Emergency communication and positioning system and method based on Beidou satellite

Abstract

The present invention discloses an emergency communication and positioning system and method based on Beidou satellites, comprising the following steps: S1, real-time data collection; S2, analyzing the user's emergency status using a context-aware algorithm; S3, transmitting emergency information to a rescue center according to a calculated priority when the satellite communication signal is stable; if the satellite signal is unstable or interrupted, establishing a self-organizing network to continue transmitting emergency information; S4, dynamically selecting the optimal path based on an adaptive path optimization algorithm inspired by the immune system, and further optimizing the path selection using a spatiotemporal perception algorithm; S5, prioritizing high-priority emergency information based on a priority management mechanism and sending feedback information; S6, if the first emergency information transmission fails, the system activates a redundant data transmission mechanism; S7, continuously tracking changes in the user's status and dynamically adjusting the rescue plan. The present invention combines context-awareness with the immune system optimization algorithm to achieve efficient transmission and feedback of emergency information.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication and emergency positioning technology, and in particular to an emergency communication and positioning system and method based on Beidou satellites. Background Art

[0002] Traditional emergency communication systems mostly rely on a single satellite or terrestrial communication network, which exhibits significant limitations in certain extreme situations. For example, when communication infrastructure is damaged or coverage is insufficient during a disaster, the system's communication link is easily interrupted, resulting in the inability to transmit information in a timely manner. Furthermore, existing systems typically only support one-way communication. Users can send distress signals but cannot receive feedback from the rescue center. This lacks interactivity during the rescue process, reducing users' sense of security and rescue efficiency. This is especially true in natural disasters or in remote areas far from communication infrastructure. Users lack timely feedback and assistance, seriously affecting rescue efficiency and accuracy.

[0003] Another common problem is that existing systems lack effective information priority management mechanisms when dealing with multiple emergency events or users, making it impossible to dynamically allocate communication resources based on the urgency of the event. This "one-size-fits-all" approach results in all messages being treated with the same priority. Even in situations of limited resources or information overload, it fails to ensure that the most important emergency messages are transmitted first, thus delaying rescue operations. This is especially true at disaster sites, where numerous users may simultaneously flood in distress messages. Traditional communication systems struggle to quickly distinguish and process these messages based on their urgency.

[0004] Furthermore, traditional emergency communication systems rely on fixed transmission paths when faced with unstable communication links. If a path fails, information is lost or transmission fails, lacking redundant transmission mechanisms. In emergency scenarios, information transmission reliability is crucial; a single transmission failure can mean the loss of a valuable rescue opportunity. Existing emergency communication systems lack a comprehensive solution in this regard. Most systems rely solely on a single link for transmission, failing to fully utilize collaborative communication across multiple paths or devices.

[0005] Existing emergency communication equipment generally relies on a single communication technology, such as long-distance communication using satellite signals or short-range wireless network transmission, and lacks the ability to combine multiple communication methods to cope with complex environments. For example, when satellite signals are interfered with, geographically blocked, or affected by weather, it is difficult for the equipment to automatically switch to other communication methods for information transmission, increasing the risk of communication interruption. In some disaster scenarios, due to remote locations or extreme climates, satellite signals may be blocked or interrupted, and the equipment cannot quickly establish a self-organizing network through other devices or short-range wireless networks to continue communication.

[0006] Furthermore, current path optimization technology has limited application in emergency communications. While widely used in the internet and other communications fields, in emergency communications scenarios, traditional fixed path selection methods struggle to adapt to the complex demands of these communications due to the dynamic nature of network and device status. In extreme environments, the power level, signal strength, and load of node devices can fluctuate rapidly, making it difficult for traditional path optimization algorithms to adjust transmission paths in real time. This results in inefficient information transmission and can even lead to transmission failures. Traditional systems lack intelligent adjustment mechanisms to handle the dynamic nature of node devices and are unable to dynamically select the optimal transmission path based on the actual node status.

[0007] To improve transmission reliability and efficiency, redundant transmission mechanisms are essential. However, most existing emergency communication systems lack multi-path or multi-node redundant transmission mechanisms, resulting in complete failure of information transmission if the communication link is interrupted. Redundancy mechanisms automatically enable backup paths or nodes for information transmission when the primary transmission link fails, ensuring that emergency information can successfully reach the rescue center even in the most adverse conditions.

[0008] Therefore, how to provide an emergency communication and positioning system and method based on Beidou satellites is an urgent problem that needs to be solved by those skilled in the art. Summary of the Invention

[0009] One purpose of the present invention is to propose an emergency communication and positioning system and method based on Beidou satellites. This invention combines multimodal sensing technology, context-aware algorithms, and an adaptive path optimization method inspired by the immune system to construct an emergency communication and positioning system based on Beidou satellites. Through dynamic prioritization, a two-way communication feedback mechanism, and a redundant transmission mechanism combining satellite and short-range wireless communications, the system can achieve efficient transmission of emergency information and rescue feedback in complex or extreme environments. This invention offers the advantages of high communication reliability, fast information transmission efficiency, flexible path selection, and timely rescue response, making it particularly suitable for disaster emergency response and remote rescue scenarios.

[0010] The Beidou satellite-based emergency communication and positioning method according to an embodiment of the present invention includes the following steps:

[0011] S1. Monitor the user's physical condition and environmental data through multimodal sensors on the user's device, collecting the user's physical movement, health status and environmental parameters in real time;

[0012] S2. Analyze the user's emergency status using a context-aware algorithm based on the collected multimodal sensor data. When an abnormal situation is detected or the user actively sends a distress signal, the system initiates emergency information processing and uses a priority calculation engine to classify emergency information into high, medium, and low priority levels based on the degree of urgency.

[0013] S3. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority. If the Beidou satellite signal is unstable or interrupted, the user device will automatically search for other nearby devices through the short-range wireless communication protocol, build a self-organizing network, and continue to transmit the emergency information;

[0014] S4, an adaptive path optimization algorithm inspired by the immune system, dynamically selects the optimal path based on the power, signal strength, and load of intelligent node devices in the self-organizing network. It also uses a spatiotemporal perception algorithm to predict the movement path and state changes of devices to further optimize path selection.

[0015] S5. After receiving the emergency information, the rescue center will prioritize high-priority emergency information according to the priority management mechanism and send feedback information to the user equipment through the reverse link of the Beidou satellite;

[0016] S6. During the communication process, if the first transmission of the emergency information fails, the system activates the redundant data transmission mechanism and transmits the information again using other paths or nodes until the rescue center confirms receipt of the emergency information;

[0017] S7. The rescue center continuously tracks the user's status changes based on the real-time data uploaded by the user's device and dynamically adjusts the rescue plan.

[0018] Optionally, the S2 specifically includes:

[0019] S21. The context awareness algorithm calculates the user's emergency index F(t) by performing real-time analysis on multimodal sensor data:

[0020]

[0021] Among them, A 加速度 (t) represents the user’s acceleration data, H 心率 (t) represents the user’s heart rate data, P 气压 (t) represents the ambient air pressure data, T 温度 (t) represents the ambient temperature, β1, β2, β3 and β4 represent nonlinear adjustment factors, λ represents the time decay factor, G 环境 (t) represents the global environment correction factor;

[0022] S22, the situational awareness algorithm dynamically adjusts the sensor data in combination with external conditions to determine whether the user is in an emergency state. When the emergency state index F(t) exceeds the preset threshold F threshold When the system determines that the user is in an emergency state, it starts the emergency information processing process;

[0023] S23. The specific emergency levels are:

[0024]

[0025] Among them, F high represents the high priority threshold, F medium Indicates the medium priority threshold;

[0026] When F(t)>F high When , it means the user is in an extremely dangerous state;

[0027] When F medium ≤F(t)≤F high When , it means the user is in a potentially dangerous state;

[0028] When F(t) <F medium When , it means the user status is relatively safe and the status information needs to be updated regularly;

[0029] S24, the situational awareness algorithm dynamically prioritizes emergency information based on sensor data and the calculated emergency index F(t), and adjusts the information transmission path and strategy based on the priority;

[0030] S25. After the emergency status analysis is completed, the system enters the corresponding emergency information processing and transmission process based on the priority of the emergency status index.

[0031] Optionally, the S3 specifically includes:

[0032] S31. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority, wherein the emergency information includes the user's real-time location information, emergency status index, sensor data, and the unique identifier of the user device;

[0033] S32. Emergency information is transmitted in the form of data packets, and the data packet size P(t) is dynamically calculated:

[0034]

[0035] Where F(t) represents the emergency index, Pri(t) represents the information priority, E(t) represents the power of the node device, S(t) represents the signal strength of the node device, α represents the proportional constant, and α1, α2, and α3 represent nonlinear adjustment factors;

[0036] S33. When the Beidou satellite signal is unstable or interrupted, the user equipment detects the current communication environment and automatically starts the short-range wireless communication protocol for local communication and information transmission;

[0037] S34. The user device automatically searches for other nearby devices through a short-range wireless communication protocol and connects them to form a self-organizing network. The self-organizing network is used to relay emergency information transmission. During the transmission process, the power E(t), signal strength S(t), and current load B(t) of the node device are taken into consideration.

[0038] S35. Each device acts as a network node, and the probability P of the node device participating in the communication node (t) is:

[0039]

[0040] Among them, γ1, γ2 and γ3 represent nonlinear adjustment factors.

[0041] Optionally, the S4 specifically includes:

[0042] S41. In a short-range wireless communication environment, the system uses an adaptive path optimization algorithm inspired by the immune system to select the optimal path and combines it with a spatiotemporal perception algorithm to evaluate the dynamic state of nodes:

[0043]

[0044] Among them, P opt (t) represents the optimal transmission path at the current time t, n represents the total number of nodes participating in the transmission, S i (t) represents the signal strength of the i-th node, B i (t) The current load of the i-th node, E i (t) represents the power of the i-th node, D i (t) represents the transmission delay of the i-th node, τ represents the spatiotemporal perception adjustment factor, P 预测 (t) represents the predicted location of the node at a certain moment in the future, L max (t) represents the maximum load value allowed in the current network, T max (t) represents the maximum allowed delay value in the current network;

[0045] S42, the spatiotemporal perception algorithm combines the movement trajectory, speed and direction information of each node to predict the spatial position P of the node at the future time 预测 (t):

[0046]

[0047] Among them, P 当前(t) represents the current position information of the node, V(t) represents the current velocity of the node, A(t) represents the acceleration of the node, and Δt represents the time step;

[0048] S43. The system uses an adaptive path optimization algorithm inspired by the immune system to adjust the node selection in the transmission path in real time. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes nodes that are not suitable for continued participation in the transmission and selects a new optimal path.

[0049] S44. If a node loses communication due to power exhaustion or out of network coverage during the transmission process, the system will automatically enable the backup path, continue to transmit the emergency information through other nodes, and reselect the optimal path based on the spatiotemporal status of the remaining nodes.

[0050] Optionally, the S42 specifically includes:

[0051] S421, the node is designed as an antibody model, and the state of each node i is measured by the antibody fitness A i (t) means:

[0052]

[0053] Among them, A i (t) represents the antibody fitness of node i at time t, G 环境 (t) represents the environmental correction factor, μ1, μ2, μ3, μ4 and μ5 represent nonlinear adjustment factors;

[0054] S422. Emergency information is designed as an antigen model to calculate the urgency Ur(t):

[0055]

[0056] Among them, G 紧急环境 (t) represents the correction factor of the current environment of the emergency task, F(t) represents the emergency state index, and Pri(t) represents the information priority;

[0057] S423. Calculate antibody A i The matching degree between (t) and antigen Ur(t) is used to measure the adaptability of the node to emergency information:

[0058]

[0059] Among them, M i (t) represents the matching degree of node i to the emergency information;

[0060] S424, when the node's matching degree M i (t) exceeds the set threshold M max When the node participates in information transmission first, if the matching degree is lower than the threshold Mmin , then the node is excluded from the transmission path;

[0061] S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism:

[0062]

[0063] in, represents the antibody fitness of node i after concentration adjustment, ρ i (t) represents the frequency of node participation in the transmission task. The higher the frequency, the lower the fitness after adjustment.

[0064] S426, immune memory mechanism is used to record the nodes with higher fitness in history, and give priority to nodes with higher fitness to participate in similar tasks in the future, and update the memory fitness A 记忆 (t):

[0065] A 记忆 (t)=(1-θ)·A 记忆 (t-Δt)+θ·A i (t);

[0066] Where θ represents the memory decay factor and Δt represents the time step.

[0067] Optionally, the S6 specifically includes:

[0068] S61. When the user device sends an emergency message to the rescue center via BeiDou satellite or self-organizing network, if the transmission fails, the system automatically records the failure time T fail (t);

[0069] S62: Optimize the transmission cost P of the backup path 冗余 (t):

[0070]

[0071] Among them, F fail (t) represents the number of historical transmission failures on the path. The higher the number, the higher the path cost. i (t) represents the dynamic adjustment factor of node i, n represents the total number of nodes participating in the transmission, S i (t) represents the signal strength of the i-th node, B i (t) The current load of the i-th node, E i (t) represents the power of the i-th node;

[0072] S63. If the backup path still fails to transmit information successfully, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate P 成功 (t):

[0073]

[0074] Among them, C 拥塞 (t) represents the congestion level of the network where the node is located. The higher the congestion level, the lower the transmission success rate. τ(t) represents the time impact of the current transmission task. F(t) represents the emergency index. Pri(t) represents the information priority.

[0075] S64. The system monitors the status of each node participating in parallel transmission in real time and dynamically adjusts the number of participating nodes based on the actual transmission results. When the transmission failure rate of a node increases, the system automatically reduces the priority of the node participating in parallel transmission until the node status returns to normal.

[0076] S65. The system designs a local caching mechanism. After a transmission failure, the device caches the emergency information in local storage and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status:

[0077]

[0078] Among them, T 重传 (t) represents the time interval for the device to retransmit after failure, represents the regulating factor;

[0079] S66. After confirming that the rescue center has received the transmitted data, the system automatically clears the local cache information of the device and records the successful transmission time T 成功 (t).

[0080] The Beidou satellite-based emergency communication and positioning system according to an embodiment of the present invention includes the following modules:

[0081] Multimodal sensor module for real-time collection of user's body movement, health status and environmental parameters;

[0082] A situational awareness module, which analyzes multimodal sensor data, determines emergency situations, and processes emergency information based on priority classification;

[0083] The communication module transmits emergency information via satellite when the Beidou satellite signal is stable, and transmits it via short-range wireless communication when the signal is interrupted;

[0084] Path optimization module, based on immune system-inspired algorithms and spatiotemporal perception technology, dynamically selects and optimizes information transmission paths;

[0085] The feedback module is used to send confirmation feedback to the user equipment through the Beidou satellite reverse link after the rescue center receives the emergency information;

[0086] A redundant transmission module is used to use a backup path or node for redundant data transmission when the first transmission fails until the information is successfully transmitted;

[0087] The rescue dispatch module is used by the rescue center to track user status based on real-time data and dynamically adjust the rescue plan.

[0088] The beneficial effects of the present invention are:

[0089] First, through the application of multimodal sensors, the present invention enables the system to collect the user's physical condition and environmental parameters in real time, including acceleration, heart rate, air pressure, temperature and other data sources, providing a comprehensive information basis for the situational awareness algorithm. This enables the system to more accurately determine whether the user is in an emergency state and dynamically calculate the user's emergency state index to ensure that the distress signal is activated in an emergency in a timely manner. Compared with traditional emergency systems that rely on a single sensor or manually trigger distress signals, the present invention significantly improves the automatic identification and response capabilities of emergencies and greatly shortens reaction time.

[0090] Secondly, this invention uses a priority calculation engine to categorize information into high, medium, and low priorities based on urgency, ensuring that the most critical information is processed and transmitted first in emergencies. This addresses the problem of inadequate information priority management in traditional systems. When information is overloaded at a disaster site, it effectively distinguishes the importance of information, ensuring that the most urgent rescue needs receive a timely response. This dynamic priority allocation mechanism improves the system's communication efficiency within limited resources, optimizes the use of information transmission paths, and avoids communication congestion and resource waste.

[0091] When it comes to communication path selection, traditional systems rely solely on fixed transmission paths and are unable to adapt to changes in node status. However, this invention introduces an adaptive path optimization algorithm inspired by the immune system, which can adjust the transmission path in real time based on the power level, signal strength, and current load of the node device, ensuring the efficiency and stability of the communication link. At the same time, the spatiotemporal perception algorithm further predicts the movement path and state changes of the device, thereby planning the optimal communication path in advance and avoiding node failures or network interruptions. This path optimization mechanism significantly improves the flexibility and adaptability of transmission, ensuring smooth information transmission even in complex and dynamic environments.

[0092] Furthermore, the present invention combines satellite communication with short-range wireless communication technologies. When the Beidou satellite signal becomes unstable or interrupted, the system automatically forms a self-organizing network using the short-range wireless communication protocol to continue transmitting emergency information, ensuring a smooth communication link in any environment. This multi-mode communication design significantly enhances the system's robustness and coverage, overcoming the limitations of existing technologies such as the vulnerability of satellite signals to interruption. This allows the system to remain effective in remote areas or at disaster sites with damaged infrastructure.

[0093] The introduction of a redundant data transmission mechanism further enhances the reliability of information transmission. In the event of a communication failure, the system automatically activates a backup path or node, leveraging redundancy to ensure that information is ultimately transmitted to the rescue center. This design avoids information loss due to failure of a single communication path and improves the success rate of information transmission. This ensures the reliability of emergency information transmission, especially in complex and unstable network environments, preventing precious rescue opportunities from being missed due to transmission failures.

[0094] Finally, the present invention incorporates a two-way communication feedback mechanism. After receiving emergency information, the rescue center can promptly send feedback to the user's device via the Beidou satellite's reverse link, informing them of the rescue progress or providing self-rescue advice. Compared to existing one-way communication systems, this design significantly enhances users' sense of security and information transparency, allowing them to receive timely feedback while awaiting rescue, reducing uncertainty, improving the efficiency of rescue operations, and increasing the user's chance of survival. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0096] Figure 1 This is an overall flow chart of the Beidou satellite-based emergency communication and positioning method proposed by the present invention;

[0097] Figure 2 This is a structural diagram of the Beidou satellite-based emergency communication and positioning system proposed by the present invention. DETAILED DESCRIPTION

[0098] The present invention will now be described in further detail with reference to the accompanying drawings, which are simplified schematic diagrams that illustrate the basic structure of the present invention in a schematic manner.

[0099] refer to Figure 1 , an emergency communication and positioning method based on Beidou satellite, comprising the following steps:

[0100] S1. Monitor the user's physical condition and environmental data through multimodal sensors on the user's device, collecting the user's physical movement, health status and environmental parameters in real time;

[0101] S2. Analyze the user's emergency status using a context-aware algorithm based on the collected multimodal sensor data. When an abnormal situation is detected or the user actively sends a distress signal, the system initiates emergency information processing and uses a priority calculation engine to classify emergency information into high, medium, and low priority levels based on the degree of urgency.

[0102] S3. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority. If the Beidou satellite signal is unstable or interrupted, the user device will automatically search for other nearby devices through the short-range wireless communication protocol, build a self-organizing network, and continue to transmit the emergency information;

[0103] S4, an adaptive path optimization algorithm inspired by the immune system, dynamically selects the optimal path based on the power, signal strength, and load of intelligent node devices in the self-organizing network. It also uses a spatiotemporal perception algorithm to predict the movement path and state changes of devices to further optimize path selection.

[0104] S5. After receiving the emergency information, the rescue center will prioritize high-priority emergency information according to the priority management mechanism and send feedback information to the user equipment through the reverse link of the Beidou satellite;

[0105] S6. During the communication process, if the first transmission of the emergency information fails, the system activates the redundant data transmission mechanism and transmits the information again using other paths or nodes until the rescue center confirms receipt of the emergency information;

[0106] S7. The rescue center continuously tracks the user's status changes based on the real-time data uploaded by the user's device and dynamically adjusts the rescue plan.

[0107] In this embodiment, S2 specifically includes:

[0108] S21. The context awareness algorithm calculates the user's emergency index F(t) by performing real-time analysis on multimodal sensor data:

[0109]

[0110] Among them, A 加速度 (t) represents the user’s acceleration data, H 心率 (t) represents the user’s heart rate data, P 气压 (t) represents the ambient air pressure data, T 温度(t) represents the ambient temperature, β1, β2, β3 and β4 represent nonlinear adjustment factors, λ represents the time decay factor, G 环境 (t) represents the global environment correction factor;

[0111] S22, the situational awareness algorithm dynamically adjusts the sensor data in combination with external conditions to determine whether the user is in an emergency state. When the emergency state index F(t) exceeds the preset threshold F threshold When the system determines that the user is in an emergency state, it starts the emergency information processing process;

[0112] S23. The specific emergency levels are:

[0113]

[0114] Among them, F high represents the high priority threshold, F medium Indicates the medium priority threshold;

[0115] When F(t)>F high When , it means the user is in an extremely dangerous state;

[0116] When F medium ≤F(t)≤F high When , it means the user is in a potentially dangerous state;

[0117] When F(t) <F medium When , it means the user status is relatively safe and the status information needs to be updated regularly;

[0118] S24, the situational awareness algorithm dynamically prioritizes emergency information based on sensor data and the calculated emergency index F(t), and adjusts the information transmission path and strategy based on the priority;

[0119] S25. After the emergency status analysis is completed, the system enters the corresponding emergency information processing and transmission process based on the priority of the emergency status index.

[0120] In this embodiment, S3 specifically includes:

[0121] S31. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority, wherein the emergency information includes the user's real-time location information, emergency status index, sensor data, and the unique identifier of the user device;

[0122] S32. Emergency information is transmitted in the form of data packets, and the data packet size P(t) is dynamically calculated:

[0123]

[0124] Where F(t) represents the emergency index, Pri(t) represents the information priority, E(t) represents the power of the node device, S(t) represents the signal strength of the node device, α represents the proportional constant, and α1, α2, and α3 represent nonlinear adjustment factors;

[0125] S33. When the Beidou satellite signal is unstable or interrupted, the user equipment detects the current communication environment and automatically starts the short-range wireless communication protocol for local communication and information transmission;

[0126] S34. The user device automatically searches for other nearby devices through a short-range wireless communication protocol and connects them to form a self-organizing network. The self-organizing network is used to relay emergency information transmission. During the transmission process, the power E(t), signal strength S(t), and current load B(t) of the node device are taken into consideration.

[0127] S35. Each device acts as a network node, and the probability P of the node device participating in the communication node (t) is:

[0128]

[0129] Among them, γ1, γ2 and γ3 represent nonlinear adjustment factors.

[0130] In this embodiment, the S4 specifically includes:

[0131] S41. In a short-range wireless communication environment, the system uses an adaptive path optimization algorithm inspired by the immune system to select the optimal path and combines it with a spatiotemporal perception algorithm to evaluate the dynamic state of nodes:

[0132]

[0133] Among them, P opt (t) represents the optimal transmission path at the current time t, n represents the total number of nodes participating in the transmission, S i (t) represents the signal strength of the i-th node, B i (t) The current load of the i-th node, E i (t) represents the power of the i-th node, D i (t) represents the transmission delay of the i-th node, τ represents the spatiotemporal perception adjustment factor, P 预测 (t) represents the predicted location of the node at a certain moment in the future, L max (t) represents the maximum load value allowed in the current network, T max (t) represents the maximum allowed delay value in the current network;

[0134] S42, the spatiotemporal perception algorithm combines the movement trajectory, speed and direction information of each node to predict the spatial position P of the node at the future time预测 (t):

[0135]

[0136] Among them, P 当前 (t) represents the current position information of the node, V(t) represents the current velocity of the node, A(t) represents the acceleration of the node, and Δt represents the time step;

[0137] S43. The system uses an adaptive path optimization algorithm inspired by the immune system to adjust the node selection in the transmission path in real time. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes nodes that are not suitable for continued participation in the transmission and selects a new optimal path.

[0138] S44. If a node loses communication due to power exhaustion or out of network coverage during the transmission process, the system will automatically enable the backup path, continue to transmit the emergency information through other nodes, and reselect the optimal path based on the spatiotemporal status of the remaining nodes.

[0139] In this embodiment, the S42 specifically includes:

[0140] S421, the node is designed as an antibody model, and the state of each node i is measured by the antibody fitness A i (t) means:

[0141]

[0142] Among them, A i (t) represents the antibody fitness of node i at time t, G 环境 (t) represents the environmental correction factor, μ1, μ2, μ3, μ4 and μ5 represent nonlinear adjustment factors;

[0143] S422. Emergency information is designed as an antigen model to calculate the urgency Ur(t):

[0144]

[0145] Among them, G 紧急环境 (t) represents the correction factor of the current environment of the emergency task, F(t) represents the emergency state index, and Pri(t) represents the information priority;

[0146] S423, calculate antibody A i The matching degree between (t) and antigen Ur(t) is used to measure the adaptability of the node to emergency information:

[0147]

[0148] Among them, M i(t) represents the matching degree of node i to the emergency information;

[0149] S424, when the node's matching degree M i (t) exceeds the set threshold M max When the node participates in information transmission first, if the matching degree is lower than the threshold M min , then the node is excluded from the transmission path;

[0150] S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism:

[0151]

[0152] in, represents the antibody fitness of node i after concentration adjustment, ρ i (t) represents the frequency of node participation in the transmission task. The higher the frequency, the lower the fitness after adjustment.

[0153] S426, immune memory mechanism is used to record the nodes with higher fitness in history, and give priority to nodes with higher fitness to participate in similar tasks in the future, and update the memory fitness A 记忆 (t):

[0154] A 记忆 (t)=(1-θ)·A 记忆 (t-Δt)+θ·A i (t);

[0155] Where θ represents the memory decay factor and Δt represents the time step.

[0156] In this embodiment, S6 specifically includes:

[0157] S61. When the user device sends an emergency message to the rescue center via BeiDou satellite or self-organizing network, if the transmission fails, the system automatically records the failure time T fail (t);

[0158] S62: Optimize the transmission cost P of the backup path 冗余 (t):

[0159]

[0160] Among them, F fail (t) represents the number of historical transmission failures on the path. The higher the number, the higher the path cost. i (t) represents the dynamic adjustment factor of node i, n represents the total number of nodes participating in the transmission, S i (t) represents the signal strength of the i-th node, B i (t) The current load of the i-th node, Ei (t) represents the power of the i-th node;

[0161] S63. If the backup path still fails to transmit information successfully, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate P 成功 (t):

[0162]

[0163] Among them, C 拥塞 (t) represents the congestion level of the network where the node is located. The higher the congestion level, the lower the transmission success rate. τ(t) represents the time impact of the current transmission task. F(t) represents the emergency index. Pri(t) represents the information priority.

[0164] S64. The system monitors the status of each node participating in parallel transmission in real time and dynamically adjusts the number of participating nodes based on the actual transmission results. When the transmission failure rate of a node increases, the system automatically reduces the priority of the node participating in parallel transmission until the node status returns to normal.

[0165] S65. The system designs a local caching mechanism. After a transmission failure, the device caches the emergency information in local storage and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status:

[0166]

[0167] Among them, T 重传 (t) represents the time interval for the device to retransmit after failure, represents the regulating factor;

[0168] S66. After confirming that the rescue center has received the transmitted data, the system automatically clears the local cache information of the device and records the successful transmission time T 成功 (t).

[0169] refer to Figure 2 , the BeiDou satellite-based emergency communication and positioning system includes the following modules:

[0170] Multimodal sensor module for real-time collection of user's body movement, health status and environmental parameters;

[0171] A situational awareness module, which analyzes multimodal sensor data, determines emergency situations, and processes emergency information based on priority classification;

[0172] The communication module transmits emergency information via satellite when the Beidou satellite signal is stable, and transmits it via short-range wireless communication when the signal is interrupted;

[0173] Path optimization module, based on immune system-inspired algorithms and spatiotemporal perception technology, dynamically selects and optimizes information transmission paths;

[0174] The feedback module is used to send confirmation feedback to the user equipment through the Beidou satellite reverse link after the rescue center receives the emergency information;

[0175] A redundant transmission module is used to use a backup path or node for redundant data transmission when the first transmission fails until the information is successfully transmitted;

[0176] The rescue dispatch module is used by the rescue center to track user status based on real-time data and dynamically adjust the rescue plan.

[0177] Example 1:

[0178] In order to verify the feasibility of the present invention in implementation, the present invention is applied to natural disaster rescue in mountainous areas.

[0179] In July of a certain year, continuous heavy rains triggered a large-scale landslide in the mountainous area of ​​M City, H Province, resulting in some mountain villages being buried by mud and rock flows and serious damage to the communication infrastructure. After the disaster, multiple rescue teams were quickly dispatched to the affected area to carry out rescue missions. Due to the damage to the local signal tower, satellite communication became the only available communication method. However, the complex terrain and severe weather in the mountainous area caused the satellite signal to be unstable in some areas, which greatly affected the communication between the rescue workers and the command center. A more stable and efficient communication method was urgently needed to ensure the smooth progress of the rescue work. The Beidou satellite-based emergency communication and positioning system of the present invention has been applied.

[0180] First, the devices worn by rescuers are equipped with multimodal sensors to monitor their physical condition and environmental data. These sensors collect real-time data such as the rescuer's movement, heart rate, and ambient temperature. Using context-aware algorithms, these data are analyzed to determine whether the rescuer is in danger. Due to the complex terrain in the debris flow area, rescuers may face unexpected situations at any time, such as slips, falls, or becoming trapped. By monitoring this real-time sensor data, the system can promptly detect any abnormalities in the rescuer's condition, activate the emergency information transmission mechanism, and prioritize information based on its urgency.

[0181] During the actual rescue process, three rescuers entered an area with extremely unstable signals, and traditional satellite communications could not maintain a stable connection. In this case, the system first determined that the Beidou satellite communication signal was unstable and automatically switched to short-range wireless communication mode. The rescue equipment formed a network with the equipment of other nearby rescuers through the short-range wireless communication protocol, and relayed the emergency information to the area where the satellite signal could be received through multi-hop transmission. During a certain operation, a rescuer accidentally slipped and the device in the backpack detected his fall. It also determined that he might be injured based on abnormal data from the acceleration sensor and heart rate sensor. The system automatically classified the information as high-priority information and transmitted it to the device that could communicate with the satellite through the self-organizing network, and finally successfully transmitted the distress message to the command center.

[0182] Through this system, the command center not only received the rescue workers' distress signals but also provided real-time feedback to them via the BeiDou satellite reverse link, informing them that the rescue team was en route and providing them with temporary self-rescue guidance. This two-way communication significantly alleviated the anxiety of the rescue workers while they waited, while also ensuring the efficient execution of the rescue plan.

[0183] Throughout the rescue process, the immune system-inspired adaptive path optimization algorithm of the present invention played an important role. Due to the complex terrain of mountainous areas and the limited power of equipment, the system analyzes the signal strength, load conditions, and power of each device in real time, and selects the optimal transmission path based on the dynamic state of the node. For example, during a certain information transmission process, some rescuers' devices exited the self-organizing network due to insufficient power. The system immediately recalculated the path and excluded these devices to ensure the stability and efficiency of data transmission. Ultimately, through the combination of multi-hop transmission, path optimization, and redundancy mechanisms, all important information was successfully transmitted to the rescue center within the specified time.

[0184] Table 1 Comparison data between the system of the present invention and the traditional satellite communication system

[0185]

[0186]

[0187] Table 1 compares in detail the performance of the Beidou satellite-based emergency communication and positioning system and the traditional satellite communication system in multiple key indicators, and demonstrates the superiority of the present invention in emergency rescue through specific data.

[0188] First, the system of the present invention significantly outperforms traditional systems in terms of emergency information processing time. The system can initiate the emergency information processing process in 0.95 seconds and complete the transmission of high-priority information in 9.87 seconds. Traditional satellite communication systems, on the other hand, are relatively slow in this process, with a startup time of approximately 62.4 seconds and a total transmission time of over 60 seconds. Fast response time is crucial for emergency rescue, and the system of the present invention significantly shortens this time by optimizing the startup and transmission processes, greatly improving rescue efficiency.

[0189] Regarding information transmission latency, the path optimization algorithm of this invention reduces the average latency by 17.8%, from the traditional 54.3 milliseconds to 44.6 milliseconds. In comparison, traditional satellite communication systems exhibit unstable latency, with an average latency of 61.2 milliseconds. In rescue scenarios, reducing information transmission latency can speed up the delivery of emergency information to the command center, ensuring timely rescue decisions.

[0190] Another indicator of the present invention's advantages is its transmission success rate. In complex terrain and harsh environments, the present invention achieved a transmission success rate of 95.8%, significantly higher than the 70.9% of conventional satellite communication systems. This advantage is due to the present invention's redundant transmission mechanism and path optimization technology, which enables the successful transmission of urgent information even in unstable signal conditions.

[0191] The present invention also demonstrates significant advantages in response time. Through two-way communication, the command center can provide feedback within 25.4 seconds, compared to an average of 80.7 seconds for traditional satellite communication systems. This difference is crucial for providing psychological support and operational control to rescuers, as rapid feedback significantly improves the coordination and timeliness of rescue efforts.

[0192] Communication interruptions are also a significant shortcoming of traditional systems. During the rescue process, the present invention successfully avoided five information transmission interruptions, while traditional systems experienced an average of 3.7 interruptions per hour. By utilizing a self-organizing network and redundant transmission mechanisms, the present invention effectively reduces the risk of communication interruptions and ensures the continuity and reliability of information transmission.

[0193] Finally, regarding device power consumption, the present invention reduced power consumption by an average of 18.4% by optimizing communication paths and reducing unnecessary communication operations, extending device battery life by 2.6 hours. Traditional systems, however, suffer from frequent communication interruptions and poor path selection, leading to rapid device power consumption and a reduction in battery life of 1.9 hours. During prolonged rescue operations, device battery life directly impacts the continuity of rescue efforts, making this aspect of optimization particularly crucial.

[0194] In summary, the Beidou satellite-based emergency communication and positioning system significantly outperforms traditional satellite communication systems across all key metrics, particularly in emergency information processing time, transmission success rate, feedback response time, and power management. This invention utilizes multimodal sensing, path optimization, and redundant transmission technologies to effectively enhance the system's performance in complex rescue scenarios, ensuring rapid and reliable information transmission and two-way feedback.

[0195] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. The emergency communication and positioning method based on Beidou satellite is characterized in that: The steps include: S1. Monitor the user's physical condition and environmental data through multimodal sensors on the user's device, collecting the user's physical movement, health status and environmental parameters in real time; S2. Analyze the user's emergency status using a context-aware algorithm based on the collected multimodal sensor data. When an abnormal situation is detected or the user actively sends a distress signal, the system initiates emergency information processing and uses a priority calculation engine to classify emergency information into high, medium, and low priority levels based on the degree of urgency. S3. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority. If the Beidou satellite signal is unstable or interrupted, the user device will automatically search for other nearby devices through the short-range wireless communication protocol, build a self-organizing network, and continue to transmit the emergency information; S4, an adaptive path optimization algorithm inspired by the immune system, dynamically selects the optimal path based on the power, signal strength, and load of intelligent node devices in the self-organizing network. It also uses a spatiotemporal perception algorithm to predict the movement path and state changes of devices to further optimize path selection. S5. After receiving the emergency information, the rescue center will prioritize high-priority emergency information according to the priority management mechanism and send feedback information to the user equipment through the reverse link of the Beidou satellite; S6. During the communication process, if the first transmission of the emergency information fails, the system activates the redundant data transmission mechanism and transmits the information again using other paths or nodes until the rescue center confirms receipt of the emergency information; S7. The rescue center continuously tracks the user's status changes based on the real-time data uploaded by the user's device and dynamically adjusts the rescue plan; The S4 specifically includes: S41. In a short-range wireless communication environment, the system uses an adaptive path optimization algorithm inspired by the immune system to select the optimal path and combines it with a spatiotemporal perception algorithm to evaluate the dynamic state of nodes: ； in, Indicates the current time The optimal transmission path, Indicates the total number of nodes participating in the transmission, Indicates the The signal strength of each node, No. The current load of the nodes, Indicates the The power of each node, Indicates the The transmission delay of each node, represents the spatiotemporal perception adjustment factor, Represents the predicted location of the node at a certain moment in the future, Indicates the maximum load value allowed in the current network. Indicates the maximum allowed delay value in the current network; S42, the spatiotemporal perception algorithm combines the movement trajectory, speed and direction information of each node to predict the spatial position of the node at the future moment : ； in, Indicates the current location information of the node. Indicates the current speed of the node, represents the acceleration of the node, represents the time step; S43. The system uses an adaptive path optimization algorithm inspired by the immune system to adjust the node selection in the transmission path in real time. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes nodes that are not suitable for continued participation in the transmission and selects a new optimal path. S44. If a node loses communication due to power exhaustion or out of network coverage during the transmission process, the system will automatically enable the backup path, continue to transmit the emergency information through other nodes, and reselect the optimal path based on the spatiotemporal status of the remaining nodes.

2. The BeiDou satellite-based emergency communication and positioning method according to claim 1, wherein: The S2 specifically includes: S21, the situational awareness algorithm calculates the user's emergency index by performing real-time analysis of multimodal sensor data : ； in, Represents the user's acceleration data, Represents the user's heart rate data, Indicates ambient air pressure data, Indicates the ambient temperature, 、 、 and represents the nonlinear adjustment factor, represents the time decay factor, Represents the global environment correction factor; S22, the situational awareness algorithm dynamically adjusts the sensor data in combination with external conditions to determine whether the user is in an emergency state. Exceeding the preset threshold When the system determines that the user is in an emergency state, it starts the emergency information processing process; S23. The specific emergency levels are: ； in, Indicates the high priority threshold, Indicates the medium priority threshold; when When , it means the user is in an extremely dangerous state; when When , it means the user is in a potentially dangerous state; when When , it means the user status is relatively safe and the status information needs to be updated regularly; S24, situational awareness algorithm based on sensor data and calculated emergency index ,dynamically prioritize emergency information and adjust information transmission paths and strategies based on priority; S25. After the emergency status analysis is completed, the system enters the corresponding emergency information processing and transmission process based on the priority of the emergency status index.

3. The BeiDou satellite-based emergency communication and positioning method according to claim 1, wherein: The S3 specifically includes: S31. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority, wherein the emergency information includes the user's real-time location information, emergency status index, sensor data, and the unique identifier of the user device; S32. Emergency information is transmitted in the form of data packets. The size of the data packet is Dynamic calculation: ； in, represents the emergency index, Indicates information priority, Indicates the power of the node device. Indicates the signal strength of the node device. represents the proportionality constant, 、 and represents the nonlinear adjustment factor; S33. When the Beidou satellite signal is unstable or interrupted, the user equipment detects the current communication environment and automatically starts the short-range wireless communication protocol for local communication and information transmission; S34: The user device automatically searches for other nearby devices through a short-range wireless communication protocol and connects them to form a self-organizing network. The self-organizing network is used to relay emergency information transmission, and the power of the node device is taken into account during the transmission process. , signal strength and current load ; S35. Each device acts as a network node, and the probability of the node device participating in the communication for: ； in, 、 and represents the nonlinear adjustment factor.

4. The BeiDou satellite-based emergency communication and positioning method according to claim 1, wherein: The S42 specifically includes: S421, the node is designed as an antibody model, each node The status of antibody fitness express: ； in, Representation node In time The antibody fitness, represents the environmental correction factor, 、 、 、 and represents the nonlinear adjustment factor; S422. Emergency information is designed as an antigen model to calculate the urgency : ； in, A correction factor indicating the current environment of the emergency task, represents the emergency index, Indicates information priority; S423, Calculation of Antibodies With antigen The matching degree is used to measure the adaptability of the node to emergency information: ； in, Representation node Matching degree to emergency information; S424, when the node's matching degree Exceeding the set threshold When the node participates in information transmission first, if the matching degree is lower than the threshold , then the node is excluded from the transmission path; S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism: ； in, Representation node Antibody fitness after concentration adjustment, Indicates the frequency of node participation in the transmission task. The higher the frequency, the lower the fitness after adjustment. S426, immune memory mechanism is used to record nodes with higher fitness in history, and give priority to nodes with higher fitness to participate in similar tasks in the future, and update the memory fitness : ； in, represents the memory decay factor, Indicates the time step.

5. The BeiDou satellite-based emergency communication and positioning method according to claim 1, wherein: The S6 specifically includes: S61. When the user device sends emergency information to the rescue center via BeiDou satellite or self-organizing network, if the transmission fails, the system automatically records the failure time. ; S62. Optimize the transmission cost of the backup path : ； in, Indicates the number of historical transmission failures on the path. The higher the number, the higher the path cost. Representation node The dynamic adjustment factor, Indicates the total number of nodes participating in the transmission, Indicates the The signal strength of each node, No. The current load of the nodes, Indicates the The power consumption of each node; S63: If the backup path still fails to transmit information successfully, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate : ； in, Indicates the degree of congestion in the network where the node is located. The higher the congestion, the lower the transmission success rate. Indicates the time impact on the current transmission task. represents the emergency index, Indicates information priority; S64. The system monitors the status of each node participating in parallel transmission in real time and dynamically adjusts the number of participating nodes based on the actual transmission results. When the transmission failure rate of a node increases, the system automatically reduces the priority of the node participating in parallel transmission until the node status returns to normal. S65. The system designs a local caching mechanism. After a transmission failure, the device caches the emergency information in local storage and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status: ； in, Indicates the time interval for the device to retransmit after failure. represents the regulating factor; S66. After confirming that the rescue center has received the transmitted data, the system automatically clears the local cache information of the device and records the successful transmission time. .

6. A BeiDou satellite-based emergency communication and positioning system, which implements the BeiDou satellite-based emergency communication and positioning method according to any one of claims 1 to 5, characterized in that: Includes the following modules: Multimodal sensor module for real-time collection of user's body movement, health status and environmental parameters; A situational awareness module, which analyzes multimodal sensor data, determines emergency status, and processes emergency information based on priority classification; The communication module transmits emergency information via satellite when the Beidou satellite signal is stable, and transmits it via short-range wireless communication when the signal is interrupted; Path optimization module, based on immune system-inspired algorithms and spatiotemporal perception technology, dynamically selects and optimizes information transmission paths; The feedback module is used to send confirmation feedback to the user equipment through the Beidou satellite reverse link after the rescue center receives the emergency information; A redundant transmission module is used to use a backup path or node for redundant data transmission when the first transmission fails until the information is successfully transmitted; The rescue dispatch module is used by the rescue center to track user status based on real-time data and dynamically adjust the rescue plan.

Images