Frequency range identification method, device, storage medium and equipment

Abstract

In a frequency range identification method, apparatus, storage medium, and device provided in this specification, radio data of a fast radio burst is obtained, and the cumulative energy distribution and signal-to-noise ratio are determined based on the spectrum of the radio data. Based on the signal-to-noise ratio, a critical threshold is determined, and the frequency at which the rate of change of energy in the cumulative energy distribution reaches the critical threshold is determined as a candidate frequency. Based on the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy, a dominant frequency is determined. From the candidate frequencies, a candidate frequency adjacent to the dominant frequency is selected. Based on the selected candidate frequency, the frequency range of the fast radio burst is determined. That is, the cumulative energy distribution of the radio data is determined, and then the dominant frequency and candidate frequencies are determined by analyzing the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy and the rate of change of energy. Finally, the candidate frequency is selected based on the dominant frequency to accurately determine the frequency range.

Description

Technical Field

[0001] This specification relates to the field of radio astronomy, and in particular to a frequency range identification method, apparatus, storage medium, and device. Background Art

[0002] Fast radio bursts (FRBs) are brief but intense bursts of radio waves originating from deep within the universe. These bursts may be caused by rare cosmic events, such as neutron star collisions or black hole swallowings. Because FRBs may carry important information about the state of cosmic events, they have become a hot topic in modern astronomical research. Within this research field, identifying the frequency range of FRBs is a key step in understanding these radio wave bursts.

[0003] Currently, the frequency range of FRB bursts is typically identified through Gaussian fitting. This involves fitting the spectrum of FRB radio data to a Gaussian distribution, determining the frequency corresponding to the peak in the Gaussian distribution as the center frequency, and estimating the width based on this peak. Finally, the frequency range is determined based on the center frequency and width. However, this Gaussian fitting method has poor accuracy in identifying the frequency range of FRB bursts.

[0004] Based on this, this specification provides a frequency range identification method, apparatus, storage medium and device. Summary of the Invention

[0005] This specification provides a frequency range identification method, apparatus, storage medium and device to partially solve the above-mentioned problems existing in the prior art.

[0006] This manual adopts the following technical solutions:

[0007] This specification provides a frequency range identification method, the method comprising:

[0008] Obtain radio data of fast radio bursts;

[0009] determining, based on a frequency spectrum of the radio data, a cumulative energy distribution of the radio data and a signal-to-noise ratio of the radio data, and determining a critical threshold based on the signal-to-noise ratio, wherein the critical threshold is negatively correlated with the signal-to-noise ratio;

[0010] determining, according to the rate of change of energy in the cumulative energy distribution, a frequency at which the rate of change reaches the critical threshold, as a candidate frequency;

[0011] Determining the dominant frequency of the radio data according to the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy;

[0012] From the candidate frequencies, a candidate frequency adjacent to the dominant frequency is selected, and the frequency range of the fast radio burst is determined according to the selected candidate frequency.

[0013] Optionally, selecting a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determining the frequency range of the fast radio burst according to the selected candidate frequency, specifically includes:

[0014] Determining whether the candidate frequencies are all greater than the dominant frequency;

[0015] If yes, then the starting frequency of the radio data is used as the lower limit endpoint;

[0016] If not, selecting a candidate frequency that is smaller than the dominant frequency and adjacent to the dominant frequency from the candidate frequencies as the lower limit endpoint;

[0017] Determining whether all of the candidate frequencies are smaller than the dominant frequency;

[0018] If yes, then the end frequency of the radio data is used as the upper limit endpoint;

[0019] If not, selecting a candidate frequency that is greater than the dominant frequency and adjacent to the dominant frequency from the candidate frequencies as the upper limit endpoint;

[0020] The frequency range of the fast radio burst is determined according to the lower endpoint and the upper endpoint.

[0021] Optionally, before acquiring the radio data, the method further includes:

[0022] Obtain raw data of fast radio bursts;

[0023] Determine a cross-correlation function between the original data and a preset Gaussian template, and use the time corresponding to the peak of the cross-correlation function as the central moment;

[0024] A time range is determined according to the cross-correlation function and the central time, and raw data within the time range is determined as radio data.

[0025] Optionally, determine a time range, including:

[0026] Determining an initial upper limit time and an initial lower limit time according to the cross-correlation function and the center time;

[0027] The root mean square of the original data between the initial upper limit moment and the initial lower limit moment is used as a reference value;

[0028] When the intensity corresponding to the initial upper limit time in the raw data is less than the reference value, the initial upper limit time is shifted leftward to obtain the target upper limit time; and when the intensity corresponding to the initial lower limit time in the raw data is less than the reference value, the initial lower limit time is shifted rightward to obtain the target lower limit time;

[0029] A time range is determined according to the target upper limit time and the target lower limit time.

[0030] Optionally, the method further includes:

[0031] Setting a high-frequency cutoff value and a low-frequency cutoff value according to the signal-to-noise ratio;

[0032] When the proportion of the cumulative energy in the cumulative energy distribution to the total energy is equal to the high-frequency cutoff value, the frequency corresponding to the high-frequency cutoff value is used as the high-frequency cutoff frequency;

[0033] When the proportion of the cumulative energy in the cumulative energy distribution to the total energy is equal to the low-frequency cutoff value, the frequency corresponding to the low-frequency cutoff value is used as the low-frequency cutoff frequency;

[0034] Determining a cutoff range according to the high-frequency cutoff frequency and the low-frequency cutoff frequency;

[0035] When the frequency range does not fall within the cutoff range, the frequency range is adjusted according to the cutoff range.

[0036] Optionally, determining a cutoff range according to the high-frequency cutoff frequency and the low-frequency cutoff frequency specifically includes:

[0037] When there are multiple high-frequency cutoff frequencies, selecting a high-frequency cutoff frequency adjacent to the dominant frequency from the high-frequency cutoff frequencies;

[0038] When there are multiple low-frequency cutoff frequencies, selecting a low-frequency cutoff frequency adjacent to the dominant frequency from the low-frequency cutoff frequencies;

[0039] The cutoff range is determined according to the selected high-frequency cutoff frequency and the selected low-frequency cutoff frequency.

[0040] Optionally, the method further includes:

[0041] determining an original spectrum of the radio data;

[0042] Obtaining an initial spectrum by median filtering according to the original spectrum and a preset median filtering window, and determining a filtering threshold according to the variance of the initial spectrum;

[0043] Marking interference channels of the initial spectrum according to the filtering threshold;

[0044] The radio frequency interference in the radio data is removed according to the interference channel.

[0045] This specification provides a frequency range identification device, comprising:

[0046] Acquisition module, used to obtain radio data of fast radio bursts;

[0047] a signal-to-noise ratio module, configured to determine, based on a frequency spectrum of the radio data, a cumulative energy distribution of the radio data and a signal-to-noise ratio of the radio data, and determine a critical threshold value based on the signal-to-noise ratio, wherein the critical threshold value is negatively correlated with the signal-to-noise ratio;

[0048] a candidate module, configured to determine, based on the rate of change of energy in the cumulative energy distribution, a frequency at which the rate of change reaches the critical threshold, as a candidate frequency;

[0049] A reference module, configured to determine a dominant frequency of the radio data based on a proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy;

[0050] A determination module is used to select a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determine the frequency range of the fast radio burst according to the selected candidate frequency.

[0051] This specification provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, a frequency range identification method is implemented.

[0052] This specification provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, a frequency range identification method is implemented.

[0053] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects: In a frequency range identification method provided in this specification, radio data of a fast radio burst is obtained, and the cumulative energy distribution and signal-to-noise ratio are determined based on the spectrum of the radio data, and then a critical threshold is determined based on the signal-to-noise ratio. Based on the rate of change of energy in the cumulative energy distribution, the frequency at which the rate of change reaches the critical threshold is determined as a candidate frequency. Based on the proportion of the cumulative energy of each frequency in the cumulative energy distribution to the total energy, the dominant frequency of the radio data is determined, and from the candidate frequencies, a candidate frequency adjacent to the dominant frequency is selected, and the frequency range of the fast radio burst is determined based on the selected candidate frequency.

[0054] It can be seen from the above method that by determining the cumulative energy distribution of radio data and determining the frequency at which the rate of change of the cumulative energy distribution reaches a critical threshold, the candidate frequency is selected based on the dominant frequency, and then the frequency range is obtained. That is, by analyzing the cumulative energy distribution of radio data and the rate of change of energy, the frequency range can be accurately determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The exemplary embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation of this specification. In the drawings:

[0056] Figure 1 A flowchart of a frequency range identification method provided in this specification;

[0057] Figure 2 A schematic diagram for determining a frequency to be selected provided in this specification;

[0058] Figure 3 A schematic diagram for determining the frequency range provided in this specification;

[0059] Figure 4 A schematic diagram for determining the cutoff range provided in this specification;

[0060] Figure 5 A schematic diagram of a frequency range identification device provided in this specification;

[0061] Figure 6 This is a schematic diagram of the electronic device structure corresponding to a frequency range identification method provided in this specification. DETAILED DESCRIPTION

[0062] To make the objectives, technical solutions, and advantages of this specification more clear, the following will clearly and completely describe the technical solutions of this specification in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this specification.

[0063] The process of executing a frequency range identification method in this specification involves processing image data. Therefore, in the embodiments of this specification, this frequency range identification method can be executed by a server. Of course, this specification does not limit the device that executes this frequency range identification method. For example, personal computers and mobile terminals can perform frequency range identification. For ease of description, the following description uses a server as the execution entity.

[0064] The technical solutions provided by the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0065] Figure 1 This is a flow chart of a frequency range identification method provided in this specification, comprising the following steps:

[0066] S100: Obtain radio data of fast radio bursts.

[0067] In one or more embodiments of this specification, the specific device implementing a frequency range identification method is not limited, for example, a personal computer, a mobile terminal, or a server. However, since subsequent steps involve operations such as data processing, which require high computing resources and are generally performed by a server, this specification will subsequently describe a frequency range identification method using a server as an example. The server can be a single device or composed of multiple devices, such as a distributed server, and this specification does not impose any restrictions on this.

[0068] In one or more embodiments of this specification, a fast radio burst (FRB) is a type of short but intense burst of radio waves originating from deep within the universe. In order to determine the cumulative energy distribution and signal-to-noise ratio of the radio data in subsequent steps, in this step, radio data of the FRB is acquired.

[0069] Specifically, the server can obtain radio data of FRBs. The specification does not limit the method of obtaining FRBs, such as using a radio telescope to observe and obtain, or other acquisition equipment.

[0070] It should be noted that FRB radio data has complex background noise, in which radio frequency interference (RFI) usually comes from artificial radio transmission sources, such as radar, wireless communication equipment, etc., and since radio frequency interference can be very strong, in order to ensure the quality of radio data. Therefore, the server can identify the interference channel in the radio data, thereby removing the RFI in the radio data. Of course, this specification does not limit the specific method of removing RFI, such as median filtering, fast Fourier transform interference removal, zero dispersion interference removal, etc. The process of removing RFI by median filtering is as follows:

[0071] First, the server determines the raw spectrum of the radio data.

[0072] Secondly, the server slides a preset median filter window on the original spectrum to obtain an initial spectrum, and then determines a filtering threshold according to the variance of the initial spectrum.

[0073] Finally, the server marks the interference channels in the initial spectrum based on the filtering threshold, thereby removing radio frequency interference in the radio data according to the interference channels.

[0074] S102: Determine the cumulative energy distribution of the radio data and the signal-to-noise ratio of the radio data according to the frequency spectrum of the radio data, and determine a critical threshold according to the signal-to-noise ratio, where the threshold is negatively correlated with the signal-to-noise ratio.

[0075] In one or more embodiments of the present specification, in order to determine the frequency to be selected in subsequent steps, in this step, the server may determine the cumulative energy distribution of the radio data and the signal-to-noise ratio of the radio data based on the spectrum of the radio data in step S100, and determine the critical threshold based on the signal-to-noise ratio.

[0076] Specifically, the server may determine the cumulative energy distribution of the radio data and the signal-to-noise ratio of the radio data according to the spectrum of the radio data in step S100, and determine a critical threshold according to the signal-to-noise ratio, wherein the threshold is negatively correlated with the signal-to-noise ratio.

[0077] According to the signal-to-noise ratio, the threshold is determined as follows:

[0078]

[0079] Wherein, n is a preset fixed value that can be set according to actual needs, T is the threshold, and SNR is the signal-to-noise ratio.

[0080] It should be noted that the critical threshold is determined based on the signal-to-noise ratio of the radio data. This critical threshold dynamically changes to adapt to the background noise of the radio data, thereby ensuring the reliability of the candidate frequency selection determined based on this critical threshold in subsequent steps. Simultaneously, spectrum information is obtained by summing the spectrum of the radio data, and the cumulative energy distribution of the radio data is obtained through cumulative summation and normalization based on this spectrum information.

[0081] S104: Determine, according to the rate of change of energy in the cumulative energy distribution, a frequency when the rate of change reaches the critical threshold, as a candidate frequency.

[0082] In one or more embodiments of this specification, in order to select a candidate frequency in subsequent steps, in this step, the server needs to determine the candidate frequency based on the rate of change of energy in the cumulative energy distribution in step S104 and the critical threshold.

[0083] Specifically, the server may use the rate of change of energy in the cumulative energy distribution in step S102, and when the rate of change reaches the critical threshold determined in step S102, the frequency corresponding to the critical threshold is used as the candidate frequency. The rate of change of energy in the cumulative energy distribution changes dynamically, and the frequency corresponding to the critical threshold when the rate of change changes is the candidate frequency. For example, if the rate of change changes from small to large (or from large to small) within a frequency range and reaches the critical threshold for the first time, the frequency corresponding to the critical threshold when the rate of change reaches the critical threshold is used as the candidate frequency. The specific method of determining the rate of change of energy in the cumulative energy distribution is not limited in this specification, such as the differential of the cumulative energy distribution.

[0084] like Figure 2 As shown, this is a schematic diagram for determining the candidate frequency provided in this specification. The server can determine the curve formed by the rate of change of energy in the cumulative energy distribution and the straight line where the critical threshold is located, and by determining the intersection of the curve and the straight line, the candidate frequency corresponding to each intersection is obtained. The value of the black horizontal dotted line on the vertical axis in the figure is the critical threshold.

[0085] S106: Determine the dominant frequency of the radio data according to the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy.

[0086] S108: Selecting a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determining a frequency range of the fast radio burst according to the selected candidate frequency.

[0087] In one or more embodiments of the present specification, in this step, the server needs to determine the dominant frequency in the radio data based on the proportion of the cumulative energy of each frequency in the cumulative energy distribution determined in step S102 in the total energy, and select a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and then determine the frequency range of the fast radio burst based on the selected candidate frequency.

[0088] Specifically, the server can determine the dominant frequency of the radio data based on the proportion of the cumulative energy of each frequency in the cumulative energy distribution determined in step S102 to the total energy, and select a candidate frequency adjacent to the dominant frequency from each candidate frequency, and then determine the frequency range of the fast radio burst based on the selected candidate frequency. When determining the frequency range based on the selected candidate frequency, the situations are divided into the following:

[0089] First, two candidate frequencies are selected. The frequency that is smaller than the dominant frequency is used as the lower endpoint, the frequency that is larger than the dominant frequency is used as the upper endpoint, and the range between the lower and upper endpoints is used as the frequency range of the fast radio burst.

[0090] Next, a candidate frequency is selected that is greater than the dominant frequency. This candidate frequency is used as the upper limit, the starting frequency of the radio data is used as the lower limit, and the range between the lower and upper limits is used as the frequency range of the fast radio burst.

[0091] Finally, a candidate frequency is selected that is smaller than the dominant frequency. This candidate frequency is used as the lower limit endpoint, the end frequency in the radio data is used as the lower limit endpoint, and the range between the lower limit endpoint and the upper limit endpoint is used as the frequency range of the fast radio burst.

[0092] It should be noted that the determination of the dominant frequency and the selection of the candidate frequency based on the dominant frequency are to ensure that the determined frequency range contains the main component of the fast radio burst. Therefore, when determining the dominant frequency of the radio data based on the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy, the frequency of the "main component" needs to be selected as the dominant frequency. Of course, the specific method of determining the dominant frequency is not limited in this specification and can be set according to actual needs. For example, in actual applications, the frequency corresponding to a proportion of 0.5 can be used as the dominant frequency, which represents that the probability of the random frequency before and after the frequency corresponding to 0.5 is 0.5. Therefore, 0.5 must be the main component of the radio data. Of course, this value is only used for illustration and does not limit the frequency corresponding to a proportion of 0.5 to be the dominant frequency.

[0093] like Figure 3 As shown, continue to use Figure 2 Taking the example of radio data, when the cumulative energy of each frequency in the cumulative energy distribution accounts for 0.5 of the total energy, the frequency corresponding to 0.5 is taken as the dominant frequency, and from each candidate frequency, the candidate frequency adjacent to the dominant frequency is selected on the frequency axis. Based on the selected candidate frequency, the frequency range of the fast radio burst is determined.

[0094] In the above method, the server removes radio frequency interference from the radio data and obtains the radio data of the fast radio burst, and then determines the cumulative energy distribution and signal-to-noise ratio of the radio data based on the spectrum of the radio data. The critical threshold is determined according to the signal-to-noise ratio, and the frequency when the rate of change of energy in the cumulative energy distribution reaches the critical threshold is determined as the candidate frequency. The dominant frequency is determined according to the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy, and among the candidate frequencies, the candidate frequency adjacent to the dominant frequency is selected, so as to accurately determine the frequency range of the burst frequency in the fast radio burst.

[0095] In addition, this specification provides a method for setting a high-frequency cutoff value and a low-frequency cutoff value according to the signal-to-noise ratio, and based on the high-frequency cutoff value and the low-frequency cutoff value, respectively determining the high-frequency cutoff frequency and the low-frequency cutoff frequency by accumulating energy distribution, thereby obtaining a cutoff range, and then adjusting the frequency range determined in step S108 based on the cutoff range. The details are as follows:

[0096] In one or more embodiments of the present specification, the server may set a high-frequency cutoff value and a low-frequency cutoff value according to the signal-to-noise ratio determined in step S102. The frequency corresponding to the high-frequency cutoff value in which the cumulative energy in the cumulative energy distribution in step S102 accounts for the proportion of the total energy is used as the high-frequency cutoff frequency. Similarly, the frequency corresponding to the low-frequency cutoff value in which the cumulative energy in the cumulative energy distribution in step S102 accounts for the proportion of the total energy is used as the low-frequency cutoff frequency. The cutoff range is determined based on the high-frequency cutoff frequency and the low-frequency cutoff frequency. When the frequency range determined in step S108 does not fall within the cutoff range, the frequency range is adjusted according to the cutoff range. The specific method of "determining the high-frequency cutoff value and the low-frequency cutoff value according to the signal-to-noise ratio" is not limited in the present specification and can be set according to actual needs. For example, the low-frequency cutoff value can be 1 / signal-to-noise ratio, and the high-frequency cutoff value can be 1-1 / signal-to-noise ratio.

[0097] When the frequency range determined in step S108 does not fall within the cutoff range, the frequency range is adjusted according to the cutoff range as follows:

[0098] When the frequency range does not fall within the cutoff range, if the upper endpoint in the frequency range is outside the cutoff range and the rate of change of energy of the upper endpoint in the cumulative energy distribution is a critical threshold, then the upper endpoint is adjusted to the high-frequency cutoff frequency of the cutoff range; if the lower endpoint in the frequency range is outside the cutoff range and the rate of change of energy of the lower endpoint in the cumulative energy distribution is a critical threshold, then the lower endpoint is adjusted to the low-frequency cutoff frequency of the cutoff range.

[0099] It should be noted that when the upper endpoint of the time range in step S108 is the frequency corresponding to the "rate of change of energy in the cumulative energy distribution reaching a critical threshold," if the upper endpoint is outside the cutoff range, the upper endpoint can be adjusted to the high-frequency cutoff frequency of the cutoff range. If the upper endpoint is the end frequency of the radio data, no adjustment is required. Similarly, when the lower endpoint of the time range in step S108 is the frequency corresponding to the "rate of change of energy in the cumulative energy distribution reaching a critical threshold," if the lower endpoint is outside the cutoff range, the lower endpoint can be adjusted to the high-frequency cutoff frequency of the cutoff range. If the lower endpoint is the start frequency of the radio data, no adjustment is required.

[0100] like Figure 4As shown, if the critical threshold and the low-frequency cutoff value are both 1 / SNR, then the value of the upper black horizontal line on the vertical axis in the figure is the high-frequency cutoff value, and the value of the lower black horizontal line on the vertical axis is the critical threshold (or low-frequency cutoff value). Determine the high-frequency cutoff frequency corresponding to when the cumulative energy in the cumulative energy distribution accounts for the high-frequency cutoff value in the total energy, and the low-frequency cutoff frequency corresponding to when the cumulative energy in the cumulative energy distribution accounts for the low-frequency cutoff value in the total energy, and obtain the cutoff range. In the figure, the lower endpoint and the upper endpoint are determined from the selected frequencies where the rate of change of energy in the cumulative energy distribution reaches the critical threshold, and in the figure, the upper endpoint and the lower endpoint both fall outside the cutoff range, that is, when the determined frequency range is outside the cutoff range, the frequency range is adjusted according to the cutoff range.

[0101] It should be noted that there may be multiple high-frequency cutoff frequencies and low-frequency cutoff frequencies determined above. Therefore, when there are multiple high-frequency cutoff frequencies, the high-frequency cutoff frequency adjacent to the dominant frequency determined in step S106 on the frequency axis is selected from the high-frequency cutoff frequencies. When there are multiple low-frequency cutoff frequencies, the low-frequency cutoff frequency adjacent to the dominant frequency determined in step S106 on the frequency axis is selected from the low-frequency cutoff frequencies. The cutoff range is then determined based on the selected high-frequency cutoff frequency and the selected low-frequency cutoff frequency.

[0102] In the above, by setting high-frequency and low-frequency cutoff values ​​and determining a cutoff range based on the cumulative energy distribution, the frequency range is adjusted when the frequency range determined by the candidate frequency is not within the cutoff range. The cutoff range defines the celestial radiation signals concentrated within the total frequency range of the radio data; that is, the cutoff range reflects the frequency concentration of the celestial radiation signals. Therefore, the frequency range of fast radio bursts can be adjusted based on this cutoff range, improving the reliability of determining the frequency range of fast radio bursts.

[0103] In addition, this manual provides a process for determining a time range based on the cross-correlation function between a preset Gaussian template and the raw data of a fast radio burst, and using the raw data within the time range as radio data, as follows:

[0104] In one or more embodiments of the present specification, the server may obtain the raw data of the fast radio burst, determine the cross-correlation function between the raw data and a preset Gaussian template, use the time corresponding to the peak of the cross-correlation function as the central moment, determine the time range based on the central moment and the cross-correlation function, and select the raw data within the time range as the radio data.

[0105] First, the server can obtain raw fast radio burst data. The server can preprocess the obtained raw data. This specification does not limit the specific methods of preprocessing, such as de-dispersion, filtering, and baseline subtraction. The relevant technologies for pre-processing such as de-dispersion are relatively mature and will not be detailed here.

[0106] Secondly, the server can slide a preset Gaussian template over the raw data to determine the cross-correlation function and use the time corresponding to the peak of the cross-correlation function as the center moment. The specific values ​​of the pulse parameters in the Gaussian template are not limited in this specification and can be set according to actual needs. The cross-correlation function represents the degree of match between the two signals, so the time corresponding to the peak of the cross-correlation function is the time when the two signals are most closely matched, and this time is used as the center moment.

[0107] Finally, the server can determine the time range based on the cross-correlation function and the center moment, and obtain the raw data within the time range as radio data. This specification does not limit the specific method of determining the time range based on the cross-correlation function and the center moment. For example, the value of the cross-correlation function can be determined as the full width at half maximum (i.e., the pulse width at 1 / 2 the peak), and then the time range is determined with the center moment as the center and the pulse width as the time width.

[0108] It should be noted that because the raw data of fast radio bursts is relatively large, it is possible to select raw data within a certain time range as radio data. However, manual selection is highly subjective and inefficient. Therefore, in the above-mentioned determination of the cross-correlation function using a Gaussian template, since the Gaussian template has a smooth peak and symmetrical shape, it can be used to detect the pulse signal in the raw data, thereby determining the center moment of the burst in the raw data. Then, based on this center moment and the pulse width preset in the Gaussian template, the time range is determined, which is highly efficient and objective.

[0109] In addition, this specification provides for adjusting the "time range determined by the cross-correlation function and the central moment", as follows:

[0110] In one or more embodiments of the present specification, the server may determine the initial upper limit time and the initial lower limit time based on the cross-correlation function and the center time, and use the root mean square of the original data between the initial upper limit time and the initial lower limit time as the reference value.

[0111] If the intensity corresponding to the value to the left of the initial upper limit is less than the reference value, the initial upper limit is shifted left to obtain the target upper limit. If the intensity corresponding to the value to the right of the initial lower limit is less than the reference value, the initial upper limit is shifted right to obtain the target lower limit. The time range is determined based on the target upper and lower limit times.

[0112] The above is a frequency range identification method provided in one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding frequency range identification device, such as Figure 5 shown.

[0113] An acquisition module 500 is configured to acquire radio data of a fast radio burst and remove radio frequency interference from the radio data to obtain radio data;

[0114] a signal-to-noise ratio module 501, configured to determine, based on the frequency spectrum of the radio data, a cumulative energy distribution of the radio data and a signal-to-noise ratio of the radio data, and determine a critical threshold value based on the signal-to-noise ratio, wherein the critical threshold value is negatively correlated with the signal-to-noise ratio;

[0115] A selection module 502 is configured to determine, based on the rate of change of energy in the cumulative energy distribution, a frequency at which the rate of change reaches the critical threshold, as a frequency to be selected;

[0116] A reference module 503 is configured to determine a dominant frequency of the radio data based on a proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy;

[0117] The determination module 504 is configured to select a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determine the frequency range of the fast radio burst according to the selected candidate frequency.

[0118] Optionally, the acquisition module 500 is specifically used to obtain the raw data of the fast radio burst; determine the cross-correlation function of the raw data and a preset Gaussian template, and take the time corresponding to the peak in the cross-correlation function as the central moment; determine the time range according to the cross-correlation function and the central moment, and determine the raw data within the time range as radio data.

[0119] Optionally, the acquisition module 500 is also used to determine the initial upper limit moment and the initial lower limit moment based on the cross-correlation function and the center moment; take the root mean square of the original data between the initial upper limit moment and the initial lower limit moment as the reference value; when the intensity corresponding to the initial upper limit moment in the original data is less than the reference value, the initial upper limit moment is shifted left to obtain the target upper limit moment, and when the intensity corresponding to the initial lower limit moment in the original data is less than the reference value, the initial lower limit moment is shifted right to obtain the target lower limit moment; determine the time range based on the target upper limit moment and the target lower limit moment.

[0120] Optionally, the acquisition module 500 is further used to determine the original spectrum of the radio data; obtain an initial spectrum through median filtering based on the original spectrum and a preset median filtering window, and determine a filtering threshold based on the variance of the initial spectrum; mark the interference channel of the initial spectrum based on the filtering threshold; and remove radio frequency interference in the radio data based on the interference channel.

[0121] Optionally, the determination module 504 is specifically used to determine whether the candidate frequencies are all greater than the dominant frequency; if so, the starting frequency of the radio data is used as the lower limit endpoint; if not, a candidate frequency that is smaller than the dominant frequency and adjacent to the dominant frequency is selected from the candidate frequencies as the lower limit endpoint; determine whether the candidate frequencies are all smaller than the dominant frequency; if so, the ending frequency of the radio data is used as the upper limit endpoint; if not, a candidate frequency that is larger than the dominant frequency and adjacent to the dominant frequency is selected from the candidate frequencies as the upper limit endpoint; and determine the frequency range of the fast radio burst according to the lower limit endpoint and the upper limit endpoint.

[0122] Optionally, the determination module 504 is further used to set a high-frequency cutoff value and a low-frequency cutoff value according to the signal-to-noise ratio; when the cumulative energy in the cumulative energy distribution accounts for the high-frequency cutoff value in the total energy, the frequency corresponding to the high-frequency cutoff value is used as the high-frequency cutoff frequency; when the cumulative energy in the cumulative energy distribution accounts for the low-frequency cutoff value in the total energy, the frequency corresponding to the low-frequency cutoff value is used as the low-frequency cutoff frequency; determine a cutoff range according to the high-frequency cutoff frequency and the low-frequency cutoff frequency; when the frequency range does not fall within the cutoff range, adjust the frequency range according to the cutoff range.

[0123] Optionally, the determination module 504 is further configured to, when there are multiple high-frequency cutoff frequencies, select a high-frequency cutoff frequency adjacent to the dominant frequency from the high-frequency cutoff frequencies; when there are multiple low-frequency cutoff frequencies, select a low-frequency cutoff frequency adjacent to the dominant frequency from the low-frequency cutoff frequencies; and determine a cutoff range based on the selected high-frequency cutoff frequency and the selected low-frequency cutoff frequency.

[0124] This specification also provides a computer-readable storage medium, which stores a computer program that can be used to execute the above Figure 1 A frequency range identification method is provided.

[0125] This manual also provides Figure 6 The schematic structure diagram of the electronic device shown in FIG. Figure 6As mentioned above, at the hardware level, the device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0126] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements today can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD through their own programming, without having to hire a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly done using "logic compiler" software. This is similar to the software compiler used when developing programs. Before compilation, the original code must also be written in a specific programming language, called a hardware description language (HDL). There is not just one HDL, but many, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that by simply programming the method flow in one of these hardware description languages ​​and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0127] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also know that in addition to implementing the controller in a purely computer-readable program code format, the controller can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules that implement the method and structures within the hardware component.

[0128] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0129] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0130] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0131] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 steps in the process. 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.

[0132] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0134] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0135] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0136] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0137] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0138] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0139] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0140] The foregoing is merely an example of the present invention and is not intended to limit the present invention. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A frequency range identification method, characterized in that: include: Obtain radio data of fast radio bursts; determining, based on a frequency spectrum of the radio data, a cumulative energy distribution of the radio data and a signal-to-noise ratio of the radio data, and determining a critical threshold based on the signal-to-noise ratio, wherein the critical threshold is negatively correlated with the signal-to-noise ratio; determining, according to the rate of change of energy in the cumulative energy distribution, a frequency at which the rate of change reaches the critical threshold, as a candidate frequency; Determining the dominant frequency of the radio data according to the proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy; From the candidate frequencies, a candidate frequency adjacent to the dominant frequency is selected, and the frequency range of the fast radio burst is determined according to the selected candidate frequency.

2. The method according to claim 1, wherein: Selecting a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determining a frequency range of the fast radio burst according to the selected candidate frequency, specifically comprising: Determining whether the candidate frequencies are all greater than the dominant frequency; If yes, then the starting frequency of the radio data is used as the lower limit endpoint; If not, selecting a candidate frequency that is smaller than the dominant frequency and adjacent to the dominant frequency from the candidate frequencies as the lower limit endpoint; Determining whether all of the candidate frequencies are smaller than the dominant frequency; If yes, then the end frequency of the radio data is used as the upper limit endpoint; If not, selecting a candidate frequency that is greater than the dominant frequency and adjacent to the dominant frequency from the candidate frequencies as the upper limit endpoint; The frequency range of the fast radio burst is determined according to the lower endpoint and the upper endpoint.

3. The method according to claim 1, wherein: Before acquiring the radio data, the method further includes: Obtain raw data of fast radio bursts; Determine a cross-correlation function between the original data and a preset Gaussian template, and use the time corresponding to the peak of the cross-correlation function as the central moment; A time range is determined according to the cross-correlation function and the central time, and raw data within the time range is determined as radio data.

4. The method according to claim 3, wherein: Determine the timeframe, including: Determining an initial upper limit time and an initial lower limit time according to the cross-correlation function and the center time; The root mean square of the original data between the initial upper limit moment and the initial lower limit moment is used as a reference value; When the intensity corresponding to the initial upper limit time in the raw data is less than the reference value, the initial upper limit time is shifted leftward to obtain the target upper limit time; and when the intensity corresponding to the initial lower limit time in the raw data is less than the reference value, the initial lower limit time is shifted rightward to obtain the target lower limit time; A time range is determined according to the target upper limit time and the target lower limit time.

5. The method according to claim 1, wherein: The method further comprises: Setting a high-frequency cutoff value and a low-frequency cutoff value according to the signal-to-noise ratio; When the proportion of the cumulative energy in the cumulative energy distribution to the total energy is equal to the high-frequency cutoff value, the frequency corresponding to the high-frequency cutoff value is used as the high-frequency cutoff frequency; When the proportion of the cumulative energy in the cumulative energy distribution to the total energy is equal to the low-frequency cutoff value, the frequency corresponding to the low-frequency cutoff value is used as the low-frequency cutoff frequency; Determining a cutoff range according to the high-frequency cutoff frequency and the low-frequency cutoff frequency; When the frequency range does not fall within the cutoff range, the frequency range is adjusted according to the cutoff range.

6. The method according to claim 5, wherein: Determining a cutoff range according to the high-frequency cutoff frequency and the low-frequency cutoff frequency specifically includes: When there are multiple high-frequency cutoff frequencies, selecting a high-frequency cutoff frequency adjacent to the dominant frequency from the high-frequency cutoff frequencies; When there are multiple low-frequency cutoff frequencies, selecting a low-frequency cutoff frequency adjacent to the dominant frequency from the low-frequency cutoff frequencies; The cutoff range is determined according to the selected high-frequency cutoff frequency and the selected low-frequency cutoff frequency.

7. The method according to claim 1, wherein: The method further comprises: determining an original spectrum of the radio data; Obtaining an initial spectrum by median filtering according to the original spectrum and a preset median filtering window, and determining a filtering threshold according to the variance of the initial spectrum; Marking interference channels of the initial spectrum according to the filtering threshold; The radio frequency interference in the radio data is removed according to the interference channel.

8. A frequency range identification device, characterized in that: include: Acquisition module, used to obtain radio data of fast radio bursts; a signal-to-noise ratio module, configured to determine, based on a frequency spectrum of the radio data, a cumulative energy distribution of the radio data and a signal-to-noise ratio of the radio data, and determine a critical threshold value based on the signal-to-noise ratio, wherein the critical threshold value is negatively correlated with the signal-to-noise ratio; a candidate module, configured to determine, based on the rate of change of energy in the cumulative energy distribution, a frequency at which the rate of change reaches the critical threshold, as a candidate frequency; A reference module, configured to determine a dominant frequency of the radio data based on a proportion of the cumulative energy of each frequency in the cumulative energy distribution in the total energy; A determination module is used to select a candidate frequency adjacent to the dominant frequency from the candidate frequencies, and determine the frequency range of the fast radio burst according to the selected candidate frequency.

9. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the method according to any one of claims 1 to 7 is implemented when the processor executes the program.

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