Satellite communication power adaptive regulation method, system and device

Abstract

The application provides a satellite communication power adaptive regulation method, system and device, which divides the space where satellite communication belongs into multiple space grid areas according to a preset space division scale; acquires satellite sensing data, space weather data and near-earth weather data in each space grid area to determine communication link loss evaluation data corresponding to each space grid area; generates space interference summary information according to the loss evaluation data corresponding to each space grid area and location data thereof; and adjusts the transmission power of satellite communication in each space grid area according to the space interference summary information. The method and system of the application collect weather data in the space area and the near-earth area thereof to determine loss evaluation data, and realize dynamic adaptive adjustment of satellite transmission power in each space grid area based on the loss evaluation data, thereby improving the reliability of satellite communication in a complex space environment.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to an adaptive control method, system and device for satellite communication power. Background Technology

[0002] In satellite communication links, communication signals need to traverse hundreds or even tens of thousands of kilometers of space, thus facing technical challenges such as long latency, channel time-varying characteristics, and rain attenuation interference. When in abnormal space weather conditions such as particle storms, ionospheric anomalies, and atmospheric density anomalies, satellite communication links may be subject to significant interference, thereby seriously threatening their stability.

[0003] Existing communication technologies typically employ a fixed link budget model, using a closed-loop power control mechanism to compensate for power loss during signal transmission. However, this traditional method has significant limitations in dynamic interference environments: on the one hand, the feedback delay characteristic of closed-loop control leads to a lag in power compensation response, making it impossible to match rapidly changing channel conditions in real time; on the other hand, its fixed parameter design struggles to adapt to the variable propagation path loss in inter-orbit communication and the differentiated interference characteristics under different application scenarios. Therefore, existing power control methods cannot achieve adaptive dynamic adjustment of satellite transmission power.

[0004] Therefore, the existing technology needs further improvement. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an adaptive control method, system and device for satellite communication power, overcoming the defect that the prior art cannot adaptively and dynamically control satellite communication power.

[0006] The technical solution adopted by this invention to solve the technical problem is as follows:

[0007] In a first aspect, the present invention provides an adaptive control method for satellite communication power, comprising:

[0008] According to the preset spatial division scale, the space to which satellite communication belongs is divided into multiple spatial grid regions;

[0009] The satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area are acquired, and the loss assessment data corresponding to each spatial grid area is determined based on the satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area.

[0010] Based on the loss assessment data and location data corresponding to each of the spatial grid regions, spatial interference summary information is generated;

[0011] Based on the aggregated spatial interference information, the transmission power of satellite communication within each spatial grid area is adjusted.

[0012] Optionally, the step of dividing the space to which satellite communication belongs into multiple spatial regions according to a preset spatial division scale includes:

[0013] A three-dimensional Cartesian coordinate system is established with the Earth's center as the origin, and a cubic region of a preset volume is set as a spatial grid region. The space to which satellite communication belongs is divided into multiple spatial grid regions. Each of the spatial grid regions corresponds to a different region code, and the region code of each spatial grid region is constructed into a spatial region code sequence based on the positional relationship between the spatial grid regions.

[0014] Optionally, the step of acquiring satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area includes:

[0015] Satellite sensors onboard in each spatial grid region are used to acquire satellite sensing data in each spatial grid region; wherein, the satellite sensing data includes: sensing ionization index, sensing ion index and sensing atmospheric density, etc.

[0016] Acquire ground ionospheric monitoring data and meteorological radar monitoring data within each spatial grid area, and determine the spatial weather data for each spatial grid area based on the ionization index, ion index, cloud thickness, and rainfall in the ground ionospheric monitoring data and meteorological radar monitoring data;

[0017] The regional location of each spatial grid region on Earth is determined by using the regional code corresponding to each spatial grid region, and the near-Earth weather data of each spatial grid region is determined based on the weather data of the corresponding regional location on Earth.

[0018] Optionally, the step of determining the loss assessment data corresponding to each of the spatial grid areas based on satellite sensing data, space weather data, and near-Earth weather data within each of the spatial grid areas includes:

[0019] According to the preset weighting coefficients, the satellite sensing data, space weather data and near-Earth weather data in each of the spatial grid areas are weighted and fused to obtain the multi-source monitoring data corresponding to each of the spatial grid areas after fusion.

[0020] The multi-source monitoring data of each spatial grid region is normalized, and the normalized multi-source monitoring data is input into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model.

[0021] Optionally, the preset dynamic link loss model includes: a free space loss calculation unit, a space weather loss calculation unit, a near-ground weather loss unit beam, and a summary calculation unit;

[0022] The step of inputting the normalized multi-source monitoring data into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model includes:

[0023] The free space loss calculation unit calculates the free space loss value based on the link distance corresponding to each of the spatial grid regions;

[0024] The space weather loss calculation unit calculates the space weather loss value based on multiple space weather influencing factors and the weight of each space weather influencing factor; wherein, the space weather influencing factors are calculated based on space weather data from multi-source monitoring data;

[0025] The near-ground weather loss unit calculates the near-ground weather loss value based on the parameters and rain attenuation coefficients corresponding to different frequency bands in the near-ground weather data from the multi-source monitoring data.

[0026] The aggregation calculation unit combines the free space loss value, space weather loss value, and near-ground weather loss value to obtain loss assessment data for each of the space grid regions.

[0027] Optionally, if the satellites in the space grid area are LEO satellites, the preset dynamic link loss model further includes a beam pointing deviation loss calculation unit;

[0028] The step of inputting the normalized multi-source monitoring data into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model further includes:

[0029] The beam pointing deviation loss is calculated based on one or more of the satellite pose data, cloud cover, or rainfall data from the multi-source monitoring data.

[0030] Optionally, the spatial interference summary information is a spatial interference heatmap; the step of generating the spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions includes:

[0031] Satellites within each of the aforementioned spatial grid areas transmit their corresponding loss assessment data and location data to the ground control center;

[0032] The ground control center will summarize the loss assessment data corresponding to each of the space grid regions into a space interference heat map.

[0033] Optionally, the step of adjusting the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information includes:

[0034] The ground control center will send the space interference heat map to all on-orbit satellites and / or ground terminals within the space to which the satellite communication belongs;

[0035] At least some of the on-orbit satellites and / or ground terminals within the space to which satellite communication pertains adjust the transmission power of satellites within the corresponding space grid area based on the received space interference heatmap.

[0036] Optionally, the step of adjusting the transmission power of satellites within the corresponding space grid area according to the received space interference heatmap, involving at least some of the on-orbit satellites and / or ground terminals in the space to which the satellite communication pertains, includes:

[0037] Based on the loss assessment data corresponding to each spatial grid region, determine the rate of change of the interference coefficient corresponding to each spatial grid region;

[0038] Based on the satellite orbit type within each space grid region, determine the corresponding power control range for each space grid region;

[0039] Based on the service scenarios of the satellites within each spatial grid area, determine the target SINR value corresponding to each spatial grid area;

[0040] Based on the determined rate of change of interference coefficient, power control range, and target SINR, the transmit power of satellites in each space grid area is determined.

[0041] Optionally, after the step of adjusting the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information, the method further includes:

[0042] The SINR value of the communication link between the satellite and the control terminal in each space grid area is obtained, and the SINR value is fed back to the ground control center, the ground terminal, or the satellite in each space grid area.

[0043] The ground control center, ground terminal, or satellites within each spatial grid area adjust the interference coefficient change rate, power control range, and target SINR based on the SINR value of the communication link between the satellite and the control terminal, and use the adjusted interference coefficient change rate, power control range, and target SINR to determine the transmission power of the satellites within each spatial grid area.

[0044] Optionally, after adjusting the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information, the method further includes:

[0045] Real-time acquisition of spatial weather status data within each spatial grid area, and determination of whether there are any spatial weather anomalies within one or more spatial grid areas based on the spatial weather status data;

[0046] If there are abnormal space weather conditions, the interference coefficient change rate, power control range, and target SINR of the satellite transmission power in each space grid area where abnormal space weather conditions exist shall be adjusted according to the space weather status data.

[0047] Furthermore, based on the positional relationship between satellites within each spatial grid area and the space weather state data, with the satellite's motion direction as the position sequence direction, predict the space weather state data for adjacent spatial grid areas in the position sequence, and adjust the interference coefficient change rate, power control range, and target SINR of the satellite transmit power in the adjacent spatial grid areas based on the space weather state prediction data.

[0048] Optionally, the step of adjusting the rate of change of the interference coefficient, the power control range, and the target SINR of the satellite transmit power in each space grid region where space weather anomalies exist, based on the space weather state data, includes:

[0049] Space weather state data is input into a preset coefficient prediction model to obtain the rate of change of the interference coefficient, the power control range, and the target SINR output by the preset coefficient prediction model; wherein, the preset coefficient prediction model is obtained by training a preset network model based on space weather state sample data and power parameters corresponding to the space weather state sample data.

[0050] Secondly, the present invention provides an adaptive control system for satellite communication power, comprising:

[0051] The region division module is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale;

[0052] The loss assessment module is used to acquire satellite sensing data, space weather data and near-Earth weather data in each spatial grid area, and determine the loss assessment data corresponding to each spatial grid area based on the satellite sensing data, space weather data and near-Earth weather data in each spatial grid area.

[0053] The interference aggregation module is used to generate spatial interference aggregation information based on the loss assessment data and location data corresponding to each of the spatial grid regions;

[0054] The power adjustment module is used to adjust the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information.

[0055] Thirdly, this application also discloses an adaptive control device for satellite communication power, which includes: multiple satellites, a ground terminal communicating with one or more satellites, and a ground control center communicating with each satellite;

[0056] The ground control center is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale;

[0057] Satellites located within each of the aforementioned spatial grid areas are used to acquire satellite sensing data, space weather data, and near-Earth weather data within their respective spatial grid areas. Based on the satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas, satellites determine the loss assessment data corresponding to each of the aforementioned spatial grid areas and transmit the loss assessment data to satellites in other spatial grid areas and the ground control center.

[0058] The ground control center is also used to generate spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions, and to transmit the spatial interference summary information to each of the satellites and the ground terminal;

[0059] Each of the satellites and the ground terminal is used to adjust the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information.

[0060] Optionally, each satellite is equipped with multiple onboard sensors, which are used to acquire satellite sensing data within their respective space grid areas; wherein, the satellite sensing data includes: sensing ionization index, sensing ion index, and sensing atmospheric density;

[0061] Each satellite is also connected to a ground-based auxiliary monitoring network and a satellite ground station;

[0062] Each satellite acquires space weather data by accessing the aforementioned ground-aided monitoring network, and acquires near-Earth weather data by accessing satellite ground stations.

[0063] Beneficial effects:

[0064] This invention provides an adaptive adjustment method, system, and apparatus for satellite communication power. The method divides the space in which satellite communication is located into multiple spatial grid regions according to a preset spatial division scale. Satellite sensing data, space weather data, and near-Earth weather data are acquired for each spatial grid region. Based on these data, loss assessment data is determined for each spatial grid region. Spatial interference summary information is generated based on the loss assessment data and location data for each spatial grid region. The transmission power of satellite communication within each spatial grid region is adjusted according to the spatial interference summary information. This method and system improve the reliability of satellite communication in complex space environments by collecting weather data from both the space region and the near-Earth region to determine loss assessment data and dynamically and adaptively adjusting the satellite transmission power within each spatial grid region based on this loss assessment data. Attached Figure Description

[0065] Figure 1 This is a schematic diagram illustrating the principle of beam pointing deviation loss in satellite communication power in existing technologies.

[0066] Figure 2 A flowchart illustrating the steps of the adaptive control method for satellite communication power provided by the present invention;

[0067] Figure 3 This is a schematic diagram of the structure corresponding to each spatial grid region in the embodiments provided by the present invention;

[0068] Figure 4 A schematic diagram illustrating the position encoding rules of each spatial grid region in the method of the embodiments provided by the present invention;

[0069] Figure 5 A graph showing the loss values ​​corresponding to different interference factors in the method of the embodiments provided by the present invention;

[0070] Figure 6 A schematic diagram illustrating the principle of satellite-to-ground / inter-satellite cooperative control in the embodiment method provided by the present invention;

[0071] Figure 7 A flowchart illustrating the steps of an embodiment of the adaptive control of satellite communication power in the method provided by the present invention;

[0072] Figure 8 The structural principle block diagram of the adaptive control system for satellite communication power provided by the present invention. Detailed Implementation

[0073] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0074] It should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown in the flowchart. The terms "first," "second," etc., used in the specification, claims, and the foregoing drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to limit the invention.

[0075] As the core support for seamless global communication, satellite communication signals need to travel through space links of hundreds to tens of thousands of kilometers. It inherently faces technical challenges such as long latency, channel time-varying, and rain attenuation interference. The occurrence of space weather anomalies such as particle storms, ionospheric anomalies, and atmospheric density anomalies further poses a severe threat to the stability of communication links, becoming a key bottleneck restricting the quality of satellite communication.

[0076] From the perspective of specific interference mechanisms, high-energy protons and electrons in particle storms directly collide with satellite electronic equipment, triggering single event upsets (SEUs). This causes a surge in the bit error rate of TPC (Transmit Power Control) signaling transmission. Simultaneously, the plasma generated by the ionization of satellite materials by particles alters the antenna impedance matching, increasing signal reflection loss and causing a sharp drop in the receiver's SINR (Signal to Interference plus Noise Ratio). In extreme cases, this can even lead to sudden signal loss of more than 20 dB. Ionospheric anomalies, through abrupt changes in the total electron content (TEC) (with a rate of change exceeding 1 TECU / min), cause signal refraction and time delay spread, superimposed with strong scintillation interference (S4 exponent > 0.2), resulting in a significant increase in BER (Bit Error Rate) and BLER (Block Error Rate). This triggers the "ping-pong effect" of traditional closed-loop power control—frequent ineffective power adjustments that actually exacerbate link instability. Atmospheric density anomalies have a particularly pronounced impact on low-Earth orbit satellites. Fluctuations in atmospheric density at their orbital altitude (500-2000 km) can cause satellite attitude shifts exceeding 0.5°, leading to beam pointing deviations. Figure 1As shown, this causes a burst path loss of 10-15dB, while also affecting the satellite's heat dissipation efficiency, resulting in a power amplifier efficiency drop of over 10%, further weakening the signal transmission capability.

[0077] These space weather anomalies not only disrupt link budget balance but also pose serious challenges to existing technological solutions. Current closed-loop power control schemes in the satellite communication field revolve around a post-event response logic of "signal quality feedback - power adjustment," primarily encompassing the following two technical paths:

[0078] The first type is power control based on fixed link budget: a static link budget model is constructed by pre-setting link loss parameters (such as free space loss, atmospheric attenuation, antenna gain, etc.). The terminal and satellite initially configure the transmission power based on the model, and then the power is fine-tuned by measuring signal quality indicators such as SINR and BER at the receiver.

[0079] The second category is closed-loop power control based on signal quality feedback: This is currently the mainstream solution, specifically including: Fixed step size control: GEO satellites typically use a ±1dB adjustment step size, controlling the frequency 10-50Hz; LEO satellites use a ±1-2dB step size, controlling the frequency 100-500Hz, achieving iterative power adjustment through TPC signaling. Adaptive step size control: The step size is dynamically adjusted based on the rate of change of SINR / BER, but the adjustment logic still relies on real-time feedback of signal quality and does not relate to the essential characteristics of the interference source. Satellite-to-ground single-end control: The satellite side and the terminal side independently adjust the power; the satellite side adjusts the transmit power based on downlink quality, and the terminal side adjusts its own transmit power based on uplink reception quality, lacking a coordination mechanism.

[0080] Therefore, it can be concluded that the power control schemes in the existing technology have failed to effectively cope with the dynamic interference caused by space weather anomalies, and the core defects are reflected in the following four aspects:

[0081] Firstly, the link budget model is static and cannot adapt to dynamic interference. Traditional solutions rely on fixed or slowly updated link budget models, which only consider conventional losses such as rain attenuation and do not incorporate space weather monitoring data. This makes it impossible to correct sudden loss parameters such as particle storms and ionospheric anomalies in real time, resulting in excessive deviations in the initial power configuration and a surge in pressure for subsequent closed-loop adjustments.

[0082] Secondly, power control relies on post-event feedback, resulting in significant response lag. Existing closed-loop power control systems all use signal quality indicators such as SINR and BER as the core feedback basis, which is a post-event control mode of "interference occurrence - quality degradation - response adjustment". However, signal loss caused by space weather anomalies is often sudden and large (10-20dB). The combination of fixed step size and control frequency cannot quickly compensate for sudden losses, which can easily cause the link quality to drop below the threshold.

[0083] Thirdly, there is a lack of space environment perception capabilities and insufficient adjustment accuracy. The existing scheme has not established a space weather perception mechanism, and cannot distinguish whether the root cause of the signal quality degradation is space weather interference, rain attenuation, or Doppler frequency shift. This causes SINR measurements to be affected by interference jitter, and the adjustment direction or amplitude of TPC commands is prone to deviation, and may even trigger the "ping-pong effect", further aggravating link instability.

[0084] Fourthly, there is a lack of space-ground coordination and insufficient adaptability. The satellite and terminal sides lack a coordinated control mechanism, preventing the terminal from obtaining early warning information about the space environment from the satellite. Furthermore, the satellite does not coordinate with the terminal's power adjustment strategy, resulting in delayed power compensation. This is particularly problematic in LEO (Geostationary Earth Orbit) satellite scenarios, where high-speed satellite movement (orbital speed approximately 7.8 km / s) leads to frequent beam switching. Traditional power detection and control methods are prone to link establishment failures or excessively long establishment times, making them unsuitable for the needs of various scenarios such as mobile communication and high-throughput satellites.

[0085] To address the shortcomings of existing technologies, such as the lack of space environment awareness and insufficient adjustment precision, this invention proposes an adaptive control method, system, and device for satellite communication power. By constructing a spaceborne sensing network covering interstellar and near-Earth space, it collects real-time weather and environmental data from the satellite's location within its spatial grid area and the near-Earth space region. Based on this weather and environmental data, it generates space interference parameter information for the entire network and uses this information to adaptively control the transmission power of each satellite. The method disclosed in this invention can dynamically and collaboratively optimize the power adjustment step size, control frequency, and target SINR, achieving a proactive control mechanism of "pre-prediction and precise pre-adjustment." This accurately compensates for sudden signal loss and improves communication reliability in complex space environments.

[0086] The adaptive control method, system, and apparatus for satellite communication power disclosed in this embodiment will be described in further detail below with reference to the accompanying drawings.

[0087] This invention provides an adaptive control method for satellite communication power, such as... Figure 2 As shown, it includes:

[0088] Step S1: Divide the space to which the satellite communication belongs into multiple spatial grid regions according to the preset spatial division scale.

[0089] In order to control the satellite's transmission power, this step first divides the space where the satellite is located and the near-Earth space into grids, and then senses the weather information and corresponding near-Earth weather information in each grid area, so as to achieve a more accurate estimation of interference loss.

[0090] Specifically, the step of dividing the space to which satellite communication belongs into multiple spatial regions according to a preset spatial division scale includes:

[0091] A three-dimensional Cartesian coordinate system is established with the Earth's center as the origin, and a cubic region of a preset volume is set as a spatial grid region. The space to which satellite communication belongs is divided into multiple spatial grid regions. Each of the spatial grid regions corresponds to a different region code, and the region code of each spatial grid region is constructed into a spatial region code sequence based on the positional relationship between the spatial grid regions.

[0092] The spatial coordinate system established in this step is a three-dimensional Cartesian coordinate system, with its center at the Earth's center. The X-axis points to the intersection of the Prime Meridian and the equator, the Z-axis points to the North Pole, and the Y-axis points to 90° East longitude, forming a right-handed coordinate system with the X and Z axes. The auxiliary reference of the coordinate system is the Earth's surface, and the length of its coordinate axes extends to the space where the satellite is located. Based on a preset spatial division scale, the space to which the satellite communication belongs is divided into multiple spatial regions.

[0093] In specific implementation methods, the ITU-recommended grid of 25 kilometers per cubic meter can be used, such as... Figure 3 As shown, the side lengths of the cube can also be customized or adjusted according to needs, so that each grid corresponds to a satellite communication area, thereby dividing the entire area where satellite communication is located into multiple spatial grid regions. It is conceivable that for low-precision scenarios, such as data services in remote areas, the grid unit can be adjusted to 50km³ to reduce the pressure on satellite data processing; for high-precision scenarios, such as mobile airborne communication, it can be adjusted to 10km³ to improve positioning accuracy.

[0094] To pinpoint the location of each spatial grid region, this step sequentially encodes each region according to their positional relationships. Therefore, each spatial grid region corresponds to a fixed region code, facilitating the acquisition of relevant environmental information for each region. Furthermore, based on the radial information from the location of each spatial grid region to the ground, near-Earth weather information can be obtained. Environmental and weather information includes space environment factors such as ionization index, particle storm index, and atmospheric density, as well as information that may interfere with satellite communications, such as cloud thickness and rainfall.

[0095] Combination Figure 4As shown, the rules for position coding of each spatial grid region are as follows: a three-dimensional Cartesian coordinate system is established with the Earth's center as the origin, covering near-Earth space (0-35786km, including the entire GEO (Geosynchronous Earth Orbit) / LEO / MEO (Medium Earth Orbit) orbits), and the ITU-recommended 25km³ is used as the standard grid unit (which can be adjusted to 10km³ or 50km³ according to accuracy requirements).

[0096] Reference scheme: Encoding format: Each cell is assigned a unique 32-bit binary code. The high 4 bits represent the orbital altitude range (0000=LEO, 0001=MEO, 0010=GEO), the middle 16 bits represent the latitude and longitude range (divided into 0.5°×0.5°), and the low 4 bits represent the radial distance range (relative to the Earth's surface), realizing the precise binding of "spatial location-environmental data-communication link".

[0097] This step is based on location coding of each spatial grid area, thereby solving the problem of traditional environmental data "lacking spatial location and unable to be matched with links", so that interference loss assessment can be accurately mapped to the spatial area where each communication link is located, with a quantization error ≤0.5dB.

[0098] Step S2: Obtain satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area, and determine the loss assessment data corresponding to each spatial grid area based on the satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area.

[0099] After dividing the entire space area of ​​satellite communication into multiple spatial grid areas, satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area are acquired to estimate interference loss.

[0100] Specifically, satellite sensing data refers to the sensing data collected by the space sensing sensors carried on each satellite. These sensors include high-energy particle detectors for monitoring proton or electron flux, ionospheric detectors for measuring TEC and S4 indices, and atmospheric density sensors based on mass spectrometers or rum probes. These space sensing sensors can perceive real-time information about the space surrounding the satellite, such as ionization, ion indices, and atmospheric density, thereby obtaining satellite sensing data. When the satellite is a small, low-Earth orbit satellite, a sensor configuration can be adopted, retaining only the atmospheric density sensor and ionospheric detector, and supplementing particle storm data through inter-satellite data sharing, balancing cost with the accuracy and real-time performance of the monitoring data.

[0101] Space weather data refers to weather data within each space grid region. In practice, each satellite establishes a connection with a ground-based auxiliary monitoring network. By accessing ground-based ionospheric monitoring stations, it obtains data such as the total electron content of the ionosphere, the ionospheric disturbance index, and signal delay monitored by the stations. It also acquires cloud thickness, rainfall, precipitation type (rain / snow / dust), and wind field within the corresponding space grid region through meteorological radar. All of this data is used as space weather data.

[0102] The acquisition of near-ground weather data is based on the near-ground weather data interface, which obtains real-time rain attenuation and cloud distribution data from global meteorological organizations through satellite ground stations, in order to adapt to Ka / Ku band link loss calculation.

[0103] Specifically, the steps of acquiring satellite sensing data, space weather data, and near-Earth weather data within each spatial grid area include:

[0104] Step S21: Use the onboard satellite sensors in each spatial grid area to acquire satellite sensing data in each spatial grid area; wherein, the satellite sensing data includes: sensing ionization index, sensing ion index and sensing atmospheric density.

[0105] In this step, since the onboard sensor cluster moves with the satellite, it can sense the space weather data of the area where the satellite is located at any time. Therefore, it can solve the defects of incomplete coverage and long time delay in traditional ground monitoring, so as to reduce the acquisition latency of space weather data to less than 10ms, which is 90% lower than the latency of existing ground monitoring schemes.

[0106] Step S22: Obtain ground ionospheric monitoring data and meteorological radar monitoring data in each spatial grid area, and determine the spatial weather data of each spatial grid area based on the ionization index, ion index, cloud thickness and rainfall in the ground ionospheric monitoring data and meteorological radar monitoring data.

[0107] Step S23: Determine the regional location of each spatial grid region on Earth using the regional code corresponding to each spatial grid region, and determine the near-Earth weather data of each spatial grid region based on the weather data of the regional location of each spatial grid region on Earth.

[0108] This step involves collecting multi-source monitoring data related to satellite communication interference factors within each spatial grid area. This avoids sensing interruptions caused by the failure of a single data source, improving data reliability. Furthermore, during the collection of the aforementioned multi-source monitoring data, different sampling frequencies can be adapted according to different satellite orbit types to balance data acquisition accuracy and satellite power consumption. In one implementation, high-frequency sampling is used for LEO satellites moving at high speeds, while low-frequency sampling is used for GEO satellites that are stable.

[0109] Furthermore, the step of determining the loss assessment data corresponding to each of the spatial grid areas based on satellite sensing data, space weather data, and near-Earth weather data within each of the spatial grid areas includes:

[0110] Step S24: According to the preset weighting coefficient, the satellite sensing data, space weather data and near-Earth weather data in each of the spatial grid areas are weighted and fused to obtain the multi-source monitoring data corresponding to each of the spatial grid areas after fusion.

[0111] After obtaining multi-source data from different monitoring methods in each spatial grid area in step S23, the multi-source data is weighted and adaptively fused to obtain fused multi-source monitoring data.

[0112] Because satellite sensing data has strong real-time characteristics and causes the most interference to satellite power, it has the highest priority when setting weighting coefficients. Near-Earth weather data and space weather data have high stability and can also be used for verification, so they have lower priority. Furthermore, the weighting coefficients can be further optimized through optimization algorithms. Therefore, in specific implementation, the initial weight of satellite sensing data can be set to 0.7, and the combined weight of near-Earth weather data and space weather data can be set to 0.3.

[0113] Once the weights of satellite sensing data, space weather data, and near-Earth weather data are set, the fused multi-source monitoring data is calculated based on a weighted fusion algorithm.

[0114] In practical implementation, when the satellite communication scenario is a high-interference scenario, the data fusion algorithm can be replaced with the Kalman filter algorithm to further improve the data's anti-noise capability, making it suitable for complex space weather regions such as the polar regions.

[0115] Step S25: Normalize the multi-source monitoring data of each spatial grid region, and input the normalized multi-source monitoring data into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model.

[0116] Because satellite sensing data, space weather data, and near-Earth weather data may contain outliers during acquisition, and different data types may have different dimensions and scales, after acquiring multi-source monitoring data, the data is normalized, and outliers are removed based on the 3σ criterion to output fused multi-source monitoring data. In this step, by eliminating measurement noise and errors from a single data source in the multi-source monitoring data, the measurement accuracy of the above parameters is improved by 30%, providing reliable data input for subsequent loss assessment.

[0117] After normalizing the multi-source monitoring data, normalized multi-source monitoring data is obtained. Based on this data, an estimated interference loss value is calculated. In this embodiment, a dynamic link loss model is constructed based on the interference intensity of different interference factors. This model is then used to analyze the multi-source monitoring data and obtain loss assessment data.

[0118] Specifically, the preset dynamic link loss model includes: a free space loss calculation unit, a space weather loss calculation unit, a near-Earth weather loss unit beam, and a summary calculation unit. Each calculation unit in this model is used to calculate its corresponding loss value, which is then summarized to obtain the total loss assessment data. For example... Figure 5 As shown, the formula for calculating the total loss assessment data is:

[0119] L_ total =L_ free +L_ space +L_ weather ;

[0120] Among them, L_ total For the overall loss assessment data; L_ free L_ represents the free space loss value. space L_ represents the space weather loss value. weather This represents near-ground weather loss.

[0121] The step of inputting the normalized multi-source monitoring data into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model includes:

[0122] Step S251: The free space loss calculation unit calculates the free space loss value based on the link distance corresponding to each of the spatial grid regions.

[0123] Free space loss is the signal attenuation caused by energy diffusion when a satellite communication signal propagates in an ideal, interference-free environment. Therefore, the free space loss value is calculated based on the communication link distance, and the data is relatively fixed, so it can be set as a fixed parameter.

[0124] Step S252: The space weather loss calculation unit calculates the space weather loss value based on multiple space weather influencing factors and the weight of each space weather influencing factor; wherein, the space weather influencing factors are calculated based on space weather data from multi-source monitoring data.

[0125] Space weather loss is a core dynamic parameter, and its calculation formula is as follows:

[0126] L_ space =k1×Φ_ particle +k2×ΔTEC+k3×S4_ norm ;

[0127] Wherein, Φ_ particle S4 represents the high-energy particle flux, ΔTEC represents the TEC change rate, and k1, k2, and k3 represent the scene adaptation coefficients. This scene adaptation system can be calibrated using measured data. norm Ionospheric scintillation index S The normalized value of 4.

[0128] Step S253: The near-ground weather loss unit calculates the near-ground weather loss value based on the parameters and rain attenuation coefficients corresponding to different frequency bands in the near-ground weather data of the multi-source monitoring data.

[0129] L_ weather Near-ground weather loss is calculated using the following formula:

[0130] L_ weather =k4×A_ norm ;

[0131] Where k4 is the frequency band coefficient, and different parameters are used for different frequency bands L, C, S, X, Ka, and Ku. Based on long-term observation data and operational results, these parameters can be adjusted in a closed loop; A_ norm Attenuation refers specifically to signal power loss caused by the atmosphere and weather (mainly rain attenuation, clouds, fog, gas absorption, etc.).

[0132] The aggregation calculation unit combines the free space loss value, space weather loss value, and near-ground weather loss value to obtain loss assessment data for each of the space grid regions.

[0133] The free space loss value, space weather loss value, near-ground weather loss value, and beam pointing deviation loss calculated in the above steps are summarized and calculated to obtain the corresponding loss assessment data for each space grid area.

[0134] Furthermore, if the satellites within the spatial grid area are LEO satellites, the preset dynamic link loss model also includes a beam pointing deviation loss calculation unit. The formula for calculating its loss assessment data is as follows:

[0135] L_ total =L_ free +L_ space +L_ weather +L_ beam Among them, L_ beam This represents the beam pointing deviation loss value.

[0136] Step S254, the step of inputting the normalized multi-source monitoring data into the preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model, further includes:

[0137] The beam pointing deviation loss is calculated based on one or more of the satellite pose data, cloud cover, or rainfall data from the multi-source monitoring data.

[0138] L_ beam The beam pointing deviation loss is calculated using the following formula:

[0139] L_ beam =k5×Δθ;

[0140] Where Δθ is the attitude offset angle and k5 is the gain coefficient.

[0141] In this step, the corresponding loss value is calculated based on each interference influencing factor to achieve real-time mapping of "environmental change - loss quantification," breaking through the limitations of the traditional static link budget model. Furthermore, the loss assessment response time provided by this step is ≤50ms (measured using light-speed communication, or even lower), accurately capturing 10-20dB of sudden space weather losses.

[0142] Step S3: Generate spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions.

[0143] In this step, after calculating the loss assessment data for each spatial grid area, the spatial interference summary information for the entire satellite communication space can be generated based on the location code corresponding to each spatial grid area.

[0144] In one embodiment, the spatial interference summary information is a spatial interference heatmap; the step of generating the spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions includes:

[0145] Step S31: Satellites within each of the aforementioned spatial grid areas send their corresponding loss assessment data and location data to the ground control center.

[0146] Combination Figure 6As shown, after each satellite completes the loss assessment data calculation for its assigned area, it transmits the loss assessment data to neighboring satellites and the ground control center. This transmission step can be achieved through inter-satellite laser links (transmission delay ≤ 1ms) to synchronize the data.

[0147] In step S32, the ground control center summarizes the loss assessment data corresponding to each of the space grid regions into a space interference heat map.

[0148] Based on the loss assessment data received from each spatial grid region, the ground control center combines the loss assessment data of each spatial grid region with the corresponding location code to generate a spatial interference heatmap. This heatmap not only visually displays the loss assessment data for each spatial grid region but also shows the spatial distribution density and intensity of interference across the entire satellite communication area. Leveraging its visualization capabilities, this spatial interference heatmap allows for the rapid identification of interference hotspots, location of interference sources, and analysis of the development trends of interference factors, enabling timely responses based on these trends.

[0149] Step S4: Adjust the transmission power of satellite communication within each spatial grid area based on the summarized spatial interference information.

[0150] Once the ground control center aggregates loss assessment data across all space grid areas and generates a space interference heatmap, it sends it to all on-orbit satellites and ground terminals via in-band signaling. Upon receiving this heatmap, satellites and ground terminals can predict the interference situation in the upcoming space grid area and adjust power in advance, rather than waiting for signal quality to degrade before providing feedback. This upgrades the traditional "post-event feedback adjustment" to "pre-event prediction and pre-adjustment," reducing power compensation lag time from 100-500ms to ≤20ms, significantly decreasing LEO satellite beam switching and link establishment time.

[0151] In detail, the step of adjusting the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information includes:

[0152] S41. The ground control center sends the space interference heat map to all on-orbit satellites and / or ground terminals within the space to which the satellite communication belongs.

[0153] S42. At least some of the on-orbit satellites and / or ground terminals within the space to which the satellite communication pertains adjust the transmission power of satellites within the corresponding space grid area based on the received space interference heatmap.

[0154] In detail, the step of adjusting the transmission power of satellites within the corresponding space grid area according to the received space interference heatmap, involving at least some of the on-orbit satellites and / or ground terminals in the space to which the satellite communication pertains, includes:

[0155] Step S421: Determine the rate of change of the interference coefficient for each spatial grid region based on the loss assessment data corresponding to each spatial grid region.

[0156] This step first calculates the rate of change of each interference coefficient based on the loss assessment data within each spatial grid region, and then determines the power adjustment step size based on this rate of change. For example, if the rate of change of the interference coefficient is >0.5 (burst interference), the corresponding power adjustment step size is ±2dB. If the rate of change of the interference coefficient is ≤0.5 (stationary interference), the corresponding power adjustment step size is ±0.5dB.

[0157] Step S422: Determine the power control range corresponding to each space grid region based on the satellite orbit type within each space grid region.

[0158] In this step, when the satellite orbit type corresponds to the high-speed moving orbit of a LEO satellite, the control frequency range is set to 100-200Hz; when the satellite orbit type corresponds to the moving orbit of a GEO satellite, the control frequency range is set to 20-50Hz; when the satellite orbit type corresponds to the moving orbit of a mobile communication scenario, the control frequency range is set to 200Hz for the mobile communication scenario.

[0159] Step S423: Determine the target SINR value corresponding to each spatial grid area based on the service scenario to which the satellites in each spatial grid area belong.

[0160] In this step, different target SINR values ​​are determined based on different business scenarios. For example, the target SINR value for voice services is ≥12dB; the target SINR value for video services is ≥15dB; and the target SINR value for data services is ≥10dB, with a margin of 3-5dB as the interference intensity increases.

[0161] Step S424: Determine the transmission power of the satellite in each space grid area based on the determined interference coefficient change rate, power control range, and target SINR.

[0162] When the interference coefficient change rate, power control range and target SINR value are determined in steps S421 to S423, the transmission power of the satellite in each spatial grid area is determined based on the interference coefficient change rate, power control range and target SINR value.

[0163] Combination Figure 6The diagram shown illustrates the signal transmission principle during the specific implementation of this embodiment. First, the ground control center completes near-Earth space global grid coding and distributes the grid coding rules to all on-orbit satellites. Onboard sensors on the satellites collect space weather data for their respective grids in real time, and the ground monitoring network simultaneously uploads near-Earth weather data. The satellites locally perform weighted fusion of the multi-source data and substitute it into the interference loss model to calculate L_. total The system synchronizes with neighboring satellites via inter-satellite links; the ground control center aggregates data from the entire region to generate an interference heatmap, and optimizes and adjusts parameters (step size, frequency, target SINR) based on service type (voice / video / data), generating power adjustment commands for both satellites and terminals; satellites adjust their transmission power in advance (completed just before entering the target grid), and terminals receive commands via in-band signaling and adjust their own transmission power; satellites and terminals measure the SINR of downlink / uplink respectively, feed it back to the control layer, and fine-tune the adjustment parameters; onboard sensors continuously collect data, updating the interference loss assessment results every 50ms to dynamically optimize power configuration.

[0164] In practice, onboard sensors can be used to continuously collect data and update the interference loss assessment results every 50ms to achieve dynamic optimization of power configuration.

[0165] In detail, when the satellite receives adjustment parameter commands, it adjusts the power amplifier's supply voltage and gain through the digital predistortion module to achieve continuously adjustable transmission power (adjustment accuracy ±0.1dB). The power adjustment formula is as follows:

[0166] P_ sat =P_ ref +L_ total -L_ margin ;

[0167] Among them, L_ total For the overall loss assessment data, P_ sat For the transmission power, P_ ref As the reference power, L_ margin To reserve redundancy (2-3dB).

[0168] When adjusting satellite transmission power using a ground terminal, the following terminal transmission power adjustment formula is used:

[0169] ;

[0170] in, For terminal transmission power, dBm is the terminal's reference transmit power, which is preset according to the terminal type. This is to compensate for losses on the satellite side, which is the increase in satellite transmission power. dB is reserved for redundancy on the terminal side.

[0171] The terminal radio frequency module receives power adjustment commands via in-line signaling and adjusts the variable gain amplifier of the transmit link to achieve dynamic adaptation of the terminal's transmit power (adjustment range 10-43dBm).

[0172] Furthermore, in order to achieve closed-loop power control, after the step of adjusting the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information, the method further includes:

[0173] S43. Obtain the real-time SINR value of the communication link between the satellite and the control terminal in each space grid area, and feed back the real-time SINR value to the ground control center, the ground terminal, or the satellite in each space grid area.

[0174] Obtain the true SINR value in the communication link within each space grid area and feed the true value back to the ground control center, ground terminal, or satellite within each space grid area.

[0175] S44. The ground control center, ground terminal, or satellites in each space grid area adjust the interference coefficient change rate, power control range, and target SINR based on the SINR value of the communication link between the satellite and the control terminal, and use the adjusted interference coefficient change rate, power control range, and target SINR to determine the transmission power of the satellites in each space grid area.

[0176] After the ground control center, ground terminal, or satellites in each space grid area receive the true SINR value, they fine-tune the interference coefficient change rate, power control range, and target SINR based on the true SINR value to further adjust the transmission power of satellites in each space grid area.

[0177] Furthermore, in this step, the ground terminal provides real-time feedback of its received SINR to generate fine-tuning instructions based on the real-time SINR, forming a two-level closed loop of satellite pre-tuning and terminal collaborative fine-tuning to follow the closed-loop power control process of "sensing-processing-control-execution-feedback". The power adjustment accuracy reaches ±0.1dB, which is an order of magnitude higher than the accuracy of the traditional fixed step size scheme. It can accurately compensate for 10-20dB of burst loss and reduce the link interruption rate.

[0178] Furthermore, in order to overcome interference caused by sudden space weather anomalies, after the step of adjusting the transmission power of satellite communication within each space grid area based on the summarized space interference information, the method further includes:

[0179] Real-time acquisition of spatial weather status data within each spatial grid area, and determination of whether there are any spatial weather anomalies within one or more spatial grid areas based on the spatial weather status data;

[0180] If anomalies in space weather are present, the interference coefficient change rate, power control range, and target SINR of satellite transmission power in each space grid region where anomalies exist are adjusted according to the space weather state data; and, based on the positional relationship between satellites in each space grid region and the space weather state data, with the satellite's motion direction as the position sequence direction, space weather state prediction data for adjacent space grid regions in the position sequence are predicted, and the interference coefficient change rate, power control range, and target SINR of satellite transmission power in each adjacent space grid region are adjusted according to the space weather state prediction data.

[0181] In this embodiment, by acquiring information about abnormal space weather conditions, adjustments are made to the publicly disclosed interference coefficient change rate, power control range, and target SINR of the satellite launch, and the satellite's transmission power is controlled using the adjusted core interference parameters. In detail, combined with... Figure 7 As shown, after the satellite transmit power control system is initialized, it first performs real-time monitoring of multi-source interference to determine if there is any interference from space weather anomalies. Space weather anomalies may include particle storms or ionospheric anomalies. Therefore, when space weather anomalies are present, the type and level of interference are determined, and corresponding parameter adjustments are made based on the type and level of interference.

[0182] In practice, the interference types can be particle storm interference caused by particle storms and ionospheric anomalous interference caused by ionospheric anomalies. Particle storm interference corresponds to the first risk level, while ionospheric anomalous interference corresponds to the second risk level. Corresponding parameter adjustment strategies are determined based on different risk levels.

[0183] In addition to adjusting parameters based on space weather anomalies, a continuous optimization control strategy was also disclosed to achieve real-time monitoring of communication link quality. Specifically, combined with Figure 7 As shown, the link quality is monitored in real time to determine whether the link quality meets the standard and whether the interference has been eliminated. If the interference is eliminated, the normal power control parameter steps are restored to operate at normal closed-loop power. Otherwise, it is determined whether the parameter adjustment exceeds the adjustment limit. If it does, the backup beam switching is initiated. If it does not exceed the limit, the adjustment step size is increased or the statistical period is extended.

[0184] Furthermore, the steps of adjusting the rate of change of the interference coefficient, the power control range, and the target SINR of satellite transmit power in each space grid region where space weather anomalies exist, based on the space weather state data, include:

[0185] Space weather state data is input into a preset coefficient prediction model to obtain the rate of change of the interference coefficient, the power control range, and the target SINR output by the preset coefficient prediction model; wherein, the preset coefficient prediction model is obtained by training a preset network model based on space weather state sample data and power parameters corresponding to the space weather state sample data.

[0186] In this step, a pre-trained preset coefficient prediction model is used to directly map parameter adjustment data from acquired space weather state data, thereby enabling control of satellite launch power based on the parameter adjustment data. In this embodiment, the preset coefficient prediction model is obtained by training a large amount of recorded space weather state data with its corresponding parameter adjustment data.

[0187] It is conceivable that satellite-to-ground communication is bidirectional, and the power adjustment method on the link is equally suitable for satellites and ground terminals. Specifically, satellite-to-ground communication is bidirectional, meaning that not only downlink communication from satellite to ground terminal but also uplink communication from ground terminal to satellite can occur. Therefore, the power control method disclosed in this embodiment is applicable not only to power adjustment on the downlink communication link but also to power adjustment on the uplink communication link. For example, the ground terminal generates a power adjustment command based on the parameter adjustment data calculated in the above steps and adjusts its uplink transmission power according to the power adjustment command. The power control method disclosed in this embodiment constructs a space sensing network composed of multiple spatial grid regions by pre-setting spatial region division rules and position coding rules. It collects space weather data in real time based on the onboard sensors in each spatial grid region and acquires near-Earth weather data synchronously uploaded by the ground monitoring network. It then fuses multi-source data composed of satellite sensing data, space weather data, and near-Earth weather data to obtain multi-source monitoring data, and determines loss assessment data based on this multi-source monitoring data. A spatial interference heatmap is constructed based on loss assessment data and the location codes of each spatial grid region. Based on the spatial interference heatmap, parameters are optimized and adjusted in combination with service type to generate satellite transmission power adjustment instructions, thereby realizing the adjustment of satellite transmission power.

[0188] Secondly, the present invention provides an adaptive control system for satellite communication power, such as... Figure 8 As shown, it includes:

[0189] The region division module 100 is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale; its function is as described in step S1.

[0190] The loss assessment module 200 is used to acquire satellite sensing data, space weather data and near-Earth weather data in each spatial grid area, and determine the loss assessment data corresponding to each spatial grid area based on the satellite sensing data, space weather data and near-Earth weather data in each spatial grid area; its function is as described in step S2.

[0191] The interference aggregation module 300 is used to generate spatial interference aggregation information based on the loss assessment data and location data corresponding to each of the spatial grid regions; its function is as described in step S3.

[0192] The power adjustment module 400 is used to adjust the transmission power of satellite communication in each spatial grid area according to the spatial interference summary information, and its function is as described in step S4.

[0193] Thirdly, this application also discloses an adaptive control device for satellite communication power, which includes: multiple satellites, a ground terminal communicating with one or more satellites, and a ground control center communicating with each satellite.

[0194] The ground control center is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale;

[0195] Satellites located within each of the aforementioned spatial grid areas are used to acquire satellite sensing data, space weather data, and near-Earth weather data within their respective spatial grid areas. Based on the satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas, satellites determine the loss assessment data corresponding to each of the aforementioned spatial grid areas and transmit the loss assessment data to satellites in other spatial grid areas and the ground control center.

[0196] The ground control center is also used to generate spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions, and to transmit the spatial interference summary information to each of the satellites and the ground terminal;

[0197] Each of the satellites and the ground terminal is used to adjust the transmission power of satellite communication within each spatial grid area based on the aggregated spatial interference information.

[0198] Optionally, each satellite is equipped with multiple onboard sensors, which are used to acquire satellite sensing data within their respective space grid areas; wherein, the satellite sensing data includes: sensing ionization index, sensing ion index, and sensing atmospheric density;

[0199] Each satellite is also connected to a ground-based auxiliary monitoring network and a satellite ground station;

[0200] Each satellite acquires space weather data by accessing the aforementioned ground-aided monitoring network, and acquires near-Earth weather data by accessing satellite ground stations.

[0201] Improved stability: It can accurately compensate for 10-20dB of sudden space weather losses, narrowing the SINR fluctuation range from ±5dB to ±1dB, and reducing the link interruption rate from 15% to ≤3%;

[0202] Link establishment efficiency optimization: LEO satellite beam switching link establishment time has been shortened from 500ms to ≤200ms, and the switching failure rate has been reduced from 8% to ≤1%, meeting the real-time communication requirements of mobile communication;

[0203] Reduced power consumption: Satellite transmit power redundancy is reduced by 5-8dB, real-time communication power consumption is reduced by 15-20%, and satellite on-orbit lifespan is extended by 3-5 years; terminal transmit power is reduced by an average of 3-5dB, and radiation impact is significantly reduced.

[0204] Scenario adaptability: Compatible with GEO, LEO, MEO multi-orbit satellites and Ka / Ku bands, adaptable to multiple service scenarios such as voice, video, data, and mobile communication, without the need for separate design solutions for a single scenario.

[0205] This invention provides an adaptive adjustment method, system, and apparatus for satellite communication power. The method divides the space in which satellite communication is located into multiple spatial grid regions according to a preset spatial division scale. Satellite sensing data, space weather data, and near-Earth weather data are acquired for each spatial grid region. Based on these data, loss assessment data is determined for each spatial grid region. Spatial interference summary information is generated based on the loss assessment data and location data for each spatial grid region. The transmission power of satellite communication within each spatial grid region is adjusted according to the spatial interference summary information. This method and system improve the reliability of satellite communication in complex space environments by collecting weather data from both the space region and the near-Earth region to determine loss assessment data and dynamically and adaptively adjusting the satellite transmission power within each spatial grid region based on this loss assessment data.

[0206] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0207] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application.

Claims

1. An adaptive control method for satellite communication power, characterized in that, include: According to the preset spatial division scale, the space to which satellite communication belongs is divided into multiple spatial grid regions; The satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas are acquired, and the loss assessment data of the corresponding communication links within each of the aforementioned spatial grid areas are determined based on the satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas. Based on the loss assessment data and location data of the communication link corresponding to each of the spatial grid regions, spatial interference summary information is generated; Based on the aggregated spatial interference information, adjust the transmission power of satellite communication within each of the aforementioned spatial grid areas; The step of adjusting the transmission power of satellite communication within each of the aforementioned spatial grid areas based on the aggregated spatial interference information includes: Based on the loss assessment data corresponding to each of the spatial grid regions, the rate of change of the interference coefficient corresponding to each of the spatial grid regions is determined; wherein, the rate of change of the interference coefficient is the rate of change of the loss assessment data relative to the space. Based on the satellite orbit type within each of the aforementioned spatial grid regions, determine the power control range corresponding to each of the aforementioned spatial grid regions; Based on the service scenario to which the satellites in each of the aforementioned spatial grid areas belong, determine the target SINR value corresponding to each spatial grid area; Based on the determined rate of change of the interference coefficient, the power control range, and the target SINR, the transmit power of the satellites in each of the space grid areas is determined; the power adjustment step size is determined based on the rate of change of the interference coefficient.

2. The adaptive control method for satellite communication power according to claim 1, characterized in that, The steps for acquiring satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas include: Satellite sensors on each of the aforementioned spatial grid regions are used to acquire satellite sensing data within each of the aforementioned spatial grid regions; wherein, the satellite sensing data includes: sensing ionization index, sensing ion index, and sensing atmospheric density; Acquire ground ionospheric monitoring data and meteorological radar monitoring data within each of the aforementioned spatial grid areas, and determine the spatial weather data for each of the aforementioned spatial grid areas based on the ionization index, ion index, cloud thickness, and rainfall in the ground ionospheric monitoring data and the meteorological radar monitoring data; The regional location of each spatial grid region on Earth is determined by using the regional code corresponding to each spatial grid region, and the near-Earth weather data of each spatial grid region is determined based on the weather data of the regional location of each spatial grid region on Earth. Each spatial grid region corresponds to a different regional code, and a spatial regional code sequence is constructed based on the regional code of each spatial grid region and the positional relationship between each spatial grid region.

3. The adaptive control method for satellite communication power according to claim 1, characterized in that, The step of determining the loss assessment data of the communication link corresponding to each of the space grid areas based on satellite sensing data, space weather data, and near-Earth weather data within each of the space grid areas includes: According to the preset weighting coefficients, the satellite sensing data, space weather data and near-Earth weather data in each of the spatial grid areas are weighted and fused to obtain the multi-source monitoring data corresponding to each of the spatial grid areas after fusion. The multi-source monitoring data of each spatial grid region is normalized, and the normalized multi-source monitoring data is input into a preset dynamic link loss model to obtain the loss assessment data of each spatial grid region output by the preset dynamic link loss model.

4. The adaptive control method for satellite communication power according to claim 1, characterized in that, The aggregated space interference information is a space interference heatmap; the step of adjusting the transmission power of satellite communication within each of the space grid areas based on the aggregated space interference information includes: The space interference heatmap is sent to all on-orbit satellites and / or ground terminals within the space where the satellite communication is located. At least some of the on-orbit satellites and / or ground terminals within the space to which satellite communication pertains adjust the transmission power of satellites within the corresponding space grid area based on the received space interference heatmap.

5. The adaptive control method for satellite communication power according to claim 1, characterized in that, After the step of adjusting the transmission power of satellite communication within each of the space grid areas based on the aggregated space interference information, the method further includes: The real-time SINR value of the communication link between the satellite and the control terminal in each of the aforementioned spatial grid areas is obtained, and the real-time SINR value is fed back to the ground control center, the ground terminal, or the satellite in each spatial grid area; The ground control center, ground terminal, or satellites within each space grid area adjust the interference coefficient change rate, power control range, and target SINR based on the real-time SINR value received from the communication link between the satellite and the control terminal, and use the adjusted interference coefficient change rate, power control range, and target SINR to determine the transmission power of satellite communication within each space grid area.

6. The adaptive control method for satellite communication power according to claim 1, characterized in that, After adjusting the transmission power of satellite communication within each of the aforementioned spatial grid areas based on the aggregated spatial interference information, the method further includes: Real-time acquisition of spatial weather status data within each of the aforementioned spatial grid areas, and determination of whether there are any spatial weather anomalies within one or more spatial grid areas based on the spatial weather status data; If there are abnormal space weather conditions, the interference coefficient change rate, power control range, and target SINR of the satellite transmission power in each space grid area where abnormal space weather conditions exist shall be adjusted according to the space weather status data. Furthermore, based on the positional relationship between satellites within each of the aforementioned spatial grid areas and the spatial weather state data, and taking the direction of satellite motion as the direction of the position sequence, the spatial weather state prediction data for adjacent spatial grid areas in the position sequence is predicted, and the interference coefficient change rate, power control range, and target SINR of the satellite transmission power in the adjacent spatial grid areas are adjusted according to the spatial weather state prediction data.

7. The adaptive control method for satellite communication power according to claim 6, characterized in that, The steps for adjusting the rate of change of the interference coefficient, the power control range, and the target SINR of satellite transmit power in each space grid region where space weather anomalies exist, based on the space weather state data, include: Space weather state data is input into a preset coefficient prediction model to obtain the rate of change of the interference coefficient, the power control range, and the target SINR output by the preset coefficient prediction model; wherein, the preset coefficient prediction model is obtained by training a preset network model based on space weather state sample data and power parameters corresponding to the space weather state sample data.

8. An adaptive control system for satellite communication power, characterized in that, include: The region division module is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale; The loss assessment module is used to acquire satellite sensing data, space weather data and near-Earth weather data in each of the space grid areas, and determine the loss assessment data of the corresponding communication link in each of the space grid areas based on the satellite sensing data, space weather data and near-Earth weather data in each of the space grid areas. The interference aggregation module is used to generate spatial interference aggregation information based on the loss assessment data and location data corresponding to each of the spatial grid regions; The power adjustment module is used to adjust the transmission power of satellite communication within each of the spatial grid areas based on the aggregated spatial interference information. The step of adjusting the transmission power of satellite communication within each of the aforementioned spatial grid areas based on the aggregated spatial interference information includes: Based on the loss assessment data corresponding to each of the spatial grid regions, the rate of change of the interference coefficient corresponding to each of the spatial grid regions is determined; wherein, the rate of change of the interference coefficient is the rate of change of the loss assessment data relative to the space. Based on the satellite orbit type within each of the aforementioned spatial grid regions, determine the power control range corresponding to each of the aforementioned spatial grid regions; Based on the service scenario to which the satellites in each of the aforementioned spatial grid areas belong, determine the target SINR value corresponding to each spatial grid area; Based on the determined rate of change of the interference coefficient, the power control range, and the target SINR, the transmit power of the satellites in each of the space grid areas is determined; the power adjustment step size is determined based on the rate of change of the interference coefficient.

9. An adaptive control device for satellite communication power, characterized in that, include: Multiple satellites, ground terminals communicating with one or more satellites, and ground control centers communicating with each satellite; The ground control center is used to divide the space to which satellite communication belongs into multiple spatial grid regions according to a preset spatial division scale; Satellites located within each of the aforementioned spatial grid areas are used to acquire satellite sensing data, space weather data, and near-Earth weather data within their respective spatial grid areas. Based on the satellite sensing data, space weather data, and near-Earth weather data within each of the aforementioned spatial grid areas, they determine the loss assessment data corresponding to each of the aforementioned spatial grid areas and transmit the loss assessment data to satellites in other of the aforementioned spatial grid areas and to the ground control center. The ground control center is also used to generate spatial interference summary information based on the loss assessment data and location data corresponding to each of the spatial grid regions, and to transmit the spatial interference summary information to each of the satellites and the ground terminal; Each of the satellites and the ground terminal is used to adjust the transmission power of satellite communication within each of the space grid areas based on the aggregated space interference information; The step of adjusting the transmission power of satellite communication within each of the aforementioned spatial grid areas based on the aggregated spatial interference information includes: Based on the loss assessment data corresponding to each of the spatial grid regions, the rate of change of the interference coefficient corresponding to each of the spatial grid regions is determined; wherein, the rate of change of the interference coefficient is the rate of change of the loss assessment data relative to the space. Based on the satellite orbit type within each of the aforementioned spatial grid regions, determine the power control range corresponding to each of the aforementioned spatial grid regions; Based on the service scenario to which the satellites in each of the aforementioned spatial grid areas belong, determine the target SINR value corresponding to each spatial grid area; Based on the determined rate of change of the interference coefficient, the power control range, and the target SINR, the transmit power of the satellites in each of the space grid areas is determined; the power adjustment step size is determined based on the rate of change of the interference coefficient.

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