Spectrum display method, device and system

Abstract

The invention relates to the technical field of spectrum monitoring, in particular to a spectrum display method, device and system and a computer readable storage medium. According to the frequency spectrum display method, through an efficient frequency point intensity change detection algorithm and a sparse matrix optimization mode, only frequency points with overlarge changes need to be processed, the processing efficiency and speed of frequency spectrum data are greatly improved, the requirement of frequency spectrum data processing for frequency spectrum display equipment is reduced, the equipment cost is reduced, and the method is suitable for popularization and application. Meanwhile, spectrum data can be presented in real time, and time-sensitive signal analysis and interference detection are greatly improved.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of spectrum monitoring technology, and particularly to a spectrum display method, device, system and computer-readable storage medium. Background Art

[0002] With the rapid development of unmanned aerial vehicle (UAV) technology, the application fields of UAVs have been continuously broadened, covering almost all aspects of modern technology, from agriculture, security, logistics, film and television to search and rescue missions, etc. UAVs communicate, navigate and execute tasks through radio signals. However, due to limited spectrum resources, radio interference problems may occur when different devices work simultaneously in the same frequency band. Especially in urban environments with tight spectrum resources, the spectrum interference problem of UAVs becomes more serious. This interference not only affects the operation safety of UAVs themselves, but also poses a threat to the surrounding communication environment.

[0003] The inventors of the present application found that in order to ensure the stable operation of UAVs in scenarios with complex spectrum environments, a spectrum detection and display system is crucial. Traditional spectrum analysis systems usually rely on complex and expensive hardware devices and cannot achieve portability and real-time performance. The introduction of embedded systems provides a new solution for the acquisition and analysis of spectrum data, enabling spectrum detection through miniaturized devices. However, these embedded systems lack an efficient real-time data display platform and are difficult to meet the high requirements of users for visual data analysis. Summary of the Invention

[0004] In view of the above problems, embodiments of the present application provide a spectrum display method, device, system and computer-readable storage medium to solve the above technical problems existing in the prior art.

[0005] In one aspect of the embodiments of the present application, a spectrum display method is provided, which includes:

[0006] Obtain spectrum data of a signal to be detected, where the spectrum data includes frequency point information and intensity values of frequency points;

[0007] Determine the intensity difference of each frequency point in the spectrum data according to the intensity values of each frequency point in the current frame and the intensity values of each frequency point in the previous frame;

[0008] If the intensity difference is greater than a preset intensity threshold, generate a sparse matrix according to the intensity difference and the frequency point information corresponding to the intensity difference;

[0009] Display the spectrum information of the signal to be detected according to the sparse matrix.

[0010] Preferably, in some embodiments, determining the intensity difference of each frequency point in the spectral data according to the intensity values of each frequency point in the current frame and the intensity values of each frequency point in the previous frame further includes:

[0011] Dividing the spectral data of the signal to be detected into blocks;

[0012] Determining the change value corresponding to each block according to the intensity values of each frequency point in each block;

[0013] If the change value is greater than a preset change threshold, determining the block corresponding to the change value as a changed block;

[0014] Determining the intensity difference of each frequency point according to the intensity values of each frequency point in the changed block in the current frame and the intensity values of each frequency point in the changed block in the previous frame.

[0015] Preferably, in some embodiments, determining the change value corresponding to each block according to the intensity values of each frequency point in each block includes:

[0016] Determining the intensity average value corresponding to each block according to the intensity values of each frequency point in each block;

[0017] Determining the difference between the intensity average value of each block corresponding to the current frame and the intensity average value of each block corresponding to the previous frame.

[0018] Preferably, in some embodiments, determining the change value corresponding to each block according to the intensity values of each frequency point in each block includes:

[0019] Determining the intensity maximum value corresponding to each block according to the intensity values of each frequency point in each block;

[0020] Determining the difference between the intensity maximum value of each block corresponding to the current frame and the intensity maximum value of each block corresponding to the previous frame.

[0021] Preferably, in some embodiments, the sparse matrix includes the intensity difference, the row index value corresponding to the intensity difference, and the column index value corresponding to the intensity difference; or,

[0022] The sparse matrix includes the intensity difference, the row index value corresponding to the intensity difference, and the column index pointer corresponding to the intensity difference.

[0023] Preferably, in some embodiments, displaying the spectral information of the signal to be detected according to the sparse matrix includes:

[0024] Redrawing the corresponding frequency points in the spectral data according to the frequency point information corresponding to the frequency points with the intensity difference greater than zero in the sparse matrix.

[0025] Preferably, in some embodiments, redrawing the corresponding frequency points in the spectral data according to the frequency point information corresponding to the frequency points in the sparse matrix where the intensity difference is greater than zero includes:

[0026] Displaying the spectral information corresponding to the frequency points according to the intensity difference corresponding to the frequency points in the sparse matrix and a preset color mapping table.

[0027] Another aspect of the embodiments of the present application further provides a spectral display device, including: a processor, a memory, a communication interface, and a communication bus. The processor, the memory, and the communication interface complete mutual communication through the communication bus;

[0028] The memory is used to store at least a program, and the program causes the processor to execute the operations of the spectral display method described in any of the above embodiments.

[0029] A third aspect of the embodiments of the present application further provides a spectral display system, including: a frequency detection device and the spectral display device described in any of the above embodiments;

[0030] The frequency detection device is used to obtain the spectral data of the signal to be detected and send the spectral data to the spectral display device;

[0031] The spectral display device is used to perform spectral display according to the spectral data.

[0032] A fourth aspect of the embodiments of the present application further provides a computer-readable storage medium. When the at least one program stored in the storage medium runs on a spectral display device, the spectral display device is caused to execute the operations of the spectral display method described in any of the above embodiments.

[0033] In summary, in the embodiments of the present application, by obtaining the intensity differences of each frequency point in the current frame and the previous frame of the spectrum data, generating a sparse matrix for the frequency points with intensity differences greater than the preset intensity threshold, recording the change of the intensity values of each frequency point through the sparse matrix, and performing local update and rendering on the display of the spectrum data according to the frequency point information in the sparse matrix, only the display results of the frequency points with intensity change values greater than the preset intensity threshold need to be updated, and there is no need to update the display of other frequency points, which greatly reduces the calculation and storage overhead of spectrum display. At the same time, for the spectrum display method, system and device proposed in the embodiments of the present application, the change of the intensity of each frequency point can also be statistically analyzed by means of block division first, and only the frequency points within the block with larger changes are further analyzed and displayed. In this way, the efficiency of spectrum data processing and the timeliness of display are further improved. The spectrum display method proposed in the embodiments of the present application can support static display of the spectrum and also support dynamic display effects such as waterfall flow display of the spectrum, meeting the high requirements of users for data visualization analysis.

[0034] The above description is only an overview of the technical solutions in the embodiments of the present application. In order to understand the technical means of the embodiments of the present application more clearly, it can be implemented according to the content of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present application more obvious and understandable, the specific embodiments of the present application are specifically described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings are only used to illustrate the embodiments and are not considered as limitations to the present application. Throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0036] Figure 1 is a schematic structural diagram of a spectrum display system proposed in the embodiments of the present application;

[0037] Figure 2 is a schematic structural diagram of a spectrum display device proposed in the embodiments of the present application;

[0038] Figure 3 is a schematic flowchart of a spectrum display method proposed in the embodiments of the present application;

[0039] Figure 4 is a schematic flowchart of another spectrum display method proposed in the embodiments of the present application;

[0040] Figure 5 is a schematic signaling flowchart of a spectrum display system proposed in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0042] Spectrum Analysis is a signal processing technique used to convert a signal from the time domain to the frequency domain to study the frequency components of the signal and their distribution. Through spectrum analysis, the intensity of different frequency components in the signal can be visually observed, which helps to analyze the characteristics of the signal, detect interference, identify the signal source, etc. Most existing spectrum analysis systems rely on traditional embedded platforms and high-cost signal processing devices, and it is often difficult to achieve real-time frequency data acquisition and analysis on mobile platforms. This results in a large delay in the acquisition and display of frequency signals. Especially in application scenarios such as drones that require high real-time performance, the delay problem seriously affects the effectiveness of the system. At the same time, the visualization effect of spectrum data in existing systems is poor. The spectrum diagram is not intuitive enough when displayed on mobile devices, lacking a dynamic spectrum stream display, and it is difficult to help users quickly locate interference sources or identify useful signals.

[0043] The inventors of the present application found in their research that Flutter, as a modern cross-platform mobile application development framework, has received extensive attention for its high performance, rich drawing capabilities, and fast development cycle. Through Flutter, efficient graphics processing and data display can be achieved on different platforms such as mobile devices and desktop devices, making it an ideal choice for spectrum data visualization display. However, when the existing spectrum analysis methods based on the Flutter framework perform spectrum display, they often process and render all the spectrum data of the entire data frame, resulting in a very large amount of data processing for the spectrum data, thus causing problems such as untimely spectrum data processing and display lag. Therefore, there is a lack of an efficient real-time data display platform to meet the high requirements of users for data visualization analysis.

[0044] In view of this, the embodiments of the present application propose a spectrum display method, system, and device. By obtaining the intensity differences of each frequency point in the current frame and the previous frame of the spectrum data, generating a sparse matrix for the frequency points with intensity differences greater than a preset intensity threshold, recording the change of the intensity value of each frequency point through the sparse matrix, and performing local update and drawing on the display of the spectrum data according to the frequency point information in the sparse matrix, only the display results of the frequency points with intensity change values greater than the preset intensity threshold need to be updated, and it is not necessary to update the display of other frequency points, which greatly reduces the calculation and storage overhead of spectrum display. At the same time, the spectrum display method, system, and device proposed by the embodiments of the present application can also first statistically analyze the intensity change of each frequency point in a block-by-block manner, and only further analyze and display the frequency points in the block with larger changes. In this way, the efficiency of spectrum data processing and the timeliness of display are further improved. The spectrum display method proposed by the embodiments of the present application can support static display of the spectrum and dynamic display effects such as waterfall flow display of the spectrum, meeting the high requirements of users for data visualization analysis.

[0045] It should be noted that the spectrum display method, device, and system proposed by the embodiments of the present application can be applied to a variety of scenarios, such as: being applied to fields such as drone detection, autonomous vehicle monitoring, and detection of unknown objects. The embodiments of the present application are only illustrated by taking drone detection as an example.

[0046] As Figure 1 shown, it is the architecture diagram of the spectrum display system proposed by the embodiments of the present application. The spectrum display method proposed by the embodiments of the present application can be applied to this spectrum display system. As Figure 1 shown, the spectrum display system includes a spectrum display device 10 and a frequency detection device 20.

[0047] The frequency detection device 20 can be a radar, which is mainly used to obtain the spectrum data of the signal to be detected. The frequency detection device 20 can detect a specific area, for example: scan a specific frequency band of the drone device within a specific area to obtain the spectrum data of all frequency points in this frequency band, and send the obtained spectrum data to the spectrum display device 10.

[0048] The spectrum display device 10 is mainly used to process and analyze the spectrum data obtained by the frequency detection device 20, and display the spectrum information through its own display screen. The user can interact through the display interface of the spectrum display device 10, input the spectrum display method, for example: display a static spectrum diagram or a waterfall flow diagram, etc., and select the frequency points to be displayed. The spectrum display device 10 analyzes the spectrum data according to the frequency points selected by the user, extracts the spectrum data related to the frequency points, and displays it in the way selected by the user.

[0049] Among them, the static spectrum diagram (Static Spectrum Diagram) is a graphical representation method used to display the frequency components and their intensity distributions of a signal at a specific moment. It converts the signal from the time domain to the frequency domain, and obtains the amplitude or power distribution of the signal at different frequencies through spectrum analysis (such as Fourier transform). The static spectrum diagram only shows the spectrum information at a certain moment and does not change with time. The waterfall display is a dynamic spectrum display method used to show the change of the signal spectrum over time. It displays the spectrum data in a three-dimensional effect on a two-dimensional plane, and can intuitively present how the frequency components of the signal evolve over time. The waterfall display can dynamically show the change of the signal spectrum over time. The latest spectrum data is usually displayed at the bottom, and as time goes by, the historical data gradually moves up, forming the effect of a waterfall flow. This dynamic display method is especially suitable for analyzing the dynamic characteristics of signals, such as frequency drift, the appearance and disappearance of interference, etc. In the embodiments of the present application, the spectrum display system proposed in the present application can support both static spectrum diagrams and dynamic spectrum diagrams.

[0050] In some application scenarios, in order to improve the data processing effect and data storage space, the spectrum display device 10 and the frequency detection device 20 can be connected and interacted through the server 30. The frequency detection device 20 sends the detected spectrum data to the server 30. After the server 30 performs integrity verification on the spectrum data, it sends the spectrum data to the spectrum display device 10. The server 30 can be a cloud server. In this way, the requirements of the spectrum display system for the storage space and data processing ability of the spectrum display device 10 can be greatly reduced, which helps the miniaturization of the spectrum display device 10.

[0051] It should be noted that the spectrum display device 10 and the frequency detection device 20 can be different devices connected through a network, or can be an integrated device, which is not limited in the embodiments of the present application.

[0052] The structural diagram of the spectrum display device 10 in the spectrum display system is as Figure 2 shown. The spectrum display device 10 may include: a display screen 101, a processor 102, a memory 106, a communication interface 104, and a communication bus 108.

[0053] Among them, the display screen 101, the processor 102, the memory 106, and the communication interface 104 complete mutual communication through the communication bus 108. The memory 106 is used to store at least one program 110, and the program 110 enables the processor 102 to execute the spectrum display method proposed in the embodiments of the present application.

[0054] Among them, the display screen 101 provides a user interaction interface. On the one hand, the user can select the displayed frequency points and the spectrum display mode through the display screen 101. On the other hand, the spectrum display device provides the spectrum display result to the user through the display screen 101.

[0055] The processor 102 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application. One or more processors included in the spectrum display device 10 may be of the same type of processor, such as one or more CPUs; or may be of different types of processors, such as one or more CPUs and one or more ASICs.

[0056] The memory 106 is used to store the program 110. The memory 106 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0057] The program 110 can be specifically called by the processor 102 to execute the spectrum display method proposed by the embodiments of the present application.

[0058] It should be noted that the spectrum display device 10 may be a handheld terminal or a desktop computer, etc. When the detection result of the signal to be detected in the area to be detected is displayed through the spectrum display system proposed by the embodiments of the present application, the spectrum display device 10 runs the spectrum display method proposed by the embodiments of the present application. The spectrum display method can run in a system based on the Flutter framework or in a system of other frameworks, which does not affect the execution of the spectrum display method. Specifically, the schematic flow chart of the spectrum display method proposed by the embodiments of the present application is as Figure 3 shown, and the method includes the following steps:

[0059] S110: Obtain the spectrum data of the signal to be detected, where the spectrum data includes the frequency point information and intensity value of the frequency point;

[0060] Such as Figure 1As shown, the spectrum display device is connected to the frequency detection device. After the frequency detection device obtains the spectrum data, it sends the spectrum data to the spectrum display device. Among them, the spectrum data is mainly used to display the representation of the signal in the frequency domain. It reflects the frequency components and their intensity distributions of the signal, including frequency point information, intensity values, etc. Among them, the frequency point information is mainly used to represent the frequency range covered by the frequency points, and the frequency range is the width between the highest frequency and the lowest frequency. The intensity value is used to represent the intensity of the signal at different frequencies, usually in units of power, amplitude or decibels. The spectrum data usually also includes background noise data, and the background noise data represents the background noise level when there is no effective signal. In spectrum analysis, it is necessary to filter the background noise data to distinguish the signal data and the background noise data. The spectrum data usually also includes a timestamp, which is used to represent the acquisition time of the spectrum data. The timestamp helps to analyze the change of the frequency signal over time.

[0061] S120: Determine the intensity difference of each frequency point in the spectrum data according to the intensity value of each frequency point in the current frame and the intensity value of each frequency point in the previous frame;

[0062] The spectrum data received by the spectrum display device includes spectrum data at different times. The spectrum data at different times corresponds to different spectrum data frames. The frequency detection device sends spectrum data frames periodically. Usually, the sending period of the spectrum data frame is pre-set. When displaying a static spectrum diagram, the sending period of the frequency data frame is usually 6s - 7s. For a spectrum diagram that needs to be dynamically displayed, the sending period of the frequency data frame is usually 200ms - 300ms. When the spectrum display device supports both static spectrum diagram display and dynamic spectrum diagram display at the same time, it is required that the period for the frequency display device to obtain frequency data frames is at least 200ms - 300ms.

[0063] Among them, the previous frame refers to the spectrum data corresponding to the moment when the spectrum display device is displaying the spectrum data, and the current frame refers to the spectrum data at the latest moment obtained by the spectrum display device.

[0064] When the spectrum display device stores the spectrum data, it usually stores it in the form of a spectrum matrix. A spectrum matrix is a method of organizing and representing spectrum data in a matrix form. It is usually used to store and process the results of spectrum analysis, especially when dynamically analyzing the change of the signal spectrum over time. The spectrum matrix can conveniently represent the frequency components and their intensities of the signal at different time points. The spectrum matrix is usually a two-dimensional array, and its structure is as follows:

[0065] Rows: Represents the frequency axis, and each row corresponds to a specific frequency point.

[0066] Columns: Represents the time axis, and each column corresponds to a specific time point.

[0067] Elements: Represents the signal intensity value at a specific frequency and time point.

[0068] As shown in Table 1, an example of the spectrum matrix is shown.

[0069] Table 1

[0070] Time / Frequency 0 Hz 1 kHz 2 kHz ... 511 kHz 0 ms -40 dB -30 dB -20 dB ... -50 dB 100 ms -45 dB -35 dB -25 dB ... -55 dB 200 ms -50 dB -40 dB -30 dB ... -60 dB ... ... ... ... ... ... 1000 ms -60 dB -50 dB -40 dB ... -70 dB

[0071] For all frequency points in the spectrum data, through the spectrum matrix, the intensity difference ΔD[x, y] of each frequency point in the current frame Dnew and the previous frame Dold can be calculated:

[0072] ΔD[x, y] = Dnew[x, y] - Dold[x, y]

[0073] ΔD[x, y]: Represents the change in the intensity value at the position (x, y) in the spectrum matrix between the current frame and the previous frame, that is, the intensity difference;

[0074] Dnew[]: Represents the current frame spectrum data matrix;

[0075] Dold[]: Represents the previous frame spectrum data matrix;

[0076] (x, y): Represents the row (frequency) and column (time) indices in the spectrum matrix.

[0077] S130: If the intensity difference is greater than the preset intensity threshold, a sparse matrix is generated according to the intensity difference and the frequency point information corresponding to the intensity difference;

[0078] For the intensity difference ΔD[x, y] of each frequency point determined in step S120, when the intensity difference ΔD[x, y] > Tpoint, it is considered that this frequency point is a change point, where Tpoint is the preset intensity threshold for filtering background noise or small fluctuations.

[0079] Record this change point as a triple (x, y, ΔD[x, y]), where x and y are the row (frequency) and column (time) indices in the spectrum matrix, and ΔD[x, y] is the intensity difference of this frequency point. At the same time, a sparse matrix is generated based on the triple (x, y, ΔD[x, y]).

[0080] In the spectrum matrix, if the intensity difference of a frequency point is less than or equal to the preset intensity threshold, it means that the change of this frequency point is small and there is no need to update its display result, and this frequency point will not be recorded in the sparse matrix.

[0081] S140: Display the spectral information of the signal to be detected according to the sparse matrix.

[0082] After completing the judgment of all frequency points in the spectral matrix and generating the sparse matrix through step S130, the sparse matrix records the frequency point information of all frequency points with intensity change values greater than the preset intensity threshold and the corresponding intensity difference in the spectral data of the current frame.

[0083] After completing the construction of the sparse matrix, refresh the spectral display diagram of the previous frame according to the sparse matrix. In the embodiment of the present application, only need to perform a partial refresh on the spectral diagram of the previous frame according to the records of the sparse matrix, that is, only need to redraw the spectral display diagram of the frequency points with large changes in the spectral data of the previous frame, and do not need to refresh the spectral diagrams of all frequency points in the previous frame.

[0084] In the above embodiment, through an efficient frequency point intensity change detection algorithm and sparse matrix optimization method, only need to process the frequency points with too large changes, which greatly speeds up the processing efficiency and speed of spectral data, reduces the requirements for spectral display devices for spectral data processing, reduces equipment costs, and at the same time enables spectral data to be presented in real time, greatly improving the analysis of time-sensitive signals and interference detection.

[0085] Further, in order to further improve the processing efficiency of spectral data, the embodiment of the present application further proposes to perform fast spectral analysis by means of block comparison to determine the intensity difference of each frequency point, so as to quickly locate the frequency points that have changed. As Figure 3 shown, the step S120 further includes:

[0086] S121: Divide the spectral data of the signal to be detected into blocks;

[0087] In order to further improve the speed of spectral data analysis, first divide the obtained spectral data into blocks. For example: the size of the spectral data received by the spectral display device is 300*128, and the block size is 8*8. Divide it into blocks, a total of 37*16 = 592 blocks.

[0088] The size of the block is set in advance and can be set to other sizes according to needs. This is only an exemplary illustration and is not specifically limited.

[0089] S122: Determine the change value corresponding to each block according to the intensity values of the frequency points in each block;

[0090] After the block division is completed, calculate the intensity values of the frequency points in each block in units of blocks to determine the change value of the current frame block relative to the block of the previous frame. Among them, the change value can be the change value of the average intensity corresponding to the block.

[0091] ΔB[i,j] = BlockStatnew[i,j] - BlockStatold[i,j];

[0092] Wherein, ΔB[i,j] represents the change value between the intensity mean value of the previous frame and the intensity mean value of the current frame of the i,j-th block, and is used to measure whether the intensity values of the frequency points within the block have changed significantly.

[0093] i,j: are the block indices (row, column) after the spectral data is segmented

[0094] BlockStatnew[i,j]: is the intensity mean value of the i,j-th block in the current frame, which is the average value of the intensity differences ΔD[x,y] of all frequency points within the block.

[0095] BlockStatold[i,j]: is the intensity mean value of the i,j-th block in the previous frame, which is the average value of the intensity differences ΔD[x,y] of all frequency points within the block in the previous frame.

[0096] By statistically calculating the mean value of the intensity differences of all frequency points within the block to determine the intensity mean value of the block, it can more comprehensively reflect the change situation of the frequency points within the block.

[0097] Optionally, the intensity difference of the maximum intensity value of the corresponding frequency points within the block can also be used as the change value corresponding to the block, that is: BlockStatnew[i,j] is the maximum intensity value in the i,j-th block in the current frame, BlockStatold[i,j] is the maximum intensity value in the i,j-th block in the previous frame, and ΔB[i,j] is the difference of the maximum intensity value of the block. By statistically calculating the difference of the maximum intensity values within the block, it can better reflect whether there are frequency points with large changes within the block.

[0098] S123: If the change value is greater than the preset change threshold, then determine the block corresponding to the change value as a changed block;

[0099] When |ΔB[i,j]| is greater than the preset change threshold Tblock, it is considered that the intensity values of the frequency points within the block have changed greatly, and then determine the block corresponding to the change value as a changed block, and it is necessary to further judge the change situation of each frequency point within the block.

[0100] When |ΔB[i,j]| is less than or equal to the preset change threshold Tblock, it is considered that the intensity values of the frequency points within the block have changed little and no processing is required.

[0101] S124: Determine the intensity difference of each frequency point according to the intensity values of each frequency point in the changed block of the current frame and the intensity values of each frequency point in the changed block of the previous frame.

[0102] After determining the changed block by the above-mentioned block comparison method, only the frequency points in the changed block need to be analyzed, and then the intensity difference of each frequency point can be determined in the same way as in step S120 according to the intensity values of each frequency point in the changed block of the current frame and the intensity values of each frequency point in the changed block of the previous frame.

[0103] After determining the intensity difference of each frequency point, continue with the operation in step S130 to generate a sparse matrix according to the intensity difference and a preset intensity threshold.

[0104] Before judging the change situation of a single frequency point in the above embodiments, the spectrum data is first processed in blocks, and the overall judgment is made in units of blocks. Only when the change of the block is large, it is necessary to further judge each frequency point in the changed block. When the change of the block is small, the step of judging the frequency point is omitted. In this way, the efficiency of judging the change situation of the intensity values of each frequency point is greatly improved, and the hardware requirements for the spectrum display device are reduced.

[0105] In order to further reduce the requirements of the system for the spectrum display device, in some embodiments, when constructing the sparse matrix, multiple methods can be used for construction.

[0106] For example: The coordinate representation method (COO) can be used, that is, the sparse matrix includes the intensity difference, the row index value corresponding to the intensity difference, and the column index value corresponding to the intensity difference. The row index value and the column index value are used to record the row and column coordinates of each changed frequency point, and the intensity difference is used to record the change value of each changed frequency point.

[0107] In order to reduce the storage space of the sparse matrix, the column compression (Compressed Sparse Column, abbreviated as CSC) method can also be used for storage. The column-compressed storage format of the sparse matrix is an efficient sparse matrix storage method. The CSC format greatly reduces the storage space requirement by only storing the non-zero elements and their position information, and also improves the efficiency of matrix operations. The sparse matrix includes the intensity difference, the row index value corresponding to the intensity difference, and the column index pointer corresponding to the intensity difference.

[0108] In the CSC format, the information of the sparse matrix is stored in three arrays:

[0109] Values() array: Store the values of all non-zero elements in the sparse matrix.

[0110] The `row_indices()` array: Stores the row indices corresponding to each non-zero element.

[0111] The `column_pointers()` array: Stores the starting position of the first non-zero element in each column within the `values` array. The length of the array is `n + 1`, where `n` is the number of columns in the matrix. `column_pointers[i]` represents the index of the first non-zero element in the `i`-th column within the `values` array. `column_pointers[n]` is a sentinel value representing the total length of the `values` array.

[0112] The following is an example to illustrate the process of generating a sparse matrix and the process of data storage in CSC format in the above embodiments:

[0113] Assume:

[0114] The spectral matrix sizes of the current frame (`Dnew`) and the previous frame (`Dold`) are 300×128, and the preset intensity threshold is `Tpoint = 20`;

[0115] Partial data of the previous frame (`Dold`) matrix (simplified to a 4x4 region):

[0116]

[0117] Partial data of the current frame (`Dnew`) matrix:

[0118]

[0119] Then the intensity differences between the intensity values of each frequency point in the current frame and those in the previous frame are:

[0120] Calculate the change amount ΔD[x, y] = Dnew[x, y] - Dold[x, y] for each point:

[0121]

[0122] Judge the intensity differences of each frequency point to determine whether they are greater than the preset intensity threshold `Tpoint = 20`. Then the frequency points with larger changes are: (x, y, ΔD[x, y]) = {(0, 2, 20), (1, 1, 25), (1, 3, 30), (2, 2, 40)}.

[0123] Generate a sparse matrix in column-compressed storage CSC format:

[0124] Values = [20, 25, 30, 40], storing the intensity change values of each changing frequency point;

[0125] Row indices = [0, 1, 1, 2], storing the row indices of each changing frequency point;

[0126] Column Pointers = [0, 1, 0, 1, 4], storing the starting position of the first non-zero element in each column in the values array, that is, the column index pointer corresponding to the intensity difference.

[0127] The above embodiments store the points with large intensity value changes in the form of a sparse matrix, improving the data storage efficiency, reducing the storage space of spectrum data, and also reducing the hardware requirements for spectrum display devices.

[0128] After generating the sparse matrix, the spectrum display device displays the spectrum information according to the sparse matrix. In the embodiments of the present application, it is only necessary to redraw the corresponding frequency points in the spectrum data according to the frequency point information corresponding to the frequency points with an intensity difference greater than zero in the sparse matrix.

[0129] At the same time, in order to highlight the frequency points with large changes, during display, the spectrum information corresponding to the frequency points can be displayed according to the intensity difference corresponding to the frequency points in the sparse matrix and a preset color mapping table. Map the intensity change value ΔD[x, y] to different color gradients according to the preset color mapping table, for example: red represents a strong positive change, blue represents a strong negative change, etc., to highlight the changed frequency points.

[0130] When drawing a static spectrum diagram, first, it is necessary to clear the old changed area according to the sparse matrix, erase the changed area recorded in the previous frame, release the drawing resources, and update the changed points one by one according to the frequency points and intensity values recorded in the sparse matrix.

[0131] When drawing a waterfall plot, since it is dynamically displayed, the historical data can be scrolled up through a scrolling update mechanism, moving the entire previous frame of data up one row, clearing the bottom row to make room for new data. At the same time, according to the information of the changed frequency points recorded in the sparse matrix, draw the non-zero points in the sparse matrix to complete the update of the waterfall plot.

[0132] In order to more specifically illustrate the process of the spectrum display system executing the spectrum display method, Figure 5 A signaling diagram when the spectrum display system executes the spectrum display method is shown.

[0133] In Figure 5 it includes a spectrum display device, a server, and a radar. The spectrum display device includes a user interface, a processing module, and a data stream module. The radar is the Figure 1 spectrum detection device in

[0134] When a user needs to view the spectrogram of a certain frequency band through a spectrum display device, first select the spectrum display mode and frequency point information through the user interface of the spectrum display device, and send the user's selection to the server. Among them, the spectrum display mode includes whether to display static spectrum or dynamic spectrum.

[0135] The server sends the frequency point information selected by the user to the radar.

[0136] The radar collects spectrum data according to the frequency point information selected by the user through its antenna system and the like. The radar periodically sends the collected spectrum data to the server.

[0137] The server verifies the spectrum data sent by the radar to determine the integrity of the spectrum data. At the same time, it can also reduce the data processing burden of the spectrum display device to a certain extent.

[0138] The spectrum display device extracts and filters the spectrum data through the data stream module.

[0139] The processing module of the spectrum display device analyzes the filtered spectrum data to generate a spectrum matrix, and determines the intensity difference of each frequency point in the spectrum data according to the intensity value of each frequency point in the current frame and the intensity value of each frequency point in the previous frame; if the intensity difference is greater than the preset intensity threshold, a sparse matrix is generated according to the intensity difference and the frequency point information corresponding to the intensity difference, and the frequency points to be refreshed are generated according to the sparse matrix, and color information for the frequency point is generated through color mapping and the like, and sent to the user display interface.

[0140] The user display interface of the spectrum display device refreshes the spectrogram according to the frequency point information and color information to be refreshed. When there is data update, data is refreshed through interaction among the user interface, the processing module and the data stream module, so as to complete the display of spectrum information.

[0141] The embodiment of the present application also provides a computer-readable storage medium, in which executable instructions are stored. When the executable instructions run on the spectrum display device, the spectrum display device is enabled to perform the operations of the spectrum display method provided in any of the above embodiments.

[0142] The embodiment of the present application also provides a spectrum display program, and this spectrum display program is used to execute the spectrum display method provided in the above embodiment.

[0143] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. A variety of general-purpose systems can also be used in conjunction with the teachings provided herein. The structure required to construct such systems will be apparent from the above description. Additionally, the embodiments of the present application are not directed to any particular programming language. It should be understood that the content of the present application described herein can be implemented using a variety of programming languages, and the description of a particular language above is for the purpose of disclosing the best mode of the present application.

[0144] In the specification provided herein, numerous specific details are set forth. However, it can be understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0145] Similarly, it should be understood that, in order to streamline the present application and assist in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof.

[0146] Those skilled in the art will appreciate that the modules in the devices in the embodiments can be adaptively changed and arranged in one or more devices different from those of the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and can also be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all the features disclosed in this specification (including the accompanying abstract and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying abstract and drawings) can be replaced by an alternative feature that provides the same, equivalent, or similar purpose.

[0147] It should be noted that the above embodiments illustrate rather than limit the present application, and those skilled in the art can design alternative embodiments without departing from the scope. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A spectrum display method, characterized in that: include: Acquire frequency spectrum data of the signal to be detected, wherein the frequency spectrum data includes frequency point information and intensity values ​​of the frequency points; Determine the intensity difference of each frequency point in the spectrum data according to the intensity value of each frequency point in the current frame and the intensity value of each frequency point in the previous frame; If the intensity difference is greater than a preset intensity threshold, generating a sparse matrix according to the intensity difference and frequency point information corresponding to the intensity difference; The frequency spectrum information of the signal to be detected is displayed according to the sparse matrix.

2. The spectrum display method according to claim 1, characterized in that: The step of determining the intensity difference of each frequency point in the spectrum data according to the intensity value of each frequency point in the current frame and the intensity value of each frequency point in the previous frame further includes: Dividing the spectrum data of the signal to be detected into blocks; Determine the change value corresponding to each of the blocks according to the intensity value of each frequency point in each of the blocks; If the change value is greater than a preset change threshold, determining the block corresponding to the change value as a change block; The intensity difference of each frequency point is determined according to the intensity value of each frequency point in the change block of the current frame and the intensity value of each frequency point in the change block of the previous frame.

3. The spectrum display method according to claim 2, characterized in that: The determining the change value corresponding to each of the blocks according to the intensity value of each frequency point in each of the blocks includes: Determine the intensity mean value corresponding to each of the blocks according to the intensity value of each frequency point in each of the blocks; Determine the difference between the mean intensity value of each block corresponding to the current frame and the mean intensity value of each block corresponding to the previous frame.

4. The spectrum display method according to claim 2, characterized in that: The determining the change value corresponding to each of the blocks according to the intensity value of each frequency point in each of the blocks includes: Determine the maximum intensity value corresponding to each of the blocks according to the intensity value of each frequency point in each of the blocks; Determine the difference between the maximum intensity of each block corresponding to the current frame and the maximum intensity of each block corresponding to the previous frame.

5. The spectrum display method according to claim 1, characterized in that: The sparse matrix includes intensity differences, row index values ​​corresponding to the intensity differences, and column index values ​​corresponding to the intensity differences; or, The sparse matrix includes intensity differences, row index values ​​corresponding to the intensity differences, and column index pointers corresponding to the intensity differences.

6. The spectrum display method according to claim 5, characterized in that: The displaying of the frequency spectrum information of the signal to be detected according to the sparse matrix includes: The corresponding frequency points in the spectrum data are redrawn according to the frequency point information corresponding to the frequency points whose intensity differences in the sparse matrix are greater than zero.

7. The spectrum display method according to claim 6, characterized in that: The redrawing of the corresponding frequency points in the spectrum data according to the frequency point information corresponding to the frequency points whose intensity difference values ​​in the sparse matrix are greater than zero includes: The spectrum information corresponding to the frequency point is displayed according to the intensity difference corresponding to the frequency point in the sparse matrix and a preset color mapping table.

8. A spectrum display device, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least a program, and the program enables the processor to perform the operation of the spectrum display method according to any one of claims 1 to 7.

9. A spectrum display system, characterized in that: include: A frequency detection device and a spectrum display device as claimed in claim 8; The frequency detection device is used to obtain spectrum data of the signal to be detected, and send the spectrum data to the spectrum display device; The spectrum display device is used to display the spectrum according to the spectrum data.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one program, and when the program is executed on the spectrum display device, the spectrum display device performs the operation of the spectrum display method according to any one of claims 1 to 7.

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