-noise ratio of solar radio telescope system

Abstract

The invention is suitable for the field of system noise prediction of a solar radio observation system, and provides a method and system for improving the signal-to-noise ratio of a solar radio telescope system.The method comprises the steps that the spectrum entropy value of spectrum data, the power square accumulated value of the spectrum data and the spectrum kurtosis of the spectrum data are obtained through calculation based on observation spectrum data; establishing a multi-threshold judgment mechanism, respectively comparing the spectrum entropy value of the spectrum data, the power square accumulated value of the spectrum data and the spectrum kurtosis of the spectrum data with corresponding thresholds to obtain the noise condition of the solar radio telescope system, and if the frame data does not contain the communication interference signal and the spectrum observation data when the sun does not burst, judging the noise condition of the solar radio telescope system. Updating the real-time bottom noise value of the system by adopting a first processing mode; if the frame data contains the communication interference signal, updating the real-time bottom noise value by adopting a second processing mode; and based on the noise condition of the solar radio telescope system, subtracting the noise floor value of the corresponding mode through a spectrum reduction method to obtain an anti-interference signal.

Description

Technical Field

[0001] The present invention belongs to the field of system noise prediction applicable to solar radio observation systems, and in particular relates to a method and system for improving the signal-to-noise ratio of a solar radio telescope system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] At present, the method to improve the signal-to-noise ratio of the receiving system is usually to perform quality analysis on the received signal to determine whether it is a noise signal or a target signal. If it is a target signal, the target signal is subjected to noise elimination processing. Commonly used processing methods include spectral subtraction method, filtering method, etc.

[0004] For example, the publication number is CN110444222A, and the invention name is a speech noise reduction method based on information entropy weighting; the publication number is CN105429657A, and the invention name is a shortwave receiver and its denoising method; the publication number is CN104617965A, and the invention name is a method and device for improving the signal-to-noise ratio of a receiver. All of them improve the signal-to-noise ratio by noise reduction. However, these methods cannot be directly used to improve the signal-to-noise ratio of a solar radio telescope system.

[0005] Existing technologies mainly focus on eliminating noise from the receiver, judging the quality of the received signal by thresholds, and then judging the quality of the received signal by threshold comparison. If it is a target signal, the noise is filtered out by filtering and other methods to further improve the signal-to-noise ratio of the received signal. However, the single threshold judgment method used is effective for receiving narrowband or single-frequency signals. However, since the solar radio telescope is mainly used to observe solar radio burst activities, including spectrum observation and flow observation of the corresponding frequency points, when observing solar radio activities, the solar radio telescope is not only subject to noise interference generated by its own analog receivers and digital receivers, but also thermal radiation noise from the sky background. When the solar radio telescope tracks the sun in real time, it will also receive thermal radiation noise from the sun in a quiet state. Since solar radio waves are wide-band, existing in the meter wave to millimeter wave bands, the system will be interfered by various communication frequency bands when observing solar radio.

[0006] When reducing the noise of speech signals, it is common to calculate the power spectrum entropy value of the frame signal to determine whether the frame data is a pure noise signal to predict the noise of the system. However, this method is not suitable for judging the observation data of solar radio telescopes. When the sun erupts, the signal energy in a wide frequency band usually increases. At this time, it is difficult to judge which is larger by simply looking at the power spectrum entropy value of the signal during the eruption and the power spectrum entropy value of the signal without the eruption. In particular, when the signal without the eruption contains communication interference, the power spectrum entropy value of the signal will be very small, and it is difficult to judge which is larger compared with the power spectrum entropy value of the signal during the eruption. Summary of the invention

[0007] In order to solve at least one technical problem existing in the above-mentioned background technology, the present invention provides a method and system for improving the signal-to-noise ratio of a solar radio telescope system. The method establishes a new judgment mechanism to accurately and real-timely obtain the noise situation of the solar radio telescope system, and obtains new spectrum data through the spectrum subtraction method, thereby improving the signal-to-noise ratio of the system, which is beneficial to improving the system's ability to observe weak solar bursts.

[0008] In order to achieve the above object, the present invention adopts the following technical solution:

[0009] A first aspect of the present invention provides a method for improving the signal-to-noise ratio of a solar radio telescope system, comprising:

[0010] Obtain observation spectrum data from solar radio telescopes;

[0011] Based on the observed spectrum data, the spectrum entropy value of the spectrum data, the power square accumulation value of the spectrum data and the spectrum kurtosis of the spectrum data are calculated;

[0012] A multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is a spectrum observation data when the sun is not erupting, the first processing mode is used to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, the second processing mode is used to update the real-time background noise value.

[0013] Based on the noise situation of the solar radio telescope system, the noise floor value of the corresponding mode is subtracted by the spectrum subtraction method to obtain the anti-interference signal.

[0014] Furthermore, the multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulated value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system, including:

[0015] Set multiple thresholds, including a power spectrum entropy value threshold T_h1, an energy threshold T_w1, and a spectrum kurtosis threshold T_sk1;

[0016] If the spectral entropy value of the spectrum data of this frame is greater than the power spectrum entropy value threshold T_h1, the power square cumulative value of the spectrum data is less than the energy threshold T_w1 and there is no extreme point exceeding the extreme point threshold, the data of this frame does not contain communication interference signals and the spectrum observation data when the sun does not erupt;

[0017] If the spectral kurtosis of the extreme point of the data in this frame exceeds the spectral kurtosis threshold T_sk1, the data in this frame contains a communication interference signal.

[0018] Furthermore, the spectral entropy value of the spectral data, the power square accumulated value of the spectral data, and the spectral kurtosis of the spectral data calculated based on the observed spectral data include:

[0019] The calculation formula of the spectral entropy value of the spectrum data is:

[0020]

[0021] The calculation formula of the power square accumulation value of the spectrum data is:

[0022]

[0023] The calculation formula of the spectral kurtosis of the spectrum data is:

[0024]

[0025] Where P1(k) is the probability density of the frequency point, N is the number of frequency points contained in the spectrum data, y(k) is the spectrum amplitude of the kth frequency point, y(i) is the power value corresponding to each frequency point; M is the number of finite points before and after the extreme point as the middle point, parameter SP is the cumulative result of the square power values ​​of the M points, and SN is the cumulative result of the power values ​​of the M points.

[0026] Furthermore, if the frame of data does not contain a communication interference signal and the spectrum observation data when the sun is not erupting, the real-time background noise value of the system is updated using the first processing mode, including:

[0027] D(k)=(D1(k)+D2(k)+…+D49(k)+DL(k)) / L,

[0028] The data of this frame is assigned to DL(k), the original DL(k) value is assigned to DN-1(k), and so on, the original D2(k) value is assigned to D1(k), D(k) is the latest updated average value, and L is the number of consecutive frames.

[0029] Furthermore, if the frame data contains a communication interference signal, the second processing mode is used to update the real-time background noise value. The difference from the first processing mode is that the data near the extreme point is firstly smoothed and filtered.

[0030] A second aspect of the present invention provides a system for improving the signal-to-noise ratio of a solar radio telescope system, comprising:

[0031] A data acquisition module, used to acquire observation spectrum data of a solar radio telescope;

[0032] A feature extraction module is used to calculate the spectral entropy value of the spectral data, the power square accumulation value of the spectral data, and the spectral kurtosis of the spectral data based on the observed spectral data;

[0033] The noise situation acquisition module is used to establish a multi-threshold judgment mechanism, and compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is spectrum observation data when the sun is not erupting, the first processing mode is used to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, the second processing mode is used to update the real-time background noise value;

[0034] The noise elimination module is used to obtain an anti-interference signal by subtracting the noise floor value of the corresponding mode through the spectrum subtraction method based on the noise situation of the solar radio telescope system.

[0035] Furthermore, in the noise situation acquisition module, a multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulated value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system, including:

[0036] Set multiple thresholds, including a power spectrum entropy value threshold T_h1, an energy threshold T_w1, and a spectrum kurtosis threshold T_sk1;

[0037] If the spectral entropy value of the spectrum data of this frame is greater than the power spectrum entropy value threshold T_h1, the power square cumulative value of the spectrum data is less than the energy threshold T_w1 and there is no extreme point exceeding the extreme point threshold, the data of this frame does not contain communication interference signals and the spectrum observation data when the sun does not erupt;

[0038] If the spectral kurtosis of the extreme point of the data in this frame exceeds the spectral kurtosis threshold T_sk1, the data in this frame contains a communication interference signal.

[0039] A third aspect of the present invention provides a computer-readable storage medium.

[0040] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the method for improving the signal-to-noise ratio of a solar radio telescope system as described above.

[0041] A fourth aspect of the present invention provides a computer device.

[0042] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for improving the signal-to-noise ratio of a solar radio telescope system as described above are implemented.

[0043] The fifth aspect of the present invention provides a program product, which is a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, it implements the steps in a method for improving the signal-to-noise ratio of a solar radio telescope system as described above.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention establishes a new judgment mechanism to accurately and real-timely derive the noise situation of the solar radio telescope system, and obtains new spectrum data through the spectrum subtraction method, thereby improving the signal-to-noise ratio of the system, which is beneficial to improving the system's ability to observe weak solar bursts.

[0046] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0048] Figure 1 It is a flowchart of a method for improving the signal-to-noise ratio of a solar radio telescope system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0051] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0052] As mentioned in the background technology, when the solar radio telescope system performs spectrum observation and radio flux observation on solar radio, it is difficult to observe smaller solar burst activities due to the influence of system noise. Therefore, it is very important to reasonably predict the system noise floor and reduce the noise floor of the solar radio observation system by spectrum subtraction method to improve the signal-to-noise ratio of the solar radio telescope. Therefore, the present invention proposes a method for predicting system noise suitable for solar radio observation system, predicting the system noise in real time, and then improving the signal-to-noise ratio of the solar radio observation system by spectrum subtraction method.

[0053] Embodiment 1

[0054] The solar radio telescope system consists of four parts: receiving antenna, analog receiver, digital receiver and host computer display and storage device.

[0055] Solar radio telescopes are mainly used to observe solar radio bursts, including spectrum observations and flow observations at corresponding frequencies. The purpose of improving the signal-to-noise ratio of the solar radio telescope system is to improve the ability of the solar radio telescope to observe weak solar bursts. When observing solar radio activities, the solar radio telescope is not only subject to noise interference from its own analog receivers and digital receivers, but also to thermal radiation noise from the sky background. When the solar radio telescope tracks the sun in real time, it will also receive thermal radiation noise from the sun in a quiet state. Since solar radio waves are wide-band, existing in the meter wave to millimeter wave bands, the system will be interfered by various communication frequency bands when observing solar radio.

[0056] With respect to the spectrum data transmitted from the solar radio telescope system to the host computer, since the weak burst signal of the sun is easily submerged in the noise, the present invention proposes a method for reducing the background noise of the solar radio telescope and improving the signal-to-noise ratio of the system.

[0057] like Figure 1 As shown, this embodiment provides a method for improving the signal-to-noise ratio of a solar radio telescope system, comprising the following steps:

[0058] Step 1: Obtain the observation spectrum data of the solar radio telescope;

[0059] Step 2: Based on the observed spectrum data, the spectrum entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectrum kurtosis of the spectrum data are calculated;

[0060] This embodiment takes 8K points of spectrum data as an example. Due to the symmetry of the spectrum data, the following processing may be performed only on the first 4K points of data.

[0061] First, frequency domain accumulation processing is performed, and then the average value is calculated to reduce the influence of dispersion and randomness of the spectrum data and improve the signal-to-noise ratio. The data received by the host computer is the accumulated 4K point spectrum data.

[0062] The purpose of the above steps is to reduce the influence of dispersion and randomness of spectrum data and improve the signal-to-noise ratio. The data received by the host computer is the accumulated 4K point spectrum data;

[0063] The spectral entropy value of the spectrum data is calculated according to the probability density of each frequency point and the spectral entropy value of this frame of data. The calculation formula of the spectral entropy value of the spectrum data is:

[0064] The calculation formula of the spectral entropy value of each frame of data is:

[0065]

[0066] The probability density calculation formula for each frequency point is:

[0067]

[0068] The calculation formula of the power square accumulation value of the spectrum data is:

[0069]

[0070] The calculation formula of the spectral kurtosis of the spectrum data is:

[0071] First, the extreme value points of each frame of spectrum data are calculated. When the extreme value points exceed the extreme value threshold MAX_T, the spectral kurtosis of each extreme value point is calculated. The calculation method is shown in formula (4).

[0072]

[0073] Wherein, P1(k) is the probability density of a frequency point, and N is the number of frequency points contained in the spectrum data. In this embodiment, the value is 4096.

[0074] y(k) is the spectrum amplitude of the kth frequency point, y(i) is the power value corresponding to each frequency point; M is the number of finite points before and after the extreme point as the middle point, and the value of M is set according to the actual data, which can generally be 10. The parameter SP is the cumulative result of the square power value of M points, and SN is the cumulative result of the power value of M points.

[0075] Step 3: Establish a multi-threshold judgment mechanism, compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds, and obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is spectrum observation data when the sun is not erupting, use the first processing mode to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, use the second processing mode to update the real-time background noise value;

[0076] The specific steps include:

[0077] Step 301: Set multiple thresholds, where threshold T_h1 is the power spectrum entropy threshold, T_w1 is the square accumulation value of the power spectrum, which can be called the energy threshold; threshold T_sk1 is the spectral kurtosis threshold of the extreme point, which is a specific range and can be called the spectral kurtosis threshold.

[0078] Step 302: When the eigenvalue H of the power spectrum of this frame is greater than T_h1, the eigenvalue W is less than T_w1 and there is no extreme point exceeding MAX_T, the data of this frame is regarded as spectrum observation data when there is no communication interference signal and the sun is not erupting.

[0079] When the spectrum kurtosis of the extreme point of the current frame data exceeds the threshold value T_sk1, it is considered that the current frame data contains a communication interference signal, and the data near the extreme point will be smoothed and filtered.

[0080] (1) When the power spectrum of this frame is data without communication interference signals and the sun is not shining, the real-time background noise value of the system is updated, and the background noise value corresponding to each frequency point of the model is the average value of such data set for continuous frames, such as 50 frames. The value of continuous frames can also be selected according to actual conditions.

[0081] Taking 50 consecutive frames as an example, the updating method is to assign the data of this frame to DL(k), and the original DL(k) value to DN-1(k). Similarly, the original D2(k) value is assigned to D1(k), and D(k) is the latest updated average value.

[0082] D(k)=(D1(k)+D2(k)+…+D49(k)+DL(k)) / L (5), the value range of k in formula (5) is 1~4096, that is, the k value corresponding to each frequency point, and L is the number of consecutive frames

[0083] This step can be used to obtain the latest noise floor data of the instrument, because the noise floor data of the instrument may change with time, temperature and other factors.

[0084] (2) When the power spectrum of this frame contains a communication interference signal, the data near the extreme point is first smoothed and filtered, and then the real-time background noise value of the system is updated by using the first processing mode mentioned above, that is, processing the data without a communication interference signal and when the sun is not shining.

[0085] Step 4: Based on the noise situation of the solar radio telescope system, the noise floor value of the corresponding mode is subtracted by the spectrum subtraction method to obtain the anti-interference signal.

[0086] Using the spectrum subtraction method, the corresponding updated noise floor value D(k) is subtracted from the real-time observed spectrum data of the solar radio telescope to obtain new spectrum data.

[0087] The above steps are a spectrum data processing method for a solar radio telescope. Through this method, the system noise of the solar radio telescope system and the influence of the quiet solar radio radiation signal on the solar radio burst signal can be greatly reduced, the signal-to-noise ratio of the observation system can be improved, and the method has the ability to resist communication interference, thereby improving the quality of the observation data.

[0088] Embodiment 2

[0089] This embodiment provides a system for improving the signal-to-noise ratio of a solar radio telescope system, including:

[0090] A data acquisition module, used to acquire observation spectrum data of a solar radio telescope;

[0091] A feature extraction module is used to calculate the spectral entropy value of the spectral data, the power square accumulation value of the spectral data, and the spectral kurtosis of the spectral data based on the observed spectral data;

[0092] The noise situation acquisition module is used to establish a multi-threshold judgment mechanism, and compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is spectrum observation data when the sun is not erupting, the first processing mode is used to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, the second processing mode is used to update the real-time background noise value;

[0093] The noise elimination module is used to obtain an anti-interference signal by subtracting the noise floor value of the corresponding mode through the spectrum subtraction method based on the noise situation of the solar radio telescope system.

[0094] Among them, in the noise situation acquisition module, the multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulated value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system, including:

[0095] Set multiple thresholds, including a power spectrum entropy value threshold T_h1, an energy threshold T_w1, and a spectrum kurtosis threshold T_sk1;

[0096] If the spectral entropy value of the spectrum data of this frame is greater than the power spectrum entropy value threshold T_h1, the power square cumulative value of the spectrum data is less than the energy threshold T_w1 and there is no extreme point exceeding the extreme point threshold, the data of this frame does not contain communication interference signals and the spectrum observation data when the sun does not erupt;

[0097] If the spectral kurtosis of the extreme point of the data in this frame exceeds the spectral kurtosis threshold T_sk1, the data in this frame contains a communication interference signal.

[0098] Among them, in the feature extraction module, the spectral entropy value of the spectral data, the power square accumulated value of the spectral data, and the spectral kurtosis of the spectral data calculated based on the observed spectral data include:

[0099] The calculation formula of the spectral entropy value of the spectrum data is:

[0100]

[0101]

[0102] The calculation formula of the power square accumulation value of the spectrum data is:

[0103]

[0104] The calculation formula of the spectral kurtosis of the spectrum data is:

[0105]

[0106] Where P1(k) is the probability density of the frequency point, N is the number of frequency points contained in the spectrum data, y(k) is the spectrum amplitude of the kth frequency point, y(i) is the power value corresponding to each frequency point; M is the number of finite points before and after the extreme point as the middle point, parameter SP is the cumulative result of the square power values ​​of the M points, and SN is the cumulative result of the power values ​​of the M points.

[0107] Among them, in the noise situation acquisition module, if the current frame data does not contain a communication interference signal and the spectrum observation data when the sun does not erupt, the first processing mode is used to update the real-time background noise value of the system, including:

[0108] D(k)=(D1(k)+D2(k)+…+D49(k)+DL(k)) / L,

[0109] The data of this frame is assigned to DL(k), the original DL(k) value is assigned to DN-1(k), and so on, the original D2(k) value is assigned to D1(k), D(k) is the latest updated average value, and L is the number of consecutive frames.

[0110] Embodiment 3

[0111] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps in the method for improving the signal-to-noise ratio of a solar radio telescope system as described above are implemented.

[0112] Embodiment 4

[0113] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the method for improving the signal-to-noise ratio of a solar radio telescope system as described above are implemented.

[0114] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0115] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for improving the signal-to-noise ratio of a solar radio telescope system, It is characterized in that include: Obtain observation spectrum data from solar radio telescopes; Based on the observed spectrum data, the spectrum entropy value of the spectrum data, the power square accumulation value of the spectrum data and the spectrum kurtosis of the spectrum data are calculated; A multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is a spectrum observation data when the sun is not erupting, the first processing mode is used to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, the second processing mode is used to update the real-time background noise value. Based on the noise situation of the solar radio telescope system, the noise floor value of the corresponding mode is subtracted by the spectrum subtraction method to obtain the anti-interference signal.

2. A method for improving the signal-to-noise ratio of a solar radio telescope system as claimed in claim 1, It is characterized in that The multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system, including: Set multiple thresholds, including a power spectrum entropy value threshold T_h1, an energy threshold T_w1, and a spectrum kurtosis threshold T_sk1; If the spectral entropy value of the spectrum data of this frame is greater than the power spectrum entropy value threshold T_h1, the power square cumulative value of the spectrum data is less than the energy threshold T_w1 and there is no extreme point exceeding the extreme point threshold, the data of this frame does not contain communication interference signals and the spectrum observation data when the sun does not erupt; If the spectral kurtosis of the extreme point of the data in this frame exceeds the spectral kurtosis threshold T_sk1, the data in this frame contains a communication interference signal.

3. A method for improving the signal-to-noise ratio of a solar radio telescope system as claimed in claim 1, It is characterized in that The spectral entropy value of the spectral data, the power square accumulated value of the spectral data, and the spectral kurtosis of the spectral data calculated based on the observed spectral data include: The calculation formula of the spectral entropy value of the spectrum data is: The calculation formula of the power square accumulation value of the spectrum data is: The calculation formula of the spectral kurtosis of the spectrum data is: Where P1(k) is the probability density of the frequency point, N is the number of frequency points contained in the spectrum data, y(k) is the spectrum amplitude of the kth frequency point, y(i) is the power value corresponding to each frequency point; M is the number of finite points before and after the extreme point as the middle point, parameter SP is the cumulative result of the square power values ​​of the M points, and SN is the cumulative result of the power values ​​of the M points.

4. A method for improving the signal-to-noise ratio of a solar radio telescope system as claimed in claim 1, It is characterized in that If the frame of data does not contain a communication interference signal and the spectrum observation data when the sun does not erupt, the real-time background noise value of the system is updated using the first processing mode, including: D(k)=(D1(k)+D2(k)+…+D49(k)+DL(k)) / L, The data of this frame is assigned to DL(k), the original DL(k) value is assigned to DN-1(k), and so on, the original D2(k) value is assigned to D1(k), D(k) is the latest updated average value, and L is the number of consecutive frames.

5. A method for improving the signal-to-noise ratio of a solar radio telescope system as claimed in claim 1, It is characterized in that If the frame data contains a communication interference signal, the second processing mode is used to update the real-time background noise value. The difference from the first processing mode is that the data near the extreme point is firstly smoothed and filtered.

6. A system for improving the signal-to-noise ratio of a solar radio telescope system, It is characterized in that include: A data acquisition module, used to acquire observation spectrum data of a solar radio telescope; A feature extraction module is used to calculate the spectral entropy value of the spectral data, the power square accumulation value of the spectral data, and the spectral kurtosis of the spectral data based on the observed spectral data; The noise situation acquisition module is used to establish a multi-threshold judgment mechanism, and compare the spectral entropy value of the spectrum data, the power square accumulation value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system. If the current frame of data does not contain a communication interference signal and is spectrum observation data when the sun is not erupting, the first processing mode is used to update the real-time background noise value of the system; if the current frame of data contains a communication interference signal, the second processing mode is used to update the real-time background noise value; The noise elimination module is used to obtain an anti-interference signal by subtracting the noise floor value of the corresponding mode through the spectrum subtraction method based on the noise situation of the solar radio telescope system.

7. A system for improving the signal-to-noise ratio of a solar radio telescope system as claimed in claim 6, It is characterized in that In the noise situation acquisition module, the multi-threshold judgment mechanism is established to compare the spectral entropy value of the spectrum data, the power square accumulated value of the spectrum data, and the spectral kurtosis of the spectrum data with the corresponding thresholds to obtain the noise situation of the solar radio telescope system, including: Set multiple thresholds, including a power spectrum entropy value threshold T_h1, an energy threshold T_w1, and a spectrum kurtosis threshold T_sk1; If the spectral entropy value of the spectrum data of this frame is greater than the power spectrum entropy value threshold T_h1, the power square cumulative value of the spectrum data is less than the energy threshold T_w1 and there is no extreme point exceeding the extreme point threshold, the data of this frame does not contain communication interference signals and the spectrum observation data when the sun does not erupt; If the spectral kurtosis of the extreme point of the data in this frame exceeds the spectral kurtosis threshold T_sk1, the data in this frame contains a communication interference signal.

8. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the program is executed by a processor, the steps in a method for improving the signal-to-noise ratio of a solar radio telescope system as described in any one of claims 1 to 5 are implemented.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the program, the steps in the method for improving the signal-to-noise ratio of a solar radio telescope system as described in any one of claims 1 to 5 are implemented.

10. A program product, the program product being a computer program product, comprising a computer program, It is characterized in that When the computer program is executed by a processor, the steps in a method for improving the signal-to-noise ratio of a solar radio telescope system as described in any one of claims 1 to 5 are implemented.

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