Emergency communication and positioning system and method based on Beidou satellite

Abstract

The invention discloses an emergency communication and positioning system and method based on a Beidou satellite. The method comprises the following steps: S1, collecting data in real time; s2, analyzing the emergency state of the user by using a context awareness algorithm; s3, under the condition that the satellite communication signal is stable, transmitting the emergency information to a rescue center according to the calculated priority, if the satellite signal is unstable or interrupted, constructing a self-organizing network, and continuing to transmit the emergency information; s4, dynamically selecting an optimal path based on an adaptive path optimization algorithm inspired by an immune system, and further optimizing path selection through a space-time perception algorithm; s5, according to a priority management mechanism, the emergency information with high priority is processed preferentially, and feedback information is sent; s6, if the first emergency information transmission fails, the system starts a redundant data transmission mechanism; and S7, continuously tracking the state change of the user, and dynamically adjusting the rescue scheme. According to the invention, the situation awareness and immune system optimization algorithm is combined to realize 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 satellite. Background Art

[0003] Traditional emergency communication systems mostly rely on a single satellite or terrestrial communication network, which shows significant limitations in some extreme cases. For example, when the communication infrastructure is damaged or insufficiently covered in a disaster, the system's communication link is easily interrupted, resulting in the inability to transmit information in a timely manner. In addition, existing systems usually only support one-way communication, where users can send out distress signals but cannot receive feedback from the rescue center, which makes the rescue process lack of interactivity and reduces users' sense of security and rescue efficiency. Especially in natural disasters or remote areas far away from communication infrastructure, users cannot get timely feedback and help, which seriously affects the efficiency and accuracy of rescue.

[0004] Another common problem is that when faced with multiple emergency events or users, existing systems lack an effective information priority management mechanism and are unable to dynamically allocate communication resources based on the urgency of the event. This "one-size-fits-all" approach results in all information being processed with the same priority, and even in situations of limited resources or information overload, it is impossible to ensure that the most important emergency information is transmitted first, thus delaying rescue operations. Especially at a disaster site, many users' distress messages may pour in at the same time, and it is difficult for traditional communication systems to distinguish and process these messages based on urgency in a short period of time.

[0005] In addition, in the face of unstable communication links, traditional emergency communication systems rely on fixed transmission paths. Once a path fails, information will be lost or transmission will fail, and there is a lack of redundant transmission mechanisms. In emergency scenarios, the reliability of information transmission is crucial, and a single transmission failure may mean the loss of precious rescue opportunities. Existing emergency communication systems have not yet formed a complete solution in this regard. Most systems can only rely on a single link for transmission, and do not fully utilize the collaborative communication between multiple paths or multiple devices.

[0006] Emergency communication equipment in existing technologies generally can only rely on a single communication technology, such as long-distance communication relying on satellite signals or short-distance 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 geographical locations or extreme climates, satellite signals may be blocked or interrupted, and the equipment cannot establish a self-organizing network through other devices or short-distance wireless networks in time to continue communication.

[0007] In addition, the current path optimization technology has limited application in emergency communications. Although path optimization technology is widely used in the Internet and other communication fields, in emergency communication scenarios, due to the dynamic changes in network status and device status, the traditional fixed path selection method is difficult to adapt to the complex needs of emergency communications. In extreme environments, the power, signal strength and load conditions of node devices may change rapidly. It is difficult for traditional path optimization algorithms to adjust the transmission path in real time, resulting in low information transmission efficiency and even transmission failure. Traditional systems lack intelligent adjustment mechanisms in dealing with the dynamic nature of node devices and cannot dynamically select the optimal transmission path based on the actual status of the node.

[0008] In order to improve the reliability and efficiency of transmission, a redundant transmission mechanism is essential. However, most of the existing emergency communication systems do not implement a mechanism for redundant transmission of multiple paths or multiple nodes, which means that once the communication link is interrupted, the transmission of information will fail completely. The redundant mechanism can automatically enable the backup path or node for information transmission when the main transmission link fails, thereby ensuring that emergency information can still successfully reach the rescue center in the worst environment.

[0009] Therefore, how to provide an emergency communication and positioning system and method based on Beidou satellite is a problem that technical personnel in this field urgently need to solve. Summary of the invention

[0010] One purpose of the present invention is to propose an emergency communication and positioning system and method based on Beidou satellites. The present invention combines multimodal sensing technology, situational awareness algorithm and immune system-inspired adaptive path optimization method to construct an emergency communication and positioning system based on Beidou satellites. Through dynamic priority division, two-way communication feedback mechanism, and redundant transmission mechanism combining satellite and short-range wireless communication, the system can achieve efficient transmission of emergency information and rescue feedback in complex or extreme environments. The invention has the advantages of high communication reliability, fast information transmission efficiency, flexible path selection and timely rescue response, and is particularly suitable for disaster emergency and remote rescue scenarios.

[0011] The Beidou satellite-based emergency communication and positioning method according to an embodiment of the present invention comprises the following steps:

[0012] S1, monitor the user's physical condition and environmental data through multimodal sensors on the user's device, and collect the user's physical movement, health status and environmental parameters in real time;

[0013] S2. Based on the collected multimodal sensor data, the user's emergency status is analyzed using a context-aware algorithm. When an abnormal situation is detected or the user actively sends a distress signal, the system starts emergency information processing and divides the emergency information into high priority, medium priority and low priority according to the degree of urgency through a priority calculation engine;

[0014] 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 emergency information;

[0015] S4, an adaptive path optimization algorithm inspired by the immune system, combines the power, signal strength and load of the smart node devices in the self-organizing network to dynamically select the optimal path, and predicts the movement path and state changes of the device through the time-space perception algorithm to further optimize the path selection;

[0016] S5. After receiving the emergency information, the rescue center will give priority to the 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;

[0017] S6. During the communication process, if the first emergency information transmission fails, the system starts 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;

[0018] S7. The rescue center continuously tracks the user's status changes based on the data uploaded by the user's device in real time and dynamically adjusts the rescue plan.

[0019] Optionally, the S2 specifically includes:

[0020] S21, the situational awareness algorithm calculates the user's emergency index F(t) by real-time analysis of multimodal sensor data:

[0021]

[0022] 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;

[0023] 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;

[0024] S23. The specific emergency levels are:

[0025]

[0026] Among them, F high represents the high priority threshold, F medium Indicates the medium priority threshold;

[0027] When F(t)>F high When it is on, it means the user is in an extremely dangerous state;

[0028] When F medium ≤F(t)≤F high When it is on, it means the user is in a potentially dangerous state;

[0029] When F(t) <F medium When the user status is relatively safe, it means that the status information needs to be updated regularly;

[0030] 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;

[0031] 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.

[0032] Optionally, the S3 specifically includes:

[0033] S31. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority, and the emergency information includes the user's real-time location information, emergency status index, sensor data and the unique identifier of the user's device;

[0034] S32. The transmission of emergency information is carried out in the form of data packets, and the size of the data packet P(t) is dynamically calculated:

[0035]

[0036] Wherein, 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;

[0037] 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;

[0038] S34, the user equipment automatically searches for other nearby devices through a short-range wireless communication protocol and connects to form a self-organizing network, which 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 considered;

[0039] S35. Each device acts as a network node, and the probability P of the node device participating in the communication node (t) is:

[0040]

[0041] Among them, γ1, γ2 and γ3 represent nonlinear adjustment factors.

[0042] Optionally, the S4 specifically includes:

[0043] 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 the time-space perception algorithm to evaluate the dynamic state of the node:

[0044]

[0045] 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 ith node, E i (t) represents the power of the ith 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 position of the node at a certain moment in the future, L max (t) represents the maximum allowed load value in the current network, T max (t) represents the maximum allowed delay value in the current network;

[0046] 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):

[0047]

[0048] Among them, P 当前(t) represents the current position information of the node, V(t) represents the current speed of the node, A(t) represents the acceleration of the node, and Δt represents the time step;

[0049] S43. The system adjusts the node selection in the transmission path in real time based on the adaptive path optimization algorithm inspired by the immune system. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes the nodes that are not suitable for continuing to participate in the transmission and selects a new optimal path.

[0050] 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.

[0051] Optionally, the S42 specifically includes:

[0052] 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:

[0053]

[0054] 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;

[0055] S422. Emergency information is designed as an antigen model to calculate the urgency Ur(t):

[0056]

[0057] 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;

[0058] S423, calculation of antibody A i The matching degree between (t) and antigen Ur(t) is used to measure the adaptability of the node to emergency information:

[0059]

[0060] Among them, M i (t) represents the matching degree of node i to the emergency information;

[0061] 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;

[0062] S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism:

[0063]

[0064] 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 adjusted fitness.

[0065] 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 A 记忆 (t):

[0066] A 记忆 (t) = (1-θ)·A 记忆 (t-Δt)+θ·A i (t);

[0067] Where θ represents the memory decay factor and Δt represents the time step.

[0068] Optionally, the S6 specifically includes:

[0069] 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 T fail (t);

[0070] S62: Optimize the transmission cost P of the backup path 冗余 (t):

[0071]

[0072] 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 ith node, E i (t) represents the power of the i-th node;

[0073] S63: If the backup path still fails to successfully transmit information, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate P 成功 (t):

[0074]

[0075] 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.

[0076] S64, the system monitors the status of each node participating in parallel transmission in real time, and dynamically adjusts the number of participating nodes according to 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;

[0077] S65. The system designs a local cache mechanism. The device caches emergency information in local storage after a transmission failure, and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status:

[0078]

[0079] Among them, T 重传 (t) represents the time interval for the device to retransmit after failure, represents the regulating factor;

[0080] 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).

[0081] The Beidou satellite-based emergency communication and positioning system according to an embodiment of the present invention includes the following modules:

[0082] Multimodal sensor module for real-time collection of user's body movement, health status and environmental parameters;

[0083] A situational awareness module that analyzes multimodal sensor data, determines emergency status, and processes emergency information based on priority classification;

[0084] 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;

[0085] Path optimization module, based on immune system-inspired algorithms and spatiotemporal perception technology, dynamically selects and optimizes information transmission paths;

[0086] Feedback module, used for the rescue center to send confirmation feedback to the user equipment through the Beidou satellite reverse link after receiving the emergency information;

[0087] 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;

[0088] 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.

[0089] The beneficial effects of the present invention are:

[0090] First, through the application of multimodal sensors, the system of the present invention can collect the user's physical state 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 time in an emergency. 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 emergency situations and greatly shortens the reaction time.

[0091] Secondly, the present invention uses a priority calculation engine to classify information into high, medium, and low priorities according to the degree of urgency, ensuring that the most important information in an emergency can be processed and transmitted first. This solves the problem of insufficient information priority management in traditional systems. When information is overloaded at a disaster site, it can effectively distinguish the importance of information and ensure that the most urgent rescue needs are responded to in a timely manner. This dynamic priority allocation mechanism improves the communication efficiency of the system under limited resources, optimizes the use of information transmission paths, and avoids communication congestion and resource waste.

[0092] In terms of communication path selection, traditional systems only rely on fixed transmission paths and cannot adapt to changes in node status. The present invention introduces an adaptive path optimization algorithm inspired by the immune system, which can adjust the transmission path in real time according to the power, signal strength and current load of the node device to ensure the efficiency and stability of the communication link. At the same time, the time-space perception algorithm further predicts the movement path and state changes of the device, so as to plan the best communication path in advance and avoid node failure or network interruption problems. This path optimization mechanism significantly improves the flexibility and adaptability of transmission, and can ensure the smooth transmission of information even in complex and dynamic environments.

[0093] In addition, the present invention combines satellite communication with short-range wireless communication technology. When the Beidou satellite signal is unstable or interrupted, the system can automatically form a self-organizing network through the short-range wireless communication protocol to continue to transmit emergency information, ensuring that the communication link can be kept unobstructed in any environment. This multi-mode communication design greatly enhances the robustness and communication coverage of the system, solves the limitation of the satellite signal being easily interrupted in the prior art, and enables the system to still function in remote areas or disaster sites with damaged infrastructure.

[0094] The introduction of redundant data transmission mechanism further enhances the reliability of information transmission. When communication fails, the system automatically starts the backup path or node, and uses the redundant mechanism to ensure that the information is eventually transmitted to the rescue center. This design avoids the problem of information loss caused by the failure of a single communication path and improves the success rate of information transmission, especially in complex and unstable network environments, ensuring the reliability of emergency information transmission and preventing the loss of precious rescue opportunities due to transmission failure.

[0095] Finally, the present invention also introduces a two-way communication feedback mechanism. After receiving the emergency information, the rescue center can send feedback information to the user device in a timely manner through the reverse link of the Beidou satellite to inform the rescue progress or provide self-rescue suggestions. Compared with the existing one-way communication system, this design greatly improves the user's sense of security and information transparency, allowing users to get feedback in time while waiting for rescue, reducing uncertainty, and improving the efficiency of the rescue operation and the user's survival probability. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] 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:

[0097] Figure 1 The overall flow chart of the Beidou satellite-based emergency communication and positioning method proposed by the present invention;

[0098] Figure 2 This is a schematic diagram of the structure of the Beidou satellite-based emergency communication and positioning system proposed by the present invention. DETAILED DESCRIPTION

[0099] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0100] refer to Figure 1 , an emergency communication and positioning method based on Beidou satellite, comprising the following steps:

[0101] S1, monitor the user's physical condition and environmental data through multimodal sensors on the user's device, and collect the user's physical movement, health status and environmental parameters in real time;

[0102] S2. Based on the collected multimodal sensor data, the user's emergency status is analyzed using a context-aware algorithm. When an abnormal situation is detected or the user actively sends a distress signal, the system starts emergency information processing and divides the emergency information into high priority, medium priority and low priority according to the degree of urgency through a priority calculation engine;

[0103] 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 emergency information;

[0104] S4, an adaptive path optimization algorithm inspired by the immune system, combines the power, signal strength and load of the smart node devices in the self-organizing network to dynamically select the optimal path, and predicts the movement path and state changes of the device through the time-space perception algorithm to further optimize the path selection;

[0105] S5. After receiving the emergency information, the rescue center will give priority to the 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;

[0106] S6. During the communication process, if the first emergency information transmission fails, the system starts 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;

[0107] S7. The rescue center continuously tracks the user's status changes based on the data uploaded by the user's device in real time and dynamically adjusts the rescue plan.

[0108] In this implementation, S2 specifically includes:

[0109] S21, the situational awareness algorithm calculates the user's emergency index F(t) by real-time analysis of multimodal sensor data:

[0110]

[0111] 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;

[0112] 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;

[0113] S23. The specific emergency levels are:

[0114]

[0115] Among them, F high represents the high priority threshold, F medium Indicates the medium priority threshold;

[0116] When F(t)>F high When it is on, it means the user is in an extremely dangerous state;

[0117] When F medium ≤F(t)≤F high When it is on, it means the user is in a potentially dangerous state;

[0118] When F(t) <F medium When the user status is relatively safe, it means that the status information needs to be updated regularly;

[0119] 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;

[0120] 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.

[0121] In this implementation, S3 specifically includes:

[0122] S31. When the Beidou satellite communication signal is stable, the emergency information is transmitted to the rescue center according to the calculated priority, and the emergency information includes the user's real-time location information, emergency status index, sensor data and the unique identifier of the user's device;

[0123] S32. The transmission of emergency information is carried out in the form of data packets, and the size of the data packet P(t) is dynamically calculated:

[0124]

[0125] Wherein, 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;

[0126] 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;

[0127] S34, the user equipment automatically searches for other nearby devices through a short-range wireless communication protocol and connects to form a self-organizing network, which 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 considered;

[0128] S35. Each device acts as a network node, and the probability P of the node device participating in the communication node (t) is:

[0129]

[0130] Among them, γ1, γ2 and γ3 represent nonlinear adjustment factors.

[0131] In this implementation, S4 specifically includes:

[0132] 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 the time-space perception algorithm to evaluate the dynamic state of the node:

[0133]

[0134] 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 ith node, E i (t) represents the power of the ith 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 position of the node at a certain moment in the future, L max (t) represents the maximum allowed load value in the current network, T max (t) represents the maximum allowed delay value in the current network;

[0135] 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):

[0136]

[0137] Among them, P 当前 (t) represents the current position information of the node, V(t) represents the current speed of the node, A(t) represents the acceleration of the node, and Δt represents the time step;

[0138] S43. The system adjusts the node selection in the transmission path in real time based on the adaptive path optimization algorithm inspired by the immune system. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes the nodes that are not suitable for continuing to participate in the transmission and selects a new optimal path.

[0139] 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.

[0140] In this implementation manner, the S42 specifically includes:

[0141] 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:

[0142]

[0143] 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;

[0144] S422. Emergency information is designed as an antigen model to calculate the urgency Ur(t):

[0145]

[0146] 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;

[0147] S423, calculation of antibody A i The matching degree between (t) and antigen Ur(t) is used to measure the adaptability of the node to emergency information:

[0148]

[0149] Among them, M i(t) represents the matching degree of node i to the emergency information;

[0150] 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;

[0151] S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism:

[0152]

[0153] 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 adjusted fitness.

[0154] 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 A 记忆 (t):

[0155] A 记忆 (t) = (1-θ)·A 记忆 (t-Δt)+θ·A i (t);

[0156] Where θ represents the memory decay factor and Δt represents the time step.

[0157] In this implementation manner, S6 specifically includes:

[0158] 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 T fail (t);

[0159] S62: Optimize the transmission cost P of the backup path 冗余 (t):

[0160]

[0161] 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 ith node, Ei (t) represents the power of the i-th node;

[0162] S63: If the backup path still fails to successfully transmit information, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate P 成功 (t):

[0163]

[0164] 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.

[0165] S64, the system monitors the status of each node participating in parallel transmission in real time, and dynamically adjusts the number of participating nodes according to 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;

[0166] S65. The system designs a local cache mechanism. The device caches emergency information in local storage after a transmission failure, and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status:

[0167]

[0168] Among them, T 重传 (t) represents the time interval for the device to retransmit after failure, represents the regulating factor;

[0169] 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).

[0170] refer to Figure 2 , the Beidou satellite-based emergency communication and positioning system includes the following modules:

[0171] Multimodal sensor module for real-time collection of user's body movement, health status and environmental parameters;

[0172] A situational awareness module that analyzes multimodal sensor data, determines emergency status, and processes emergency information based on priority classification;

[0173] 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;

[0174] Path optimization module, based on immune system-inspired algorithms and spatiotemporal perception technology, dynamically selects and optimizes information transmission paths;

[0175] Feedback module, used for the rescue center to send confirmation feedback to the user equipment through the Beidou satellite reverse link after receiving the emergency information;

[0176] 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;

[0177] 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.

[0178] Embodiment 1:

[0179] In order to verify the feasibility of the present invention in implementation, the present invention is applied to natural disaster rescue in mountainous areas.

[0180] In July of a certain year, continuous heavy rains triggered large-scale landslides in the mountainous area of ​​M City, H Province, resulting in some mountain villages being buried by mud and rock flows, and the communication infrastructure was also severely damaged. After the disaster, multiple rescue teams were quickly dispatched to the disaster-stricken areas 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 bad weather in the mountainous areas caused the satellite signal in some areas to be unstable, and the communication between the rescuers and the command center was greatly affected. 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.

[0181] First, the equipment worn by rescuers is equipped with multimodal sensors to monitor their physical condition and environmental data. These sensors can collect the rescuers' motion information, heart rate, ambient temperature and other data in real time, and analyze these data through situational awareness algorithms to determine whether the rescuers are in danger. Due to the complex terrain in the debris flow area, rescuers may face accidents at any time, such as slips, falls or being trapped. Through real-time monitoring of sensor data, the system can promptly detect the abnormal state of rescuers, activate the emergency information transmission mechanism, and prioritize information according to the degree of urgency.

[0182] During the actual rescue process, three rescuers entered an area where the signal was extremely unstable, and traditional satellite communications could not maintain a stable connection. In this case, the system first determines that the Beidou satellite communication signal is unstable and automatically switches to short-range wireless communication mode. The rescue equipment forms a network with the equipment of other nearby rescuers through the short-range wireless communication protocol, and relays the emergency information to the area where the satellite signal can be received through multi-hop transmission. During a certain operation, a rescuer accidentally slipped, and the device in the backpack detected his fall and determined that he might be injured through abnormal data from the acceleration sensor and heart rate sensor. The system automatically classifies the information as high-priority information, and transmits it to the device relay that can communicate with the satellite through the self-organizing network, and finally successfully transmits the distress message to the command center.

[0183] Through this system, the command center not only received the distress signals sent by the rescuers, but also sent real-time feedback to the rescuers through the Beidou satellite reverse link, informing them that the rescue team was on the way and providing temporary self-rescue guidance. This two-way communication function greatly alleviated the anxiety of the rescuers during the waiting process, and also ensured the efficient execution of the rescue plan.

[0184] Throughout the rescue process, the adaptive path optimization algorithm inspired by the immune system of the present invention played an important role. Due to the complex terrain in 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 according to the dynamic state of the node. For example, during a certain information transmission process, some rescuers' equipment 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. Finally, through the combination of multi-hop transmission, path optimization and redundancy mechanism, all important information was successfully transmitted to the rescue center within the specified time.

[0185] Table 1 Comparison data between the system of the present invention and the traditional satellite communication system

[0186]

[0187]

[0188] Table 1 compares in detail the performance of the Beidou satellite-based emergency communication and positioning system and the traditional satellite communication system in terms of multiple key indicators, and demonstrates the superiority of the present invention in emergency rescue through specific data.

[0189] First, in terms of emergency information processing time, the system of the present invention performs significantly better than traditional systems. The present invention can start the emergency information processing process within 0.95 seconds and complete the transmission of high-priority information within 9.87 seconds. Traditional satellite communication systems are relatively slow in this process, with a startup time of approximately 62.4 seconds and an overall transmission time of more than 60 seconds. Fast response time is crucial for emergency rescue. The system of the present invention significantly shortens this time by optimizing the startup and transmission processes, greatly improving rescue efficiency.

[0190] In terms of information transmission delay, the path optimization algorithm of the present invention reduces the average delay of information transmission by 17.8%, from the traditional 54.3 milliseconds to 44.6 milliseconds. In contrast, the delay of traditional satellite communication systems is unstable, with an average delay of 61.2 milliseconds. In rescue scenarios, reducing information transmission delay can deliver emergency information to the command center faster, ensuring the timeliness of rescue decisions.

[0191] The transmission success rate is another indicator that reflects the advantages of the present invention. In complex terrain and harsh environments, the transmission success rate of the present invention is as high as 95.8%, which is much higher than the 70.9% of traditional satellite communication systems. This advantage is due to the redundant transmission mechanism and path optimization technology of the present invention, which enables the successful transmission of emergency information even in unstable signal conditions.

[0192] The present invention also shows great advantages in feedback response time. Through the two-way communication function, the command center can feedback information within 25.4 seconds, while the feedback response time of the traditional satellite communication system is 80.7 seconds on average. This difference is crucial for the psychological support and action command of rescuers. Rapid feedback can significantly improve the coordination and timeliness of rescue.

[0193] The number of communication interruptions is also a significant shortcoming of traditional systems. During the rescue process, the present invention successfully avoided 5 information transmission interruptions, while the traditional system had an average of 3.7 interruptions per hour. Through the self-organizing network and redundant transmission mechanism, the present invention effectively reduces the risk of communication interruptions and ensures the continuity and reliability of information transmission.

[0194] Finally, in terms of power consumption of the equipment, the present invention reduces power consumption by an average of 18.4% by optimizing communication paths and reducing unnecessary communication operations, extending the battery life of the equipment by 2.6 hours. However, due to frequent communication interruptions and poor path selection, the traditional system consumes power quickly and the battery life is reduced by 1.9 hours. In long-term rescue operations, the battery life of the equipment directly affects the continuity of the rescue, and the optimization of this aspect of the present invention is particularly important.

[0195] In summary, the Beidou satellite-based emergency communication and positioning system is significantly superior to the traditional satellite communication system in all key indicators, especially in emergency information processing time, transmission success rate, feedback response time and power management. The present invention effectively improves the performance of the system in complex rescue scenarios through multimodal sensing, path optimization and redundant transmission technologies, ensuring fast and reliable transmission of information and two-way feedback.

[0196] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An emergency communication and positioning method based on Beidou satellite, characterized in that: The steps include: S1, monitor the user's physical condition and environmental data through multimodal sensors on the user's device, and collect the user's physical movement, health status and environmental parameters in real time; S2. Based on the collected multimodal sensor data, the user's emergency status is analyzed using a context-aware algorithm. When an abnormal situation is detected or the user actively sends a distress signal, the system starts emergency information processing and divides the emergency information into high priority, medium priority and low priority according to the degree of urgency through a priority calculation engine; 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 emergency information; S4, an adaptive path optimization algorithm inspired by the immune system, combines the power, signal strength and load of the smart node devices in the self-organizing network to dynamically select the optimal path, and predicts the movement path and state changes of the device through the time-space perception algorithm to further optimize the path selection; S5. After receiving the emergency information, the rescue center will give priority to the 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 emergency information transmission fails, the system starts 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 data uploaded by the user's device in real time and dynamically adjusts the rescue plan.

2. The Beidou satellite-based emergency communication and positioning method according to claim 1, characterized in that: The S2 specifically includes: S21, the situational awareness algorithm calculates the user's emergency index F(t) by real-time analysis of multimodal sensor data: 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; 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; S23. The specific emergency levels are: Among them, F high represents the high priority threshold, F medium Indicates the medium priority threshold; When F(t)>F high When it is on, it means the user is in an extremely dangerous state; When F medium ≤F(t)≤F high When it is on, it means the user is in a potentially dangerous state; When F(t) <F medium When the user status is relatively safe, it means that the status information needs to be updated regularly; 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; 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, characterized in that: 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, and the emergency information includes the user's real-time location information, emergency status index, sensor data and the unique identifier of the user's device; S32. The transmission of emergency information is carried out in the form of data packets, and the size of the data packet P(t) is dynamically calculated: Wherein, 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; 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 equipment automatically searches for other nearby devices through a short-range wireless communication protocol and connects to form a self-organizing network, which 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 considered; S35. Each device acts as a network node, and the probability P of the node device participating in the communication node (t) is: Among them, γ1, γ2 and γ3 represent nonlinear adjustment factors.

4. The Beidou satellite-based emergency communication and positioning method according to claim 1, characterized in that: 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 the time-space perception algorithm to evaluate the dynamic state of the node: 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 ith node, E i (t) represents the power of the ith 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 position of the node at a certain moment in the future, L max (t) represents the maximum allowed load value in the current network, T max (t) represents 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 P of the node at the future time 预测 (t): Among them, P 当前 (t) represents the current position information of the node, V(t) represents the current speed of the node, A(t) represents the acceleration of the node, and Δt represents the time step; S43. The system adjusts the node selection in the transmission path in real time based on the adaptive path optimization algorithm inspired by the immune system. At the same time, the state change of the node triggers the path recalculation. The system automatically excludes the nodes that are not suitable for continuing to participate 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.

5. The Beidou satellite-based emergency communication and positioning method according to claim 4, characterized in that: The S42 specifically includes: 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: 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; S422. Emergency information is designed as an antigen model to calculate the urgency Ur(t): 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; S423, calculation of antibody A i The matching degree between (t) and antigen Ur(t) is used to measure the adaptability of the node to emergency information: Among them, M i (t) represents the matching degree of node i to the emergency information; 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; S425. The system adjusts the node's fitness by introducing an antibody concentration adjustment mechanism: 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 adjusted fitness. 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 A 记忆 (t): A 记忆 (t)=(1-θ)·A 记忆 (t-Δt)+θ·A i (t); Where θ represents the memory decay factor and Δt represents the time step.

6. The Beidou satellite-based emergency communication and positioning method according to claim 1, characterized in that: 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 T fail (t); S62: Optimize the transmission cost P of the backup path 冗余 (t): 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 ith node, E i (t) represents the power of the i-th node; S63: If the backup path still fails to successfully transmit information, the system starts a multi-node parallel transmission mechanism to optimize the transmission success rate P 成功 (t): 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. S64, the system monitors the status of each node participating in parallel transmission in real time, and dynamically adjusts the number of participating nodes according to 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 cache mechanism. The device caches emergency information in local storage after a transmission failure, and dynamically adjusts the cache retransmission frequency based on the number of historical failures and network status: Among them, T 重传 (t) represents 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 T 成功 (t).

7. The Beidou satellite-based emergency communication and positioning system implements the Beidou satellite-based emergency communication and positioning method according to any one of claims 1 to 6, 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 that 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; Feedback module, used for the rescue center to send confirmation feedback to the user equipment through the Beidou satellite reverse link after receiving 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.

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