Adaptive pan-star spectrum cognitive method

Abstract

The adaptive satellite spectrum cognitive method is used for carrying out fast Fourier operation on the sampling data of the satellite transponder, converting the time domain sampling data into frequency spectrum data, and sensing the spectrum situation of the transponder in the frequency domain. The spectrum data processing includes smoothing processing, reducing the burr noise in the spectrum data; according to the smoothed spectrum data, the edges of each transponder (each satellite usually contains multiple transponders) of the satellite are searched, so as to generate the frequency plan of the satellite transponder; according to the spectrum data, the hollow bandwidth in each transponder is searched, and finally the spectrum situation of the transponder of the whole satellite is formed.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, and is aimed at satellite transponder spectrum perception in satellite communication technology. Specifically, it refers to an adaptive pan-satellite spectrum perception method, and particularly relates to a pan-satellite spectrum perception method based on adaptive threshold adjustment. Background Technology

[0002] In satellite communications, transparent transpondering is a common communication mode for commercial geostationary satellites. This involves using transponders to convert and relay uplink and downlink signals. A transponder is a device on a satellite that receives signals transmitted from the ground, amplifies them, and then transmits them back to the ground at a different frequency. A satellite typically has multiple transponders. Satellite operators and transponder users need to monitor the spectrum status of the transponders to confirm whether they are functioning properly and whether the frequencies they use are being interfered with or illegally occupied.

[0003] In existing technologies, because spectrum situational awareness devices need to accurately reflect the level of received signals, the use of automatic gain control (AGC) modules should be avoided as much as possible during signal processing. Therefore, the amplitude of the sampled signal can change due to factors such as antenna aperture, amplifier gain, and weather conditions. For these reasons, using only one judgment threshold in the spectrum situational awareness process will undoubtedly have a significant impact on the accuracy of spectrum situational awareness. Summary of the Invention

[0004] This invention proposes a spectrum data processing method for satellite transponder spectrum situational awareness devices that can adaptively adjust the threshold. This method can adaptively adjust the situational awareness threshold under different sampling signal amplitude conditions, thereby improving the accuracy of spectrum situational awareness.

[0005] To achieve the above effects, this invention provides an adaptive pan-satellite spectrum awareness method for satellite transponder spectrum situation awareness devices. The method performs fast Fourier transform on the sampled data of the satellite transponder, converting the time-domain sampled data into spectrum data, and perceives the spectrum situation of the transponder in the frequency domain. The spectrum data is smoothed to reduce glitches and noise. Based on the smoothed spectrum data, the edges of each transponder of each satellite are searched to generate a frequency plan for the satellite transponder. Then, based on the spectrum data, hole bandwidth is searched within each transponder to finally form the transponder spectrum situation of the entire satellite.

[0006] Preferably, the above method specifically includes:

[0007] S1. Sample transponder data from multiple satellites, each of which contains multiple transponders;

[0008] S2. Perform a fast Fourier transform on the sampled data to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain;

[0009] S3. Smooth the spectrum data to reduce glitches and noise in the spectrum data;

[0010] S4. Perform a boundary search on the satellite transponder based on the smoothed spectrum data;

[0011] S5. Generate a frequency plan for the satellite transponders based on the boundary search results of each transponder.

[0012] S6. Based on the spectrum data, search for the hole bandwidth of each transponder according to the transponder frequency plan;

[0013] S7. Generate the transponder spectrum status of the entire satellite.

[0014] Preferably, the above-mentioned spectrum data processing performs FFT operations on the sampled data of the satellite transponder, for a total of 1000 operations; and performs cumulative mean smoothing on the results of the 1000 FFT operations.

[0015] Preferably, the above-mentioned boundary search for satellite transponders includes:

[0016] Step S101: Within the entire frequency band of the acquired signal, with a bandwidth resolution of 1MHz, search for the minimum energy value within the monitoring data frequency band starting from the starting frequency point, and determine the boundary point of the first transponder.

[0017] Step S102: Search for all minimum energy values ​​within a 1MHz bandwidth sequentially in the direction of increasing frequency, with certain frequency band intervals.

[0018] Step S103: Repeat step S102 in the direction of decreasing frequency to search for all minimum energy values ​​within a 1MHz bandwidth.

[0019] Step S104: Based on the collected spectrum data, determine the frequency of the boundary points of all transponders;

[0020] Step S105: Based on all boundary frequency points of the transponder, take the center point value, calculate the center frequency point of the transponder, and generate the transponder frequency plan.

[0021] Preferably, in step S102, all minimum energy values ​​within a 1MHz bandwidth are searched sequentially at frequency band intervals of 40MHz, 60MHz, and 80MHz.

[0022] Preferably, the satellite transponder hole search in step S6 specifically includes:

[0023] Step S201: In a transponder frequency band, with the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points, and the average value of these points is calculated and denoted as Pn.

[0024] Step S202: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find all frequency points less than Pn, and these frequency points are marked as hole frequency points.

[0025] Step S203: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find the 10 largest frequency points except for the hole frequency points, and the average value of these points is calculated and recorded as Pm.

[0026] Step S204: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points except for the hole frequency points, and the average value of these points is calculated and denoted as P1.

[0027] Step S205: Using the boundary point of the transponder as the reference f1, the bandwidth increases every 1MHz, and is successively denoted as f2, f3...fN. The forward search signal is performed, and the mean value of all frequency points except the hole frequency point is calculated and denoted as Pa.

[0028] Step S206: Calculate the decision threshold Pt for the satellite transponder's signal size. Frequency points greater than Pt are determined as large signals, and frequency points less than Pt are determined as small signals. ; Step S207: Repeat steps S201-S206 to search for holes in all transponders on the satellite and finally generate transponder spectrum situational awareness results.

[0029] This invention also provides an adaptive pan-satellite spectrum cognition method, applicable to multiple satellites, each satellite containing multiple transponders, the method comprising:

[0030] Step 1: Perform Fast Fourier Transform (FFT) operation on the sampled data of the satellite transponder to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain;

[0031] Step 2: Smooth the spectrum data to reduce glitches and noise.

[0032] Step 3: Based on the smoothed spectrum data, search for the edges of each transponder of the satellite to generate a frequency plan for the satellite transponders;

[0033] Step 4: Based on the spectrum data, search for hole bandwidths in each transponder of each satellite to ultimately form the transponder spectrum status of the entire satellite.

[0034] Preferably, the FFT operation in step one is performed a total of 1000 times; step two performs cumulative mean smoothing on the results of the 1000 FFT operations.

[0035] This invention also provides a system for implementing the above-described adaptive panstellar spectrum cognition method, comprising a sampling data processing module, a spectrum data smoothing module, a satellite transponder boundary search module, and a satellite transponder hole bandwidth search module, wherein,

[0036] The sampling data processing module performs Fast Fourier Transform (FFT) operations on the sampling data of the satellite transponder, converting the time-domain sampling data into spectrum data, and sensing the spectrum status of the transponder in the frequency domain;

[0037] The spectrum data smoothing module smooths the spectrum data, reducing glitches and noise in the spectrum data;

[0038] The satellite transponder boundary search module searches for the edges of each transponder on the satellite based on the smoothed spectrum data, thereby generating a frequency plan for the satellite transponders.

[0039] The satellite transponder hole bandwidth search module searches for hole bandwidth in each transponder of each satellite based on spectrum data, ultimately forming the transponder spectrum status of the entire satellite.

[0040] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0041] This invention proposes a spectrum data processing method with adaptive threshold adjustment for satellite transponder spectrum situational awareness devices. Since spectrum situational awareness devices need to accurately reflect the level of received signals, the use of automatic gain control (AGC) modules should be avoided as much as possible during signal processing. Therefore, the amplitude of the sampled signal can change due to factors such as antenna aperture, amplifier gain, and weather conditions. For these reasons, using only one judgment threshold during spectrum situational awareness will undoubtedly have a significant impact on the accuracy of spectrum situational awareness. Therefore, this invention proposes an adaptive threshold adjustment method that can adaptively adjust the situational judgment threshold under different sampled signal amplitude conditions, thereby improving the accuracy of spectrum situational awareness. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating the adaptive panstellar spectrum cognition method of the present invention is shown;

[0044] Figure 2 A schematic diagram of an embodiment of the adaptive panstellar spectrum cognition method of the present invention is shown;

[0045] Figure 3 A schematic diagram of an embodiment of the adaptive panstellar spectrum cognition method of the present invention is shown. Detailed Implementation

[0046] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only configured to explain the present invention and are not configured to limit the present invention. For those skilled in the art, the present invention can be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the invention.

[0047] It should be noted that in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0048] An embodiment of the adaptive pan-satellite spectrum awareness method proposed in this invention is used in a satellite transponder spectrum situation awareness device. It performs fast Fourier operation on the sampled data of the satellite transponder to convert the time-domain sampled data into spectrum data, perceives the spectrum situation of the transponder in the frequency domain, smooths the spectrum data to reduce glitches and noise in the spectrum data, and then searches for the edges of each transponder of each satellite based on the smoothed spectrum data to generate the frequency plan of the satellite transponder. Then, based on the spectrum data, it searches for hole bandwidth in each transponder to finally form the transponder spectrum situation of the entire satellite.

[0049] like Figure 1 As shown, an embodiment of the adaptive panstellar spectrum cognition method proposed in this invention specifically includes:

[0050] S1. Sample transponder data from multiple satellites, each of which contains multiple transponders;

[0051] S2. Perform a fast Fourier transform on the sampled data to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain;

[0052] S3. Smooth the spectrum data to reduce glitches and noise in the spectrum data;

[0053] S4. Perform a boundary search on the satellite transponder based on the smoothed spectrum data;

[0054] S5. Generate a frequency plan for the satellite transponders based on the boundary search results of each transponder.

[0055] S6. Based on the spectrum data, search for the hole bandwidth of each transponder according to the transponder frequency plan;

[0056] S7. Generate the transponder spectrum status of the entire satellite.

[0057] In some embodiments, the spectrum data processing performs FFT operations on the sampled data of the satellite transponder, for a total of 1000 operations; and performs cumulative mean smoothing on the results of the 1000 FFT operations.

[0058] In some embodiments, performing a boundary search on a satellite transponder includes:

[0059] Step S101: Within the entire frequency band of the acquired signal, with a bandwidth resolution of 1MHz, search for the minimum energy value within the monitoring data frequency band starting from the starting frequency point, and determine the boundary point of the first transponder.

[0060] Step S102: Search for all minimum energy values ​​within a 1MHz bandwidth sequentially in the direction of increasing frequency, with certain frequency band intervals.

[0061] Step S103: Repeat step S102 in the direction of decreasing frequency to search for all minimum energy values ​​within a 1MHz bandwidth.

[0062] Step S104: Based on the collected spectrum data, determine the frequency of the boundary points of all transponders;

[0063] Step S105: Based on all boundary frequency points of the transponder, take the center point value, calculate the center frequency point of the transponder, and generate the transponder frequency plan.

[0064] In some embodiments, step S102 searches for all minimum energy values ​​within a 1MHz bandwidth in sequence at frequency band intervals of 40MHz, 60MHz, and 80MHz.

[0065] In some embodiments, the satellite transponder hole search in step S6 specifically includes:

[0066] Step S201: In a transponder frequency band, with the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points, and the average value of these points is calculated and denoted as Pn.

[0067] Step S202: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find all frequency points less than Pn, and these frequency points are marked as hole frequency points.

[0068] Step S203: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find the 10 largest frequency points except for the hole frequency points, and the average value of these points is calculated and recorded as Pm.

[0069] Step S204: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points except for the hole frequency points, and the average value of these points is calculated and denoted as P1.

[0070] Step S205: Using the boundary point of the transponder as the reference f1, the bandwidth increases every 1MHz, and is successively denoted as f2, f3...fN. The forward search signal is performed, and the mean value of all frequency points except the hole frequency point is calculated and denoted as Pa.

[0071] Step S206: Calculate the decision threshold Pt for the satellite transponder's signal size. Frequency points greater than Pt are determined as large signals, and frequency points less than Pt are determined as small signals. ; Step S207: Repeat steps S201-S206 to search for holes in all transponders on the satellite and finally generate transponder spectrum situational awareness results.

[0072] like Figure 2 As shown, an embodiment of the adaptive panstellar spectrum cognition method proposed in this invention includes:

[0073] (1) Spectrum data processing

[0074] Step 1: Perform FFT operations on the sampled data from the satellite transponder, a total of 1000 operations;

[0075] Step 2: Perform cumulative mean smoothing on the results of 1000 FFT operations.

[0076] (2) Satellite transponder boundary search

[0077] Step 1: Within the entire frequency band of the acquired signal, with a bandwidth resolution of 1MHz, search for the minimum energy value within the monitoring data frequency band starting from the starting frequency point to determine the boundary point of the first transponder;

[0078] Step 2: Search for all minimum energy values ​​within a 1MHz bandwidth in the direction of increasing frequency, with frequency bands of 40MHz, 60MHz, and 80MHz respectively.

[0079] Step 3: Repeat step 2 in the direction of decreasing frequency, and search for all minimum energy values ​​within a 1MHz bandwidth in turn;

[0080] Step 4: Combine the collected spectrum data to comprehensively analyze and determine the frequency of the boundary points of all transponders;

[0081] Step 5: Based on all the boundary frequency points of the transponder, take the center point value, calculate the center frequency point of the transponder, and generate the transponder frequency plan.

[0082] (3) Satellite transponder hole search

[0083] Step 1: In a transponder frequency band, take the boundary point of the transponder as the reference f1, and increase the bandwidth by 1MHz, and denot it as f2, f3...fN in sequence. Search for the signal in the forward direction, find the 10 smallest frequency points, and calculate the average value of these points, denoted as Pn.

[0084] Step 2: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find all frequency points less than Pn, and these frequency points are marked as hole frequency points.

[0085] Step 3: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 largest frequency points except for the hole frequency points, and the average value of these points is calculated and denoted as Pm.

[0086] Step 4: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points except for the hole frequency points, and the average value of these points is calculated and denoted as Pl.

[0087] Step 5: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The forward search signal is used to calculate the mean of all frequency points except the hole frequency point, denoted as Pa.

[0088] Step 6: Calculate the decision threshold Pt for the satellite transponder's signal size. Frequency points greater than Pt are determined as large signals, and frequency points less than Pt are determined as small signals. ; Step 7: Repeat steps 1-6 to search for holes in all transponders on the satellite and finally generate transponder spectrum situational awareness results.

[0089] like Figure 3 As shown, an embodiment of the adaptive pan-satellite spectrum cognition method proposed in this invention is applicable to multiple satellites, each satellite containing multiple transponders, including:

[0090] Step 1: Perform Fast Fourier Transform (FFT) operation on the sampled data of the satellite transponder to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain;

[0091] Step 2: Smooth the spectrum data to reduce glitches and noise.

[0092] Step 3: Based on the smoothed spectrum data, search for the edges of each transponder of the satellite to generate a frequency plan for the satellite transponders;

[0093] Step 4: Based on the spectrum data, search for hole bandwidths in each transponder of each satellite to ultimately form the transponder spectrum status of the entire satellite.

[0094] In some embodiments, step one involves FFT calculation, which is performed a total of 1000 times; step two involves performing cumulative mean smoothing on the results of the 1000 FFT calculations.

[0095] This invention also provides a system embodiment for implementing an adaptive panstellar spectrum cognition method, including a sampling data processing module, a spectrum data smoothing module, a satellite transponder boundary search module, and a satellite transponder hole bandwidth search module, wherein,

[0096] The sampling data processing module performs Fast Fourier Transform (FFT) operations on the sampling data of the satellite transponder, converting the time-domain sampling data into spectrum data, and sensing the spectrum status of the transponder in the frequency domain;

[0097] The spectrum data smoothing module smooths the spectrum data, reducing glitches and noise in the spectrum data;

[0098] The satellite transponder boundary search module searches for the edges of each transponder on the satellite based on the smoothed spectrum data, thereby generating a frequency plan for the satellite transponders.

[0099] The satellite transponder hole bandwidth search module searches for hole bandwidth in each transponder of each satellite based on spectrum data, ultimately forming the transponder spectrum status of the entire satellite.

[0100] The present invention also provides an embodiment of a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0101] This invention proposes a spectrum data processing method with adaptive threshold adjustment for satellite transponder spectrum situational awareness devices. Since spectrum situational awareness devices need to accurately reflect the level of received signals, the use of automatic gain control (AGC) modules should be avoided as much as possible during signal processing. Therefore, the amplitude of the sampled signal can change due to factors such as antenna aperture, amplifier gain, and weather conditions. For these reasons, using only one judgment threshold during spectrum situational awareness will undoubtedly have a significant impact on the accuracy of spectrum situational awareness. Therefore, this invention proposes an adaptive threshold adjustment method that can adaptively adjust the situational judgment threshold under different sampled signal amplitude conditions, thereby improving the accuracy of spectrum situational awareness.

[0102] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0103] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0104] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. An adaptive pan-satellite spectrum cognition method for use in satellite transponder spectrum situational awareness equipment, characterized in that... The method performs a fast Fourier operation on the sampled data of the satellite transponders, converting the time-domain sampled data into spectrum data. It then senses the spectrum status of the transponders in the frequency domain, smooths the spectrum data to reduce glitches and noise, and searches for the edges of each transponder for each satellite based on the smoothed spectrum data to generate a frequency plan for the satellite transponders. Finally, it searches for hole bandwidths within each transponder based on the spectrum data to form the spectrum status of the transponders for the entire satellite.

2. The adaptive panstellar spectrum cognition method according to claim 1, characterized in that... The method specifically includes: S1. Sample transponder data from multiple satellites, each of which contains multiple transponders; S2. Perform a fast Fourier transform on the sampled data to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain; S3. Smooth the spectrum data to reduce glitches and noise in the spectrum data; S4. Perform a boundary search on the satellite transponder based on the smoothed spectrum data; S5. Generate a frequency plan for the satellite transponders based on the boundary search results of each transponder. S6. Based on the spectrum data, search for the hole bandwidth of each transponder according to the transponder frequency plan; S7. Generate the transponder spectrum status of the entire satellite.

3. The adaptive panstellar spectrum cognition method according to claim 2, characterized in that... The spectrum data processing performs FFT operations on the sampled data from the satellite transponder, a total of 1000 operations; and performs cumulative mean smoothing on the results of the 1000 FFT operations.

4. The adaptive panstellar spectrum cognition method according to claim 2, characterized in that, The boundary search for the satellite transponder includes: Step S101: Within the entire frequency band of the acquired signal, with a bandwidth resolution of 1MHz, search for the minimum energy value within the monitoring data frequency band starting from the starting frequency point, and determine the boundary point of the first transponder. Step S102: Search for all minimum energy values ​​within a 1MHz bandwidth sequentially in the direction of increasing frequency, with certain frequency band intervals. Step S103: Repeat step S102 in the direction of decreasing frequency to search for all minimum energy values ​​within a 1MHz bandwidth. Step S104: Based on the collected spectrum data, determine the frequency of the boundary points of all transponders; Step S105: Based on all boundary frequency points of the transponder, take the center point value, calculate the center frequency point of the transponder, and generate the transponder frequency plan.

5. The adaptive panstellar spectrum cognition method according to claim 4, characterized in that... In step S102, the minimum energy values ​​within a 1MHz bandwidth are searched sequentially at frequency intervals of 40MHz, 60MHz, and 80MHz.

6. The adaptive panstellar spectrum cognition method according to claim 2, characterized in that... The satellite transponder hole search in step S6 specifically includes: Step S201: In a transponder frequency band, with the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points, and the average value of these points is calculated and denoted as Pn. Step S202: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find all frequency points less than Pn, and these frequency points are marked as hole frequency points. Step S203: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively recorded as f2, f3...fN. The signal is searched in the forward direction to find the 10 largest frequency points except for the hole frequency points, and the average value of these points is calculated and recorded as Pm. Step S204: Using the boundary point of the transponder as the reference f1, the bandwidth increases by 1MHz, and is successively denoted as f2, f3...fN. The signal is searched in the forward direction to find the 10 smallest frequency points except for the hole frequency points, and the average value of these points is calculated and denoted as P1. Step S205: Using the boundary point of the transponder as the reference f1, the bandwidth increases every 1MHz, and is successively denoted as f2, f3...fN. The forward search signal is performed, and the mean value of all frequency points except the hole frequency point is calculated and denoted as Pa. Step S206: Calculate the decision threshold Pt for the satellite transponder's signal size. Frequency points greater than Pt are determined as large signals, and frequency points less than Pt are determined as small signals. ； Step S207: Repeat steps S201-S206 to search for holes in all transponders on the satellite and finally generate transponder spectrum situational awareness results.

7. An adaptive pan-satellite spectrum cognition method, applicable to multiple satellites, each satellite containing multiple transponders, characterized in that... The method includes: Step 1: Perform Fast Fourier Transform (FFT) operation on the sampled data of the satellite transponder to convert the time-domain sampled data into spectrum data, and perceive the spectrum status of the transponder in the frequency domain; Step 2: Smooth the spectrum data to reduce glitches and noise. Step 3: Based on the smoothed spectrum data, search for the edges of each transponder of the satellite to generate a frequency plan for the satellite transponders; Step 4: Based on the spectrum data, search for hole bandwidths in each transponder of each satellite to ultimately form the transponder spectrum status of the entire satellite.

8. The adaptive panstellar spectrum cognition method according to claim 7, characterized in that, The first step, FFT operation, is performed a total of 1000 times; the second step is to perform cumulative mean smoothing on the results of the 1000 FFT operations.

9. A system for implementing the adaptive panstellar spectrum cognition method according to any one of claims 1-8, comprising a sampling data processing module, a spectrum data smoothing module, a satellite transponder boundary search module, and a satellite transponder hole bandwidth search module, characterized in that: The sampling data processing module performs Fast Fourier Transform (FFT) operations on the sampling data of the satellite transponder, converting the time-domain sampling data into spectrum data, and sensing the spectrum status of the transponder in the frequency domain; The spectrum data smoothing module smooths the spectrum data, reducing glitches and noise in the spectrum data; The satellite transponder boundary search module searches for the edges of each transponder on the satellite based on the smoothed spectrum data, thereby generating a frequency plan for the satellite transponders. The satellite transponder hole bandwidth search module searches for hole bandwidth in each transponder of each satellite based on spectrum data, ultimately forming the transponder spectrum status of the entire satellite.

10. A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the method of any one of claims 1-8.

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