Method and device for data transmission back of unmanned surface vessel based on urban water area monitoring

Abstract

The present invention relates to the technical field of data transmission of unmanned surface vessels, and discloses a method and device for data backhaul of unmanned surface vessels based on urban water area monitoring. The method includes acquiring a plurality of target unmanned surface vessels, determining their data acquisition nodes and data backhaul central nodes, as well as communication relay nodes therebetween; selecting target relay nodes according to communication quality indicators to generate a data transmission path; determining the packet arrival time according to the data transmission rate and sub-link transmission indicators, marking to obtain a real-time communication timing diagram, detecting communication channel conflicts, and planning the data transmission path based on the conflict results. The device includes acquisition, generation, determination, marking, detection, and planning modules. The present invention comprehensively considers the signal strength and transmission delay to select relay nodes, can effectively solve communication conflicts, adapt to data transmission of different priorities, and can also dynamically cope with communication interference, improving the stability, reliability, and transmission efficiency of data backhaul of unmanned surface vessels, and meeting the requirements of urban water area monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission for unmanned surface vessels, and specifically to a method and device for data backhaul of unmanned surface vessels based on urban water area monitoring. Background Art

[0002] In the field of urban water area monitoring, unmanned surface vessels play an increasingly important role as an efficient monitoring tool. With the acceleration of urbanization, the scope of urban water areas is constantly expanding, and their environmental conditions have become more complex and diverse. Traditional manual monitoring methods are not only inefficient and costly, but also unable to conduct comprehensive and accurate monitoring in some dangerous or inaccessible waters. Unmanned surface vessels, with their flexibility, operability, and the advantage of being able to work in harsh environments, have become an important means of urban water area monitoring.

[0003] However, unmanned surface vessels face many challenges in data backhaul. There are a large number of interference factors in the urban water area environment, such as building blockage, water surface reflection, and electromagnetic interference from other vessels, which seriously affect the transmission quality of communication signals. When existing data backhaul methods face these interferences, the signals are prone to attenuation, delay, or even interruption, resulting in the inability to transmit monitoring data to the data center in a timely and accurate manner, greatly reducing the real-time performance and reliability of monitoring.

[0004] In the selection of communication relay nodes, current technologies often lack scientific and effective strategies. Most methods simply select relay nodes based on a single factor such as distance or signal strength, without comprehensively considering multiple key indicators such as signal strength and transmission delay. This makes the constructed data transmission path not optimal and unable to fully guarantee the stability and efficiency of data transmission.

[0005] In addition, when multiple unmanned vessels transmit data simultaneously, communication channel conflict problems occur frequently. Due to the lack of a reasonable conflict detection and resolution mechanism, once a conflict occurs, it will lead to packet loss and retransmission, further reducing the data transmission efficiency and increasing the time cost and resource consumption of data transmission. Moreover, existing data backhaul methods usually do not consider the possible communication interference situations during the dynamic driving of unmanned vessels, such as mutual interference between adjacent unmanned vessels, which makes it difficult to effectively guarantee the stability and reliability of data backhaul in actual application scenarios.

[0006] With the continuous improvement of urban requirements for water area environment monitoring, more accurate and timely monitoring data is needed to support environmental decision-making and management. The existing data backhaul technology for unmanned surface vessels has been difficult to meet these growing demands, and there is an urgent need for a data backhaul method and device that can adapt to complex urban water area environments and is efficient and stable to improve the overall level of urban water area monitoring. Summary of the Invention

[0007] The object of the present invention is to provide a method and device for data transmission back of an unmanned surface vehicle based on urban water area monitoring, so as to solve the problems raised in the above-mentioned background technology.

[0008] To achieve the above object, the present invention provides the following technical solution: A method for data transmission back of an unmanned surface vehicle based on urban water area monitoring, the method includes:

[0009] Obtain a plurality of target unmanned surface vehicles, and determine the data acquisition nodes and data transmission back center nodes of each of the target unmanned surface vehicles from a preset monitoring area map, wherein the monitoring area map includes a plurality of communication relay nodes located between the data acquisition nodes and the data transmission back center nodes;

[0010] For each of the target unmanned surface vehicles, select a plurality of target relay nodes with the best communication quality indicators based on the communication quality indicators of each of the communication relay nodes relative to the data acquisition nodes and the data transmission back center nodes, and generate a data transmission path of the target unmanned surface vehicle according to the plurality of target relay nodes;

[0011] For each of the target unmanned surface vehicles, obtain the data transmission rate of the target unmanned surface vehicle, and determine the data packet arrival time when the target unmanned surface vehicle passes through a plurality of target relay nodes based on the sub-link transmission indicators between the target relay nodes included in the data transmission path and the data transmission rate;

[0012] Mark the data packet arrival time on each of the target relay nodes in the monitoring area map to obtain a real-time communication timing diagram;

[0013] For each of the target relay nodes, perform detection of communication channel conflicts according to the data packet arrival time to obtain a conflict detection result;

[0014] Perform data transmission path planning based on the conflict detection result to obtain a data transmission back planning result.

[0015] Preferably, the communication quality indicator is a comprehensive evaluation value of the signal strength and transmission delay for each communication relay node from the data acquisition node to each communication relay node and from each communication relay node to the data transmission back center node; the data transmission path is a planned path from the data acquisition node to the data transmission back center node, and is the optimal communication link composed of the selected plurality of target relay nodes.

[0016] Preferably, performing data transmission path planning based on the conflict detection result to obtain a data feedback planning result includes: when the conflict detection result indicates that there is a conflict in the arrival times of multiple data packets included in the target relay node, determining the target relay node as a conflict relay node; obtaining the arrival time of the data packet that generates the conflict in the conflict relay node as a conflict period, and determining the data transmission priorities of multiple target unmanned vessels corresponding to the conflict period; performing data transmission path planning on the target unmanned vessels based on the data transmission priorities to obtain a data feedback planning result.

[0017] Preferably, the target unmanned vessels include first-priority unmanned vessels and second-priority unmanned vessels. The data transmission priority of the first-priority unmanned vessels is the emergency level, and the data transmission priority of the second-priority unmanned vessels is the normal level; performing data transmission path planning on the target unmanned vessels based on the data transmission priorities to obtain a data feedback planning result includes:

[0018] Determining the data transmission path corresponding to the second-priority unmanned vessels based on the order of the emergency level and the normal level;

[0019] Based on the real-time communication timing diagram, obtaining the arrival times of data packets of the second-priority unmanned vessels at each target relay node in the corresponding data transmission path;

[0020] Performing data transmission path planning on the second-priority unmanned vessels based on the arrival times of the data packets and combining the real-time communication timing diagram to obtain a data feedback planning result.

[0021] Preferably, for each target unmanned vessel, selecting multiple target relay nodes with the optimal communication quality indicators based on the communication quality indicators of each communication relay node relative to the data acquisition node and the data feedback center node, and generating a data transmission path for the target unmanned vessel according to the multiple target relay nodes includes:

[0022] For each target unmanned vessel, determining multiple adjacent communication nodes adjacent to the data acquisition node;

[0023] Calculating the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data feedback center node, and determining the first target relay node with the optimal communication quality indicator from the multiple adjacent communication nodes based on the multiple communication quality indicators;

[0024] Starting from the first target relay node, determine multiple adjacent communication nodes adjacent to the target relay node, calculate the communication quality metrics of each adjacent communication node relative to the data acquisition node and the data backhaul center node, and based on the multiple communication quality metrics, determine the next target relay node with the optimal communication quality metric from the multiple adjacent communication nodes adjacent to the target relay node;

[0025] Repeat the steps of determining multiple adjacent communication nodes adjacent to the target relay node, calculating the communication quality metrics of each adjacent communication node relative to the data acquisition node and the data backhaul center node, and based on the multiple communication quality metrics, determining the next target relay node with the optimal communication quality metric from the multiple adjacent communication nodes adjacent to the target relay node until the next target relay node is determined to be the data backhaul center node to obtain multiple target relay nodes between the data acquisition node and the data backhaul center node;

[0026] Generate the data transmission path of the target unmanned ship based on the multiple target relay nodes.

[0027] Preferably, the calculating the communication quality metrics of each adjacent communication node relative to the data acquisition node and the data backhaul center node includes:

[0028] Calculate the first signal strength metric of the distance between each adjacent communication node and the data acquisition node, and the second transmission delay metric of the distance between each adjacent communication node and the data backhaul center node respectively;

[0029] For each adjacent communication node, use the weighted value of the first signal strength metric and the second transmission delay metric as the communication quality metric of the adjacent communication node relative to the data acquisition node and the data backhaul center node.

[0030] Preferably, the determining the first target relay node with the optimal communication quality metric from the multiple adjacent communication nodes based on the multiple communication quality metrics includes:

[0031] Store the multiple communication quality metrics corresponding to the multiple adjacent communication nodes in a communication quality evaluation list, and perform a descending order sorting on the communication quality metrics in the communication quality evaluation list to obtain a sorting result;

[0032] Based on the sorting result, determine the adjacent communication node corresponding to the optimal communication quality metric as the first target relay node.

[0033] Preferably, after performing data transmission path planning based on the conflict detection result to obtain a data feedback planning result, the method further includes:

[0034] After each of the target unmanned boats starts transmitting according to the data feedback planning result, for each of the target unmanned boats, the communication interference distance between the target unmanned boat and at least one adjacent target unmanned boat is detected in real time;

[0035] When the communication interference distance between the target unmanned boat and the adjacent target unmanned boat is less than a preset safety threshold, the adjacent target unmanned boat is used as an interference source, and dynamic data transmission path planning is performed on the target unmanned boat based on the interference source to obtain an updated data transmission path for the target unmanned boat.

[0036] Preferably, the present invention further includes a data feedback device for an unmanned boat on water based on urban water area monitoring, and the device includes:

[0037] An acquisition module, configured to acquire a plurality of target unmanned boats, and determine a data acquisition node and a data feedback center node for each of the target unmanned boats from a preset monitoring area map, wherein the monitoring area map includes a plurality of communication relay nodes located between the data acquisition node and the data feedback center node;

[0038] A generation module, configured to, for each of the target unmanned boats, select a plurality of target relay nodes with the optimal communication quality index based on the communication quality indexes of the respective communication relay nodes with respect to the data acquisition node and the data feedback center node, and generate a data transmission path for the target unmanned boat according to the plurality of target relay nodes; wherein the communication quality index is a comprehensive evaluation value of the signal strength and transmission delay for each communication relay node from the data acquisition node to the each communication relay node and from the each communication relay node to the data feedback center node; the data transmission path is a planned path from the data acquisition node to the data feedback center node and is an optimal communication link formed by the selected plurality of target relay nodes;

[0039] A determination module, configured to, for each of the target unmanned boats, obtain the data transmission rate of the target unmanned boat, and determine the packet arrival time when the target unmanned boat passes through a plurality of target relay nodes based on the sub-link transmission indexes between the target relay nodes included in the data transmission path and the data transmission rate;

[0040] A marking module, configured to mark the packet arrival time for each of the target relay nodes in the monitoring area map to obtain a real-time communication timing diagram;

[0041] A detection module, configured to detect communication channel conflicts according to the arrival time of the data packet for each of the target relay nodes, and obtain a conflict detection result;

[0042] A planning module, configured to perform data transmission path planning based on the conflict detection result to obtain a data backhaul planning result; the performing data transmission path planning based on the conflict detection result to obtain a data backhaul planning result includes: when the conflict detection result indicates that there are conflicts in the arrival times of multiple data packets included in the target relay node, determining the target relay node as a conflict relay node; obtaining the arrival time of the data packet generating the conflict of the conflict relay node as a conflict period, and determining the data transmission priorities of multiple target unmanned boats corresponding to the conflict period; performing data transmission path planning on the target unmanned boats based on the data transmission priorities to obtain a data backhaul planning result.

[0043] Preferably, the generation module is further configured to:

[0044] Dynamically adjust the communication quality index of the communication relay node according to real-time environment monitoring data, and regenerate the data transmission path of the target unmanned boat based on the updated communication quality index.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] In terms of data transmission path planning, by comprehensively considering communication quality indexes such as the signal strength and transmission delay of the communication relay node relative to the data acquisition node and the data backhaul center node, multiple optimal target relay nodes are selected to generate a data transmission path. This method can construct an optimal communication link from the data acquisition node to the data backhaul center node compared with the traditional method of simply selecting relay nodes based on distance or a single index. This enables the data to effectively avoid areas with strong signal interference and large transmission delays during the transmission process, greatly improving the stability and speed of data transmission. For example, in the case of many buildings and other interference sources in urban waters, the method of the present invention can accurately select the relay node with the best signal quality, ensure stable data transmission, reduce signal attenuation and delay, so as to ensure that the monitoring data can be quickly and accurately backhauled to the data center and improve the real-time performance of monitoring.

[0047] In dealing with the problem of communication channel conflicts, the present invention obtains a real-time communication timing diagram by marking the arrival time of data packets, and performs communication channel conflict detection based on this. When a conflict is detected, the conflict period and the data transmission priorities of relevant unmanned boats are determined, and then the data transmission path is re-planned based on the priorities. This mechanism can effectively solve the conflict problem generated when multiple unmanned boats transmit data simultaneously, avoid the loss and retransmission of data packets, and improve the success rate and efficiency of data transmission. For example, in an area where multiple unmanned boats are operating intensively, the traditional method is prone to data transmission chaos due to conflicts, while the present invention can orderly arrange data transmission according to priorities, ensure the priority transmission of important data, and reduce the time cost and resource consumption of data transmission.

[0048] For unmanned boats with different priorities, the present invention formulates a reasonable data transmission path planning strategy for the first priority (emergency level) and the second priority (regular level) unmanned boats. First, determine the data transmission path of the second priority unmanned boats, and then optimize it in combination with the real-time communication timing diagram to ensure that unmanned boats with different priorities can reasonably arrange the transmission order and path on the premise of ensuring the data transmission quality. This not only ensures the timely transmission of emergency data but also takes into account the orderly transmission of regular data, improving the data processing capacity and flexibility of the entire system.

[0049] In addition, during the transmission of unmanned boats, the present invention also real-time detects the communication interference distance of adjacent unmanned boats. When the interference distance is less than the preset safety threshold, a dynamic data transmission path planning is performed for the target unmanned boat based on the interference source. This function can effectively address the communication interference problem that occurs during the dynamic driving of unmanned boats and ensure the stability of data transmission. In practical applications, there are frequent ship movements in urban waters, and it is easy to generate communication interference between unmanned boats. The dynamic planning mechanism of the present invention can timely adjust the data transmission path to ensure that data transmission is not interfered, improving the adaptability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] [[ID=II]] Figure 1 is the working principle diagram of the method for data transmission back to shore of the unmanned boat based on urban water area monitoring according to the present invention;

[0051] Figure 2 is the flowchart for planning the data transmission path based on the conflict detection result;

[0052] Figure 3 is the flowchart for planning the data transmission paths of unmanned boats with different priorities;

[0053] Figure 4 is the flowchart for generating the data transmission path of the target unmanned boat. DETAILED DESCRIPTION OF THE INVENTION

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] Please refer to Figures 1-4 , the present invention relates to a method for data transmission of an unmanned surface vehicle based on urban water area monitoring, and the specific implementation steps are as follows:

[0056] Obtain multiple target unmanned surface vehicles, and determine the data collection nodes and data transmission center nodes of each target unmanned surface vehicle from a preset monitoring area map. The monitoring area map covers multiple communication relay nodes located between the data collection nodes and the data transmission center nodes. These communication relay nodes play a crucial bridging role in the data transmission process, capable of expanding the signal coverage range and ensuring stable data transmission.

[0057] For each target unmanned surface vehicle, based on the communication quality indicators of each communication relay node relative to the data collection node and the data transmission center node respectively, select multiple target relay nodes with the optimal communication quality indicators, and generate the data transmission path of the target unmanned surface vehicle according to these target relay nodes. The communication quality indicator comprehensively considers factors such as the signal strength and transmission delay from the data collection node to each communication relay node and from each communication relay node to the data transmission center node. Through the comprehensive evaluation of these factors, the relay nodes most conducive to data transmission can be screened out, and then the optimal communication link from the data collection node to the data transmission center node can be constructed.

[0058] For each target unmanned surface vehicle, obtain its data transmission rate, and based on the sub-link transmission indicators between the target relay nodes included in the data transmission path and this data transmission rate, determine the packet arrival time when the target unmanned surface vehicle passes through multiple target relay nodes. This step helps to accurately master the time nodes during the data transmission process, providing an important basis for subsequent conflict detection and path planning. [[ID=1..16]]

[0059] Mark the packet arrival time for each target relay node in the monitoring area map, thereby obtaining a real-time communication timing diagram. This timing diagram intuitively shows the arrival time of each data packet at different relay nodes, making the entire data transmission process clear at a glance and facilitating subsequent analysis and processing.

[0060] For each target relay node, communication channel conflict detection is performed according to the arrival time of the data packet, and a conflict detection result is obtained. By analyzing the arrival time of the data packet, it is possible to promptly discover whether there are multiple data packets arriving at the same relay node at the same time, that is, a communication channel conflict, so as to take corresponding measures for processing.

[0061] Based on the conflict detection result, a data transmission path is planned to obtain a data feedback plan result. If there is a conflict, the data transmission path will be adjusted and optimized to ensure that the data can be efficiently and stably fed back.

[0062] The technical solution of the present invention will be further described in detail below in conjunction with specific embodiments.

[0063] Embodiment 1: In this embodiment, the method for determining the communication quality index and the process of generating the data transmission path will be described in detail. In an actual urban water area monitoring scenario, it is assumed that there are multiple unmanned surface vehicles performing monitoring tasks, and these unmanned surface vehicles are distributed at different locations. Taking one of the unmanned surface vehicles as an example, first, its data acquisition node and data feedback center node are determined. On the monitoring area map, the data acquisition node is located at the current position of the unmanned surface vehicle, and the data feedback center node may be set at a monitoring station on the shore or other locations. Between the data acquisition node and the data feedback center node, there are numerous communication relay nodes.

[0064] For each communication relay node, its communication quality index needs to be determined. Here, the communication quality index is a comprehensive evaluation value of the signal strength and transmission delay from the data acquisition node to this communication relay node and from this communication relay node to the data feedback center node. The signal strength reflects the strength of the signal during the data transmission process. The stronger the signal, the higher the stability of the data transmission; the transmission delay reflects the time required for the data to be transmitted from one node to another node. The smaller the delay, the higher the efficiency of the data transmission. To determine the communication quality index, it is necessary to obtain the signal strength data from the data acquisition node to each communication relay node and the transmission delay data from the communication relay node to the data feedback center node. These data can be obtained through signal monitoring devices installed on the unmanned surface vehicle, communication relay nodes, and data feedback center nodes. For example, installing a signal strength sensor on the unmanned surface vehicle can monitor the signal strength between it and each communication relay node in real time; setting time recording devices on the communication relay node and the data feedback center node to record the start and end times of data transmission, thereby calculating the transmission delay.

[0065] After obtaining the relevant data of each communication relay node, comprehensively evaluate this data. Suppose there are three communication relay nodes A, B, and C. The signal strength from the data acquisition node to node A is strong, but the transmission delay is large; the signal strength to node B is weak, but the transmission delay is small; the signal strength and transmission delay to node C are at an intermediate level. By comprehensively considering the signal strength and transmission delay and using a certain evaluation method (such as weighted average, although no formula is involved, it can be understood as a comprehensive calculation based on the importance of the two), it is concluded that the communication quality index of node B is the best.

[0066] Next, generate the data transmission path. First, determine multiple adjacent communication nodes adjacent to the data acquisition node, and calculate the communication quality index of each adjacent communication node relative to the data acquisition node and the data backhaul center node. Suppose there are three adjacent communication nodes D, E, and F around the data acquisition node. After calculating their communication quality indexes, determine the node D with the best communication quality index as the first target relay node. Then, starting from node D, determine multiple adjacent communication nodes adjacent to it, and calculate the communication quality indexes of these adjacent communication nodes again. Select the one with the best communication quality index from these nodes as the next target relay node. Continuously repeat this process until the next target relay node determined is the data backhaul center node. In this way, multiple target relay nodes between the data acquisition node and the data backhaul center node are obtained, and these target relay nodes constitute the data transmission path of this unmanned ship. The data transmission path generated in this way can ensure the stability and efficiency of data during transmission to the greatest extent and improve the quality of data backhaul.

[0067] Embodiment 2: This embodiment elaborates in detail the specific process of data transmission path planning based on the conflict detection result. In the urban water area monitoring environment, when each target unmanned ship performs data transmission according to the established data transmission path, it is necessary to detect communication channel conflicts. Suppose at a certain moment, through the monitoring of the packet arrival time, it is found that there are multiple packet arrival time conflicts on the target relay node X. At this time, determine the target relay node X as the conflict relay node.

[0068] Obtain the packet arrival time when the conflict relay node X generates a conflict, and this time range is determined as the conflict period. During this conflict period, the data transmission of multiple target unmanned ships is involved. To reasonably resolve the conflict, it is necessary to determine the data transmission priorities of these target unmanned ships. Suppose the data transmission of unmanned ships M, N, and P is involved during the conflict period. According to actual needs and factors such as the importance of the data (such as the data of the unmanned ship that detects water quality anomalies has a higher priority than the unmanned ship with regular monitoring data), it is determined that the data transmission priority of unmanned ship M is the highest, followed by unmanned ship N, and the lowest is unmanned ship P.

[0069] Plan the data transmission path for the target unmanned ship based on the data transmission priority. First, consider the unmanned ship M with the highest priority. When planning the data transmission path for it, try to avoid passing through the conflicting relay node X again, or adjust its transmission time to avoid the conflict period. For example, it is possible to check whether there are other available relay nodes and construct a new transmission path to ensure the smooth transmission of the data of the unmanned ship M. The same method is used for the unmanned ships N and P. According to their priority order, adjust the transmission path or transmission time in turn. If it is impossible to completely avoid the conflicting relay node X, it is also possible to reasonably allocate the transmission time according to the priority, allowing the unmanned ship with a higher priority to perform data transmission first, and the unmanned ship with a lower priority to wait for a period of time before transmitting. In this way, in the case of communication channel conflicts, the data transmission path can be reasonably planned to ensure the timely backhaul of important data, while minimizing the impact on other data transmissions and improving the reliability and stability of the entire data backhaul system.

[0070] Embodiment 3: In this embodiment, for the case where the target unmanned ship includes different priorities (the first-priority unmanned ship and the second-priority unmanned ship, the data transmission priority of the first-priority unmanned ship is the emergency level, and the data transmission priority of the second-priority unmanned ship is the normal level), the process of planning the data transmission path based on the data transmission priority is described in detail. In the urban water area monitoring task, there are multiple waterborne unmanned ships with different priorities. For example, there is a first-priority unmanned ship A, which is responsible for monitoring possible sudden pollution events, and the data is urgent; there are also multiple second-priority unmanned ships B, C, D, etc., which perform regular water quality, water level and other monitoring work.

[0071] When planning the data transmission path, first determine the data transmission path corresponding to the second-priority unmanned ship based on the order of the emergency level and the normal level. Taking the unmanned ship B as an example, select the target relay node according to the communication quality index of the communication relay node, and construct a data transmission path from its data acquisition node to the data backhaul center node. During the path construction process, calculate the communication quality index of each adjacent communication node relative to the data acquisition node and the data backhaul center node, and select the optimal node as the relay node on the path until reaching the data backhaul center node.

[0072] Then, based on the real-time communication timing diagram, obtain the packet arrival times of the unmanned ship B at each target relay node in the corresponding data transmission path. Assume that the data transmission path of the unmanned ship B includes relay nodes Y, Z, and W. By checking the real-time communication timing diagram, the specific times when the packet arrives at nodes Y, Z, and W can be determined. For example, the time when the packet arrives at node Y is T1, the time when it arrives at node Z is T2, and the time when it arrives at node W is T3.

[0073] Next, based on the arrival times of these data packets, combined with the real-time communication timing diagram, perform data transmission path planning for unmanned ship B. If it is found during the planning process that a communication channel conflict may occur at a certain relay node, handle it according to the priority of the unmanned ship. Since unmanned ship B is a second-priority unmanned ship, if a data transmission conflict occurs with a first-priority unmanned ship, the data transmission of the first-priority unmanned ship should be guaranteed first. For example, if it is found that node Z may conflict with the data transmission of unmanned ship A at a certain moment, the transmission path of unmanned ship B can be adjusted at this time to bypass node Z, or its transmission time can be adjusted to avoid the conflict moment. In this way, in the case of unmanned ships with different priorities, reasonably plan the data transmission path to ensure that emergency data can be transmitted back preferentially and stably, while taking into account the transmission requirements of regular data and improving the performance of the entire data backhaul system.

[0074] Embodiment 4: This embodiment further refines the process of calculating the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data backhaul center node, and the specific operation of determining the first target relay node based on the communication quality indicators. In the urban water area monitoring scenario, when an unmanned ship needs to determine the data transmission path, it is necessary to calculate and analyze the communication quality indicators of adjacent communication nodes.

[0075] Taking an unmanned ship as an example, assume that there are multiple adjacent communication nodes around its data acquisition node. First, calculate the first signal strength indicator of the distance between each adjacent communication node and the data acquisition node. In actual operation, these data can be obtained through a signal strength detection device installed on the unmanned ship. This device can measure the signal strength between the unmanned ship and each adjacent communication node in real time. For example, for adjacent communication nodes Q, R, and S, through the detection device, the signal strength between the unmanned ship and node Q is a certain value (represented by a specific strength value, such as 50 dBm, only for example), the signal strength with node R is 45 dBm, and the signal strength with node S is 40 dBm.

[0076] At the same time, calculate the second transmission delay indicator of the distance between each adjacent communication node and the data backhaul center node. This can be achieved by setting time recording devices on the communication node and the data backhaul center node. When data is transmitted from an adjacent communication node to the data backhaul center node, record the start and end times of data transmission, so as to calculate the transmission delay. Assume that the transmission delay of node Q transmitting data to the data backhaul center node is 30 ms, the delay of node R is 25 ms, and the delay of node S is 20 ms.

[0077] For each adjacent communication node, the first signal strength index and the second transmission delay index are comprehensively evaluated to obtain a communication quality index. Here, a weighted method is adopted (without involving formulas, understood as a comprehensive consideration based on the importance of the two). Assuming that the weight of the signal strength is relatively large because a stronger signal helps to ensure the stability of data transmission. After comprehensive evaluation, it is concluded that the communication quality index of node R is the best.

[0078] Next, determine the first target relay node. Store the communication quality indexes corresponding to multiple adjacent communication nodes in a communication quality evaluation list. For example, record the communication quality indexes of nodes Q, R, and S in the list in sequence. Then, sort the communication quality indexes in descending order in the communication quality evaluation list to obtain a sorting result. From the sorting result, it can be seen that the communication quality index of node R is the best. Therefore, node R is determined as the first target relay node. Through this detailed calculation and screening process, the node with the best communication quality can be accurately selected as the first target relay node on the data transmission path, laying a foundation for constructing a stable and efficient data transmission path in the future.

[0079] Example 5: This example details the process of dynamic data transmission path planning when communication interference occurs after each target unmanned ship starts transmission according to the data backhaul planning result. In urban water area monitoring, multiple unmanned surface vessels perform data transmission according to the established data backhaul planning result. During the transmission process, it is necessary to detect the communication interference distance between the target unmanned ship and at least one adjacent target unmanned ship in real time.

[0080] Suppose at a certain moment, unmanned ship E is performing data transmission. Through a distance detection device (such as a radar, etc.) installed on unmanned ship E, the distance between it and adjacent unmanned ships is monitored in real time. When it is found that the communication interference distance between unmanned ship E and adjacent unmanned ship F is less than the preset safety threshold, unmanned ship F is regarded as the interference source.

[0081] At this time, based on the interference source, dynamic data transmission path planning is performed for unmanned ship E. First, analyze the current data transmission path of unmanned ship E to check which relay nodes on the path may be interfered by unmanned ship F. Suppose the data transmission path of unmanned ship E includes relay nodes G, H, and I. After analysis, it is found that nodes G and H may be interfered by unmanned ship F.

[0082] Then, check whether there are other available relay nodes to avoid interference. On the monitoring area map, standby relay nodes J and K are found. Recalculate the communication quality indexes from the data acquisition node of unmanned ship E through nodes J and K to the data backhaul center node, and evaluate the feasibility of this new path.

[0083] If the communication quality index of the new path meets the requirements, then this new path is determined as the updated data transmission path of the unmanned ship E. For example, after calculation and evaluation, it is determined that the path from the data acquisition node of the unmanned ship E through nodes J and K to the data backhaul center node can effectively avoid the interference of the unmanned ship F and has stable communication quality, so this path is used as the updated data transmission path of the unmanned ship E. Through this dynamic data transmission path planning method, in the case of communication interference, the data transmission path of the unmanned ship can be adjusted in time to ensure the stability and reliability of data transmission and ensure that the urban water area monitoring data can be successfully backhauled.

[0084] Embodiment 6: This embodiment describes the process in which the generation module dynamically adjusts the communication quality index of the communication relay node according to the real-time environment monitoring data and regenerates the data transmission path of the target unmanned ship based on the updated communication quality index. During the urban water area monitoring process, the environment is constantly changing, and these changes will affect the communication quality of the communication relay node. For example, changes in weather conditions (such as heavy rain, strong wind, etc.) may cause a decrease in signal strength and an increase in transmission delay; an increase in the number of ships in the water area may also cause signal interference and affect the communication quality.

[0085] Suppose that during a certain period of time, strong wind weather appears in the urban water area. The environmental monitoring devices (such as wind speed sensors, signal interference monitors, etc.) installed on each communication relay node and unmanned ship will collect environmental data in real time and transmit this data to the generation module. The generation module dynamically adjusts the communication quality index of the communication relay node according to these real-time environment monitoring data. For the communication relay node that is greatly affected by the strong wind, its signal strength may decrease and the transmission delay may increase, and the generation module will correspondingly adjust its communication quality index to reduce its comprehensive evaluation value.

[0086] Taking an unmanned ship as an example, its original data transmission path passed through relay nodes L, M, and N. After the environment changed, the generation module re-evaluated the path based on the updated communication quality metrics. When calculating the communication quality metrics of the communication nodes adjacent to the data acquisition node, it was found that due to the environmental change, the communication quality metric of node M, which originally had good communication quality, decreased, while the communication quality metric of another node O that was not selected before increased. Therefore, based on the new communication quality metrics, the target relay nodes were re-determined. Starting from the data acquisition node, the node with the optimal communication quality metric was selected as the first target relay node, and then the subsequent target relay nodes were determined in sequence until the data backhaul central node was reached. Finally, a new data transmission path was constructed, which might pass through nodes L, O, and N. By dynamically adjusting the communication quality metrics according to the real-time environmental monitoring data and regenerating the data transmission path in this way, the data transmission of the unmanned ship on water can better adapt to the complex and changeable urban water environment, improve the efficiency and stability of data backhaul, and ensure that the monitoring data can be accurately and timely transmitted to the data backhaul center.

[0087] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0088] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for data transmission of an unmanned surface vehicle based on urban water area monitoring, characterized in that The method includes: Obtaining a plurality of target unmanned vessels, and determining a data collection node and a data transmission center node for each of the target unmanned vessels from a preset monitoring area map, wherein the monitoring area map includes a plurality of communication relay nodes located between the data collection node and the data transmission center node; For each of the target unmanned vessels, selecting a plurality of target relay nodes with the optimal communication quality index based on the communication quality indexes of each of the communication relay nodes relative to the data collection node and the data transmission center node, and generating a data transmission path for the target unmanned vessel according to the plurality of target relay nodes; For each of the target unmanned vessels, obtaining the data transmission rate of the target unmanned vessel, and determining the packet arrival time when the target unmanned vessel passes through a plurality of target relay nodes based on the sub-link transmission indexes between the target relay nodes included in the data transmission path and the data transmission rate; Marking the packet arrival time for each of the target relay nodes in the monitoring area map to obtain a real-time communication timing diagram; For each of the target relay nodes, detecting communication channel conflicts according to the packet arrival time to obtain a conflict detection result; Performing data transmission path planning based on the conflict detection result to obtain a data transmission back planning result.

2. The method for transmitting data of an unmanned surface vessel based on urban water area monitoring according to claim 1, wherein, The communication quality index is a comprehensive evaluation value of the signal strength and transmission delay from the data collection node to each communication relay node and from each communication relay node to the data transmission center node for each communication relay node; the data transmission path is a planned path from the data collection node to the data transmission center node, and is the optimal communication link composed of the selected plurality of target relay nodes.

3. The method for data transmission of an unmanned surface vehicle based on urban water area monitoring according to claim 1, characterized in that, The performing data transmission path planning based on the conflict detection result to obtain a data transmission back planning result includes: when the conflict detection result indicates that there are conflicts in the packet arrival times of the plurality of packets included in the target relay node, determining the target relay node as a conflict relay node; obtaining the packet arrival time of the packet generating the conflict of the conflict relay node as a conflict period, and determining the data transmission priorities of the plurality of target unmanned vessels corresponding to the conflict period; performing data transmission path planning on the target unmanned vessels based on the data transmission priorities to obtain a data transmission back planning result.

4. The method for data transmission of the unmanned surface vessel based on urban water area monitoring according to claim 1, characterized in that The target unmanned vessels include first-priority unmanned vessels and second-priority unmanned vessels, the data transmission priority of the first-priority unmanned vessels is the emergency level, and the data transmission priority of the second-priority unmanned vessels is the normal level; The performing data transmission path planning on the target unmanned vessels based on the data transmission priorities to obtain a data transmission back planning result includes: Determining the data transmission path corresponding to the second-priority unmanned vessels based on the order of the emergency level and the normal level; Based on the real-time communication timing diagram, obtaining the packet arrival times of the second-priority unmanned vessels at each target relay node in the corresponding data transmission path; Based on the arrival time of the data packet, combined with the real-time communication timing diagram, perform data transmission path planning for the second-priority unmanned vessel to obtain a data backhaul planning result.

5. The method for transmitting data of an unmanned surface vessel based on urban water area monitoring according to claim 1, wherein For each of the target unmanned vessels, select multiple target relay nodes with the best communication quality indicators based on the communication quality indicators of each of the communication relay nodes relative to the data acquisition node and the data backhaul central node, and generate a data transmission path for the target unmanned vessel, including: For each of the target unmanned vessels, determine multiple adjacent communication nodes adjacent to the data acquisition node; Calculate the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data backhaul central node, and determine the first target relay node with the best communication quality indicator from the multiple adjacent communication nodes based on the multiple communication quality indicators; Taking the first target relay node as the starting point, determine multiple adjacent communication nodes adjacent to the target relay node, calculate the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data backhaul central node, and determine the next target relay node with the best communication quality indicator from the multiple adjacent communication nodes adjacent to the target relay node based on the multiple communication quality indicators; Repeat the steps of determining multiple adjacent communication nodes adjacent to the target relay node, calculating the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data backhaul central node, and determining the next target relay node with the best communication quality indicator from the multiple adjacent communication nodes adjacent to the target relay node until the next target relay node is determined to be the data backhaul central node to obtain multiple target relay nodes between the data acquisition node and the data backhaul central node; Generate a data transmission path for the target unmanned vessel based on the multiple target relay nodes.

6. The method for data transmission back of the unmanned surface vessel based on urban water area monitoring according to claim 5, wherein The calculation of the communication quality indicators of each adjacent communication node relative to the data acquisition node and the data backhaul central node includes: Calculate the first signal strength indicator of the distance between each adjacent communication node and the data acquisition node, and the second transmission delay indicator of the distance between each adjacent communication node and the data backhaul central node respectively; For each adjacent communication node, use the weighted value of the first signal strength indicator and the second transmission delay indicator as the communication quality indicator of the adjacent communication node relative to the data acquisition node and the data backhaul central node.

7. The method for data transmission back of the unmanned surface vessel based on urban water area monitoring according to claim 5, wherein The determination of the first target relay node with the best communication quality indicator from the multiple adjacent communication nodes based on the multiple communication quality indicators includes: Store the multiple communication quality indicators corresponding to the multiple adjacent communication nodes in a communication quality evaluation list, and perform a descending order sorting on the communication quality indicators in the communication quality evaluation list to obtain a sorting result; Based on the sorting result, determine the adjacent communication node corresponding to the optimal communication quality index as the first target relay node.

8. The method for data transmission back of the unmanned surface vessel based on urban water area monitoring according to claim 1, wherein, After performing data transmission path planning based on the conflict detection result and obtaining the data feedback planning result, it further includes: When each of the target unmanned vessels starts transmitting according to the data feedback planning result, for each of the target unmanned vessels, real-time detect the communication interference distance between the target unmanned vessel and at least one adjacent target unmanned vessel; When there is a situation where the communication interference distance between the target unmanned vessel and the adjacent target unmanned vessel is less than the preset safety threshold, regard the adjacent target unmanned vessel as an interference source, and perform dynamic data transmission path planning for the target unmanned vessel based on the interference source to obtain the updated data transmission path of the target unmanned vessel.

9. An underwater unmanned ship data transmission device based on urban water area monitoring, characterized in that, The device includes: An acquisition module, configured to acquire a plurality of target unmanned vessels, and determine a data acquisition node and a data feedback center node for each of the target unmanned vessels from a preset monitoring area map, where the monitoring area map includes a plurality of communication relay nodes located between the data acquisition node and the data feedback center node; A generation module, configured to, for each of the target unmanned vessels, select a plurality of target relay nodes with the optimal communication quality index based on the communication quality indexes of each of the communication relay nodes relative to the data acquisition node and the data feedback center node, and generate a data transmission path for the target unmanned vessel according to the plurality of target relay nodes; wherein, the communication quality index is a comprehensive evaluation value of the signal strength and transmission delay from the data acquisition node to each communication relay node and from each communication relay node to the data feedback center node for each communication relay node; the data transmission path is a planned path from the data acquisition node to the data feedback center node, and is the optimal communication link composed of the selected plurality of target relay nodes; A determination module, configured to, for each of the target unmanned vessels, obtain the data transmission rate of the target unmanned vessel, and determine the packet arrival time when the target unmanned vessel passes through a plurality of target relay nodes based on the sub-link transmission index between the target relay nodes included in the data transmission path and the data transmission rate; A marking module, configured to mark the packet arrival time for each of the target relay nodes in the monitoring area map to obtain a real-time communication timing diagram; A detection module, configured to, for each of the target relay nodes, detect communication channel conflicts according to the packet arrival time to obtain a conflict detection result; A planning module, configured to perform data transmission path planning based on the conflict detection result to obtain a data feedback planning result; the performing data transmission path planning based on the conflict detection result to obtain a data feedback planning result includes: when the conflict detection result indicates that there are conflicts in the arrival times of multiple data packets included in the target relay node, determining the target relay node as a conflict relay node; obtaining the arrival time of the data packet that generates the conflict of the conflict relay node as a conflict period, and determining the data transmission priorities of multiple target unmanned boats corresponding to the conflict period; performing data transmission path planning on the target unmanned boats based on the data transmission priorities to obtain a data feedback planning result.

10. The data transmission device for an unmanned surface vessel based on urban water area monitoring according to claim 9, characterized in that, The generating module is further configured to: Dynamically adjust the communication quality index of the communication relay node according to real-time environment monitoring data, and regenerate the data transmission path of the target unmanned boat based on the updated communication quality index.

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