Emergency command system and method based on satellite communication

Abstract

The invention discloses an emergency command system and method based on satellite communication, and particularly relates to the technical field of radio transmission. On-site information of a disaster area is obtained in real time, the information is transmitted to an emergency command center through a satellite communication channel, dynamic command decision and resource optimization are achieved, in the signal transmission process of the system, the phase noise and the inter-carrier interference ratio of satellite signals are monitored and analyzed in real time, whether the signals are distorted or not is judged, and when the signals are distorted, the emergency command center is started. The system is automatically switched to a standby satellite communication channel to ensure that information transmission is not interrupted; besides, the satellite communication link monitoring system can adjust the signal quality in real time and carry out fault-tolerant processing, continuous operation of the command system is ensured, emergency response failure caused by communication interruption is avoided, the stability of satellite signals in various environments is effectively improved, and efficient operation of the emergency command system is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of radio transmission, and in particular to an emergency command system and method based on satellite communication. Background Art

[0002] With the rapid development of global communication technology, satellite communications have gradually played an important role in emergency command systems. Traditional emergency command systems mainly rely on ground communication networks such as radio, telephone and the Internet, but when disasters occur, ground communications are often damaged or interrupted, resulting in obstruction of information transmission. Satellite communication systems can provide stable communication support during post-disaster recovery, and therefore have become a key technical means in emergency command. Emergency command methods based on satellite communications can ensure effective collaboration and information sharing among emergency departments in the absence of ground communication facilities, and improve the efficiency and timeliness of emergency response. Especially in extreme environments such as natural disasters or wartime, satellite communications have shown their irreplaceable advantages.

[0003] The prior art has the following deficiencies: Although the emergency command system based on satellite communication has many advantages, in actual application, satellite signals may be distorted. Since satellite communication relies on signal propagation in the atmosphere, severe weather conditions (such as strong winds, heavy rains, sandstorms, etc.) may cause temporary loss of signals or degradation of quality, which poses a major challenge to the real-time and reliability of the emergency command system. At the disaster site, the timely transmission of information may determine the success or failure of emergency response. Therefore, how to ensure the stability of satellite signals in various environments has become a difficult problem in current technology. Summary of the invention

[0004] The purpose of the present invention is to provide an emergency command system and method based on satellite communication to solve the shortcomings of the background technology.

[0005] In order to achieve the above object, the present invention provides the following technical solution: an emergency command method based on satellite communication, comprising the following steps: S1: When an emergency occurs, real-time on-site information of the disaster area is obtained through the satellite communication network, including geographic location, disaster assessment and resource demand data; S2: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center, where dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies; S3: During satellite signal transmission, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted. S4: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; S5: Use the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

[0006] Preferably, in S3, after analyzing the increase of the phase noise, a phase noise increase abnormality index is generated, and the method for obtaining the phase noise increase abnormality index is: Get the original time domain signal x(t), expressed as: , where N is the number of data points, For the sampled time domain signal value, use fast Fourier transform to convert the time domain signal into frequency domain signal. The formula of Fourier transform is: ; Where: X(f) is the representation of the signal in the frequency domain, called the spectrum, f is the frequency, j is the imaginary unit, is the kernel function of Fourier transform. By calculating the amplitude spectrum and phase spectrum of the spectrum X(f), the phase noise information is obtained. The phase noise is expressed as: ; Where: L(f) represents the phase noise spectral density, is the square of the amplitude of the spectrum X(f), indicating the signal strength, is a constant. Based on spectrum analysis, the spectrum in two time periods is and By comparison, the phase noise increase abnormality index is calculated, and the expression is: ; Where: SD is the phase noise increase abnormality index.

[0007] Preferably, in S3, after analyzing the fluctuation of the inter-carrier interference ratio, an inter-carrier interference ratio fluctuation index is generated, and the method for obtaining the inter-carrier interference ratio fluctuation index is: First, obtain the time domain data of the C / I signal in the frequency interval. C / I represents the ratio of carrier power to interference power. Calculate a C / I value at each moment and divide the C / I signal into multiple boxes. Each box represents a discrete C / I range. Calculate the frequency of occurrence of the C / I signal in each box, that is, the probability of the C / I value in the box. Set it in M ​​intervals. Pi represents the probability of the C / I value in the i-th interval. Calculate the probability , the expression is: ,For the discretized probability distribution of C / I signal, calculate the entropy H of C / I signal: ;in: is the probability of the ith interval, and the inter-carrier interference ratio fluctuation index is calculated. The expression is: ; In the formula, BK is the inter-carrier interference ratio fluctuation index, ΔH is the difference in entropy values ​​of the C / I signal in different time periods, is the entropy value in the reference state.

[0008] Preferably, the phase noise increase anomaly index and the inter-carrier interference ratio fluctuation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as inputs of the machine learning model. The machine learning model uses the probability analysis value labels of satellite signal distortion predicted by each group of comprehensive feature vectors as prediction targets, and minimizes the sum of prediction errors of probability analysis value labels of all satellite signals being distorted as training targets. The machine learning model is trained until the sum of prediction errors converges, and the model training is stopped. The probability analysis value of satellite signal distortion is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0009] Preferably, the acquired probability analysis value of the satellite signal distortion is compared with a preset probability analysis value reference threshold; if the probability analysis value of the satellite signal distortion is greater than or equal to the preset probability analysis value reference threshold, it is classified as a satellite signal distortion situation; if the probability analysis value of the satellite signal distortion is less than the preset probability analysis value reference threshold, it is classified as a satellite signal non-distortion situation.

[0010] Preferably, in S5, the satellite communication link monitoring system first monitors the quality of the satellite signal in real time. When the signal quality is lower than the set threshold, it automatically triggers the switching mechanism of the backup satellite communication channel or the backup channel; and gradually reduces the data transmission load of the main channel. After switching to the backup channel, the system continues to monitor the signal quality of the backup channel and predicts the long-term performance of the backup channel. The use priority of the backup channel is adjusted according to the prediction results. Once the signal quality of the main channel recovers to the predetermined available range, the system will automatically switch back to the main channel.

[0011] The present invention also provides an emergency command system based on satellite communication, including a data acquisition module, a communication and decision-making module, a monitoring and analysis module, a management module and a fault-tolerant processing module; Data collection module: When an emergency occurs, it obtains real-time on-site information of the disaster area through the satellite communication network, including geographic location, disaster assessment and resource demand data; Communication and decision-making module: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center. At the emergency command center, dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies. Monitoring and analysis module: During the satellite signal transmission process, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted; Management module: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; Fault-tolerant processing module: Utilize the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

[0012] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. The present invention can accurately judge the quality change of satellite signals by real-time monitoring of the phase noise and inter-carrier interference ratio fluctuations of satellite signals, and automatically switch to the backup satellite communication channel when the signal is distorted to ensure the continuity of information transmission and the stable operation of the command system. Combined with the real-time adjustment and fault-tolerant processing mechanism of the satellite communication link monitoring system, the system can flexibly respond to signal quality fluctuations in different environments, avoid failure of the command system due to communication interruption, and thus provide efficient emergency command support for disaster areas.

[0013] 2. The present invention adopts a machine learning model to predict the probability of satellite signal distortion through a comprehensive feature vector, thereby realizing intelligent monitoring and early warning of satellite signal quality. By minimizing the prediction error, the model can adjust the signal processing strategy in real time to adapt to the dynamically changing communication environment. When the signal quality is restored, the system can automatically switch back to the main channel and gradually restore the data transmission of the main channel to ensure the continuity and reliability of the command system. This technology not only improves the response efficiency of the emergency command system, but also optimizes resource allocation, ensuring smooth information and timely decision-making in disaster emergency response. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0015] Figure 1 The present invention is a flow chart of the method.

[0016] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, the emergency command method based on satellite communication described in this embodiment includes the following steps: S1: When an emergency occurs, real-time on-site information of the disaster area is obtained through the satellite communication network, including geographic location, disaster assessment and resource demand data; S2: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center, where dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies; S3: During satellite signal transmission, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted. S4: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; S5: Use the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

[0019] In S1, when an emergency occurs, on-site information of the disaster area is obtained in real time through the satellite communication network, including the specific process of geographical location, disaster assessment and resource demand data. This involves multiple links and aims to ensure the rapid and accurate transmission of disaster area information, thereby supporting the command center to make timely and effective decisions.

[0020] Satellite positioning system: The emergency command system can obtain real-time geographical location information of the disaster area by accessing satellite positioning systems (such as GPS, GLONASS, etc.). Through satellite signals, the command center can obtain the precise coordinates of the disaster area (latitude and longitude, altitude, etc.) and the dynamic changes in the specific location.

[0021] Real-time navigation and map updates: Satellite communications can provide real-time navigation support for disaster areas. Through satellite images and data, the locations of various locations, shelters, hospitals, transportation facilities, etc. in the disaster area can be updated. Based on these data, the command center can grasp the geographical distribution of the disaster area and quickly assess which areas are most severely affected and which areas need priority rescue.

[0022] Positioning of emergency personnel: Satellite communications can also be used to track the location of rescue personnel and equipment in real time, ensuring the coordination of rescue operations and the efficient dispatch of resources.

[0023] Satellite remote sensing technology: Satellite remote sensing technology can obtain ground images of disaster areas through various sensors carried by satellites (such as optical, infrared, radar, etc.). These images can reflect the detailed situation of the disaster area, including the degree of damage to infrastructure after the disaster, the smoothness of roads, and the flooding of waters. Image processing and analysis: Through remote sensing images, information such as the affected area, severity, and traffic interruption areas in the disaster area can be extracted and transmitted to the command center. Advanced image processing technologies (such as automated analysis, machine learning, etc.) can help commanders quickly identify the worst-hit areas.

[0024] Disaster data integration: Through the satellite communication network, the disaster assessment results (such as casualties, building damage, road closures, etc.) are integrated with other disaster area data (meteorological, environmental, etc.) to form a comprehensive disaster report. Dynamic disaster update: Satellite communication can provide continuous real-time images and data streams to the disaster area, enabling the command center to continuously update the disaster assessment and adjust the rescue strategy in a timely manner.

[0025] Material demand assessment: Emergency command terminals in disaster areas (such as rescue command vehicles, temporary communication stations, on-site command centers, etc.) transmit material demand information to the command center in real time through satellite communication networks, including food, medical supplies, clothing, drinking water, rescue equipment, etc. The demand data of the disaster area is transmitted to the satellite network through the input devices of the emergency terminals (such as handheld terminals, mobile communication devices, etc.).

[0026] Real-time monitoring of resource status: Satellite communications can not only obtain resource needs in disaster areas, but also monitor the distribution of existing resources. For example, satellite images can help the command center understand the storage status of various material storage warehouses and medical facilities, thus providing a basis for subsequent material allocation.

[0027] Personnel requirements and deployment: Based on the disaster assessment, the satellite communication network can obtain the personnel requirements of the disaster area, including the urgent needs of medical assistance, rescue teams and other professionals. The command center can deploy according to these needs to ensure a rapid and effective resource response.

[0028] By integrating geographic location information, disaster assessment and resource demand data into the emergency command system through satellite communication networks, the command center can conduct multi-dimensional comprehensive analysis and assess the overall situation in the disaster area. This data fusion can help commanders identify the most urgent needs and prioritize the mobilization of resources.

[0029] Emergency decision-making model: Combined with real-time satellite data, the command center can use data-based decision support systems to optimize emergency response. For example, the system can automatically generate the most appropriate rescue plan based on the resource needs, weather forecast, and disaster situation in the disaster area, and issue instructions to the on-site rescue team through satellite communications.

[0030] Remote coordination and real-time feedback: Satellite communication networks enable command organizations at all levels to obtain real-time feedback information from disaster areas. The emergency command center can interact and coordinate with emergency teams, rescue personnel, medical institutions, etc. in real time through the network to ensure that various rescue operations can be carried out synchronously.

[0031] In this application, through the satellite communication network, the command center can obtain the precise geographic location of the disaster area, disaster assessment data and real-time resource demand information, so as to make quick and accurate decisions. The acquisition and analysis of these real-time data enables the command center to efficiently dispatch resources, optimize emergency response strategies, and improve the overall efficiency of post-disaster recovery work.

[0032] In S2, on-site information of the disaster area is collected through satellite communication channels. This information usually includes the geographical location of the disaster area, disaster assessment data (such as the scope of the disaster, casualties, infrastructure damage, etc.), meteorological data, and resource demand information. This information can be collected in real time through various on-site sensors (such as remote sensing images, temperature, humidity, air pressure, etc.). The on-site information is sent to the satellite communication network through the emergency communication terminal in the disaster area (such as satellite phone, satellite data transmission equipment), and then transmitted to the emergency command center through the satellite channel. In this process, the satellite channel plays a key role in ensuring smooth communication over long distances and without ground networks. Especially when the ground communication infrastructure is damaged, the satellite communication channel is particularly important.

[0033] After receiving the disaster area information transmitted by satellite, the emergency command center analyzes the real-time data through the data processing platform. With the help of advanced data analysis tools (such as geographic information system GIS, disaster assessment system, artificial intelligence decision support system, etc.), the command center can quickly identify changes in the disaster area, including the scope of the disaster, the degree of disaster, and the damage to key facilities. In the case of changing disasters, the command center uses real-time data to make dynamic decisions. For example, when the disaster in a certain area intensifies, the command center can adjust the rescue priority in real time and change the direction of resource dispatch to ensure that urgently needed resources (such as medical teams, rescue supplies, etc.) are mobilized at the first time. The command center can also predict the development trend of the disaster through trend analysis of satellite data. Based on the combination of historical data and real-time satellite information, the command center can predict the subsequent impact of certain disaster events, such as floods and landslides, and make early warnings and emergency deployments.

[0034] The emergency command center receives resource demand information in the disaster area through satellite signals, and can evaluate the material demand (such as medical supplies, food, drinking water, etc.) and personnel deployment demand in the disaster area in real time. The command center quickly mobilizes rescue teams, material transportation, medical resources, etc. according to the actual needs of the disaster area to ensure that resources can be delivered to the most needed places in a timely and accurate manner. The command center adjusts the priority of emergency response according to the disaster area situation reflected by satellite data. For example, when some roads in the disaster area are blocked or communications are interrupted, the command center can select the best rescue route based on real-time satellite images and traffic data to ensure that the rescue team can enter the disaster area smoothly. For some areas with extremely urgent medical resource needs, the command center will give priority to the deployment of hospitals, medical supplies and other support. Emergency response is not only a one-time deployment. As the disaster situation changes, resource allocation and emergency strategies also need to be adjusted in real time. For example, when the meteorological conditions in a disaster area change and cause a new disaster, the command center will promptly obtain meteorological data transmitted by the satellite communication network, so as to adjust the response strategy, mobilize new resources, and ensure uninterrupted emergency rescue.

[0035] Satellite communications can ensure efficient information sharing and collaborative decision-making between emergency command centers in different regions. For example, when the disaster area is large and widely distributed, command centers in multiple regions can share on-site information and response measures in real time through satellite communications, thereby avoiding duplication or dispersion of resources and rescue forces and ensuring the integration and efficiency of command. The real-time nature of satellite communications ensures that the command center can obtain the situation in the disaster area as soon as the disaster occurs and respond quickly. With the real-time transmission of disaster data, the command center can directly enter the rescue state, avoiding response delays caused by information lags.

[0036] In S3, phase noise refers to the random fluctuation of the carrier phase of the satellite signal in time, which is usually caused by atmospheric disturbances during signal propagation, unstable equipment performance, or other external interference. Phase noise can cause the phase of the signal to become unstable, which in turn affects the demodulation quality of the signal and may even cause data loss or communication failure.

[0037] In satellite communication systems, the received satellite signals are often monitored in real time through special phase noise analysis instruments or software. Normal phase noise should be within a certain range. If the phase noise increases abnormally, it may be caused by atmospheric ionospheric disturbances, equipment failure or signal attenuation. In this case, the increase in phase noise will directly affect the stability and accuracy of the signal, resulting in information decoding errors or loss. Therefore, real-time monitoring and analysis of phase noise levels can help to detect signal distortion in a timely manner.

[0038] After analyzing the increase of phase noise, a phase noise increase abnormality index is generated. The method for obtaining the phase noise increase abnormality index is as follows: First, obtain the original time domain signal x(t), which is usually sampled time series data, expressed as: , where N is the number of data points, For the sampled time domain signal value, use fast Fourier transform to convert the time domain signal into frequency domain signal. The formula of Fourier transform is: ; Where: X(f) is the representation of the signal in the frequency domain, called the spectrum, f is the frequency, j is the imaginary unit, is the kernel function of Fourier transform. By calculating the amplitude spectrum and phase spectrum of spectrum X(f), the phase noise information can be obtained. Phase noise is expressed as: ; Where: L(f) represents the phase noise spectral density, is the square of the amplitude of the spectrum X(f), indicating the signal strength, is a constant. Based on spectrum analysis, the spectrum in the same time period is and By comparison, the phase noise increase abnormality index is calculated, and the expression is: ; Where: SD is the phase noise increase abnormality index. If the SD value is large, it means that the phase noise has increased significantly and there may be an abnormality. If the SD value is small, it means that the phase noise has not increased significantly and the system status is normal.

[0039] The Carrier-to-Noise Ratio (C / N ratio) indicates the ratio of the strength of the carrier signal to the noise signal. A higher C / N ratio means a stronger signal and less noise, and better communication quality; while a lower C / N ratio means that the effective carrier of the signal is weaker, the noise interference is greater, the communication quality is poor, and signal distortion may occur.

[0040] Satellite communication systems can calculate the C / N ratio in real time through a signal analyzer. The ratio of signal strength to noise power can be obtained in real time through the signal quality monitoring module in the receiving device and transmitted to the emergency command center through a feedback mechanism. The C / N ratio is usually closely related to the signal-to-noise ratio (SNR) of the signal. If the C / N ratio drops to a certain critical value, the decoding and data transmission capabilities of the communication system will be affected, and the signal will be significantly distorted, which may lead to information loss or decoding errors. Therefore, continuous monitoring of the C / N ratio can help to detect the decline in signal quality in a timely manner and take appropriate repair measures. In disaster scenarios, the reduction in the C / N ratio may be caused by factors such as signal attenuation, weather conditions (such as heavy rain, heavy snow, etc.), or unstable communications due to equipment failure.

[0041] After analyzing the fluctuation of the inter-carrier interference ratio, an inter-carrier interference ratio fluctuation index is generated. The method for obtaining the inter-carrier interference ratio fluctuation index is as follows: First, obtain the time domain data of the C / I signal in a certain time period or frequency interval. For example, C / I can be the ratio of carrier power to interference power, and a C / I value can be calculated at each moment. Normalize the C / I signal to ensure that the data is in the range of [0, 1]. Normalization can reduce the impact of dimensional differences and make subsequent processing more stable and unified.

[0042] The normalized C / I signal is discretized. Usually, the C / I signal is divided into multiple bins, each bin represents a discrete C / I range, and the frequency of occurrence of the C / I signal in each bin is calculated, that is, the probability of the C / I value in the bin, set in M ​​intervals, pi represents the probability of the C / I value in the i-th interval, and the probability is calculated , the expression is: ,For the discretized probability distribution of C / I signal, calculate the entropy H of C / I signal: ;in: is the probability of the ith interval, and the inter-carrier interference ratio fluctuation index is calculated. The expression is: ; In the formula, BK is the inter-carrier interference ratio fluctuation index, ΔH is the difference in entropy values ​​of the C / I signal in different time periods, It is the entropy value under the reference state, which can usually be taken as the entropy value of the C / I signal under the ideal or stable state.

[0043] The phase noise increase anomaly index and the inter-carrier interference ratio fluctuation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as the input of the machine learning model. The machine learning model uses the probability analysis value label of the satellite signal distortion predicted by each group of comprehensive feature vectors as the prediction target, and takes minimizing the sum of the prediction errors of the probability analysis value labels of all satellite signals with distortion as the training target. The machine learning model is trained until the sum of the prediction errors converges, and the model training is stopped. The probability analysis value of the satellite signal distortion is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0044] The acquired probability analysis value of the satellite signal distortion is compared with the preset probability analysis value reference threshold. If the probability analysis value of the satellite signal distortion is greater than or equal to the preset probability analysis value reference threshold, it is classified as the satellite signal distortion; if the probability analysis value of the satellite signal distortion is less than the preset probability analysis value reference threshold, it is classified as the satellite signal non-distortion.

[0045] S4: When the satellite signal is distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system.

[0046] When satellite signals are distorted, to ensure that information transmission is not affected, emergency measures need to be taken to guarantee the continuity of the communication system. First, the system will monitor the quality of satellite signals in real time and use a previously established prediction model to determine whether signal distortion has occurred. Once a decrease in signal quality or distortion is detected, the system will automatically activate the backup satellite communication channel and quickly switch to this channel. This process is usually completed through an automated switching mechanism without manual intervention to reduce switching latency.

[0047] After switching to the backup satellite communication channel, the backup channel will immediately take over the task of transmitting the information flow, ensuring that communication is not interrupted and avoiding the long-term impact of signal distortion on the command system or data transmission. The backup channel is usually similar to the main channel in terms of performance and bandwidth and can provide sufficient resources to maintain efficient communication.

[0048] In addition, to ensure the continuous operation of the command system, the use of the backup channel is not limited to a single communication task. It will also flexibly adjust the signal transmission priority according to real-time needs to ensure that emergency instructions, real-time data, and monitoring information can be transmitted to relevant personnel in a timely manner. This switching mechanism provides redundant protection for satellite communication and can effectively improve the reliability and emergency response ability of the communication system.

[0049] S5: Use the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, automatically perform fault tolerance processing, and avoid the failure of the command system due to communication interruption.

[0050] First, the satellite communication link monitoring system needs to monitor the quality of satellite signals in real time, including the signal-to-noise ratio (SNR) and the bit error rate (BER). The calculation formulas are as follows: Signal-to-noise ratio (SNR): ; where is the signal power at time t, is the noise power.

[0051] Set signal quality thresholds, including the SNR threshold and the BER threshold: For example, SNR threshold: SNRthreshold = 10 dB (for example, the specific value can be adjusted according to system requirements).

[0052] Once the signal quality is monitored to be lower than the threshold, the system should immediately activate the backup satellite communication channel or the backup channel to avoid communication interruption. The specific steps are as follows: Step 1: Monitor the signal quality Q(t) in real time, such as SNR, BER, phase noise, etc.

[0053] Step 2: If Q(t) < Qthreshold, it is determined that the signal is distorted, and the system automatically switches to the backup satellite channel, where Qthreshold is the signal quality threshold; Step 3: After the backup channel is switched, it starts synchronizing the new signal data stream and gradually reduces the data transmission load of the main channel.

[0054] After switching to the backup channel, the satellite communication link monitoring system needs to continue to monitor the quality of the new signal to ensure that the backup channel does not have similar problems. In addition, the system needs to record the quality data of the main channel and the backup channel for subsequent performance analysis and optimization.

[0055] After switching, monitor the quality of the backup channel (e.g., SNR, BER, phase noise, etc.). Use regression analysis or machine learning models to predict the long-term performance of the backup channel, and adjust the priority of the backup channel based on the prediction results. Once the signal quality of the primary channel returns to the predetermined usable range (i.e., the quality is better than the preset threshold), the system automatically switches back to the primary channel while ensuring that no information is lost or communication is interrupted during the process. When the signal quality of the primary channel exceeds the threshold, the primary channel transmission is automatically restored. Gradually switch the data traffic of the backup channel back to the primary channel.

[0056] In this embodiment, when an emergency occurs, on-site information of the disaster area, including geographic location, disaster assessment and resource demand data, is obtained in real time through the satellite communication network, and this information is transmitted to the emergency command center. In the command center, real-time data of satellite signals are used to make dynamic decisions to optimize resource allocation and emergency response strategies. During signal transmission, the phase noise and inter-carrier interference ratio of the satellite signal are monitored and analyzed in real time to determine whether the signal is distorted. If the signal is distorted, the system will automatically switch to the backup satellite communication channel to ensure smooth transmission of information and continuous operation of the command system. At the same time, the satellite communication link monitoring system will monitor and adjust the signal quality in real time, implement automatic fault-tolerant processing, and avoid communication interruptions affecting the normal operation of the command system.

[0057] Example 2, please refer to Figure 2 As shown, the satellite communication-based emergency command system described in this embodiment includes a data acquisition module, a communication and decision-making module, a monitoring and analysis module, a management module and a fault-tolerant processing module; Data collection module: When an emergency occurs, it obtains real-time on-site information of the disaster area through the satellite communication network, including geographic location, disaster assessment and resource demand data; Communication and decision-making module: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center. At the emergency command center, dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies. Monitoring and analysis module: During the satellite signal transmission process, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted; Management module: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; Fault-tolerant processing module: Utilize the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

[0058] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0059] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0060] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0061] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An emergency command method based on satellite communication, characterized in that: The following steps are involved: S1: When an emergency occurs, real-time on-site information of the disaster area is obtained through the satellite communication network, including geographic location, disaster assessment and resource demand data; S2: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center, where dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies; S3: During satellite signal transmission, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted. S4: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; S5: Use the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

2. The satellite communication-based emergency command method according to claim 1, characterized in that: In S3, the increase of the phase noise is analyzed to generate a phase noise increase abnormality index, and the method for obtaining the phase noise increase abnormality index is: Get the original time domain signal x(t), expressed as: , where N is the number of data points, For the sampled time domain signal value, use fast Fourier transform to convert the time domain signal into frequency domain signal. The formula of Fourier transform is: ; Where: X(f) is the representation of the signal in the frequency domain, called the spectrum, f is the frequency, j is the imaginary unit, is the kernel function of Fourier transform. By calculating the amplitude spectrum and phase spectrum of the spectrum X(f), the phase noise information is obtained. The phase noise is expressed as: ; Where: L(f) represents the phase noise spectral density, is the square of the amplitude of the spectrum X(f), indicating the signal strength, is a constant. Based on spectrum analysis, the spectrum in two time periods is and By comparison, the phase noise increase abnormality index is calculated, and the expression is: ; Where: SD is the phase noise increase abnormality index.

3. The satellite communication-based emergency command method according to claim 2, characterized in that: In S3, after analyzing the fluctuation of the inter-carrier interference ratio, an inter-carrier interference ratio fluctuation index is generated. The method for obtaining the inter-carrier interference ratio fluctuation index is: First, obtain the time domain data of the C / I signal in the frequency interval. C / I represents the ratio of carrier power to interference power. Calculate a C / I value at each moment and divide the C / I signal into multiple boxes. Each box represents a discrete C / I range. Calculate the frequency of occurrence of the C / I signal in each box, that is, the probability of the C / I value in the box. Set it in M ​​intervals. Pi represents the probability of the C / I value in the i-th interval. Calculate the probability , the expression is: ,For the discretized probability distribution of C / I signal, calculate the entropy H of C / I signal: ;in: is the probability of the ith interval, and the inter-carrier interference ratio fluctuation index is calculated. The expression is: ; Where BK is the inter-carrier interference ratio fluctuation index, ΔH is the difference in entropy values ​​of the C / I signal in different time periods, is the entropy value in the reference state.

4. The satellite communication-based emergency command method according to claim 3, characterized in that: The phase noise increase anomaly index and the inter-carrier interference ratio fluctuation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as the input of the machine learning model. The machine learning model uses the probability analysis value label of the satellite signal distortion predicted by each group of comprehensive feature vectors as the prediction target, and takes minimizing the sum of the prediction errors of the probability analysis value labels of all satellite signals with distortion as the training target. The machine learning model is trained until the sum of the prediction errors converges, and the model training is stopped. The probability analysis value of the satellite signal distortion is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

5. The satellite communication-based emergency command method according to claim 4, characterized in that: The acquired probability analysis value of the satellite signal distortion is compared with the preset probability analysis value reference threshold. If the probability analysis value of the satellite signal distortion is greater than or equal to the preset probability analysis value reference threshold, it is classified as the satellite signal distortion; if the probability analysis value of the satellite signal distortion is less than the preset probability analysis value reference threshold, it is classified as the satellite signal non-distortion.

6. The satellite communication-based emergency command method according to claim 1, characterized in that: In S5, the satellite communication link monitoring system first monitors the quality of the satellite signal in real time. When the signal quality is lower than the set threshold, it automatically triggers the switching mechanism of the backup satellite communication channel or the backup channel; and gradually reduces the data transmission load of the main channel. After switching to the backup channel, the system continues to monitor the signal quality of the backup channel and predicts the long-term performance of the backup channel. The use priority of the backup channel is adjusted according to the prediction results. Once the signal quality of the main channel recovers to the predetermined available range, the system will automatically switch back to the main channel.

7. An emergency command system based on satellite communication, used to implement an emergency command method based on satellite communication according to any one of claims 1 to 6, characterized in that: It includes data acquisition module, communication and decision-making module, monitoring and analysis module, management module and fault-tolerant processing module; Data collection module: When an emergency occurs, it obtains real-time on-site information of the disaster area through the satellite communication network, including geographic location, disaster assessment and resource demand data; Communication and decision-making module: Use satellite communication channels to transmit on-site information from disaster areas to the emergency command center. At the emergency command center, dynamic command decisions are made based on real-time data from satellite signals to optimize resource allocation and emergency response strategies. Monitoring and analysis module: During the satellite signal transmission process, real-time monitoring and analysis of the satellite signal’s phase noise level and the satellite signal’s inter-carrier interference ratio are performed to determine whether the satellite signal is distorted; Management module: When satellite signals are distorted, it automatically switches to the backup satellite communication channel to supplement information transmission, ensuring smooth information flow and continuous operation of the command system; Fault-tolerant processing module: Utilize the satellite communication link monitoring system to monitor and adjust the quality of satellite signals in real time, and automatically perform fault-tolerant processing to avoid command system failure due to communication interruption.

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