Aviation sonar buoy networked cooperative detection and communication method

Abstract

The invention relates to the technical field of sonar detection communication, in particular to an aviation sonar buoy networked cooperative detection and communication method, which comprises the following steps that a plurality of sonar buoys are arranged in a target sea area according to a preset rule, and the distance between the buoys is dynamically adjusted according to a detection area and target characteristics; the buoy nodes carry out self-adaptive networking through the wireless communication module, and the connection relation between buoys is dynamically adjusted according to signal strength, delay and electric quantity parameters, so that an optimized communication network structure is formed; the buoy works cooperatively through a built-in detection module, and sonar detection data is shared in real time; the buoy network adopts a multi-path transmission strategy and transmits detection data to receiving equipment through a plurality of communication paths, so that the influence of a single-path fault on data transmission is reduced; and fault detection and self-adaptive repair are carried out. According to the invention, the communication stability of the buoy network is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of sonar detection and communication, and in particular to a networked collaborative detection and communication method for aviation sonar buoys. Background Art

[0002] Sonar technology is an important means of ocean exploration and is widely used in the fields of marine resource exploration, environmental monitoring, submarine detection, etc. However, existing sonar detection systems mostly use a single buoy or single-point detection mode, with limited coverage, and the detection results are easily interfered by marine environmental factors. At the same time, traditional sonar buoys mostly rely on single-path communication, which is susceptible to interference in the complex communication environment at sea, and data loss or delay often occurs. Especially in the multi-buoy collaborative detection scenario, the lack of communication stability and data transmission efficiency seriously limits the overall performance of the system.

[0003] In addition, existing sonar buoy equipment is easily affected by factors such as equipment power and failure during operation, resulting in interruption of detection missions. The failure of a single buoy often makes the detection mission impossible to continue, and there is a lack of adaptive fault tolerance mechanism. Summary of the invention

[0004] The present invention provides a networked collaborative detection and communication method for aviation sonar buoys.

[0005] The networked collaborative detection and communication method of aviation sonar buoys comprises the following steps:

[0006] S1, construction of sonar buoy deployment network: multiple sonar buoys are deployed in the target sea area according to predetermined rules. The spacing between the buoys is dynamically adjusted according to the detection area and target characteristics to ensure seamless coverage and maximize detection effect;

[0007] S2, adaptive networking and communication optimization: buoy nodes are adaptively networked through wireless communication modules, and the connection relationship between buoys is dynamically adjusted according to signal strength, delay and power parameters to form an optimized communication network structure;

[0008] S3, collaborative detection and data sharing: buoys work together through built-in detection modules, share sonar detection data in real time, and comprehensively evaluate the position and speed information of marine targets;

[0009] S4, multi-path data transmission and backup: The buoy network adopts a multi-path transmission strategy to transmit the detection data to the receiving device through multiple communication paths, reducing the impact of a single path failure on data transmission;

[0010] S5, fault detection and adaptive repair: When a buoy node encounters a communication failure or low battery, it automatically detects and reconfigures the network topology to ensure that the detection mission is not interrupted.

[0011] Optionally, in the step of constructing the sonar buoy network, the spacing of the buoys is dynamically calculated based on a preset mathematical model. The mathematical model takes parameters such as the buoy's detection radius, target movement speed, and ocean environment noise level as input variables, and solves the optimal spacing configuration function to ensure that there are no blind spots in the detection area and maximize the effective detection range of the buoy.

[0012] Optionally, in the adaptive networking and communication optimization steps, the buoy node calculates the optimal network topology by comparing the signal strength, data transmission delay and remaining power of each adjacent node during networking through a heuristic algorithm, thereby ensuring communication stability and optimal utilization of resources and avoiding excessive loading of a single node.

[0013] Optionally, in the collaborative detection and data sharing steps, the collaborative detection of the buoy nodes is run based on a distributed computing framework. Through real-time transmission and summary analysis of the detection data of each buoy, Kalman filtering is used in combination with historical detection data to perform multi-level prediction and correction of the target's position, speed and motion trajectory, so as to improve the detection accuracy and response speed.

[0014] Optionally, in the multi-path data transmission and backup steps, the buoy node communicates using multi-band frequency hopping technology, which specifically includes sending detection data in the high frequency band and the low frequency band at the same time, and dynamically switching the frequency band during the communication process to avoid signal interference and path blocking, while ensuring high reliability and low latency of data transmission through multi-path redundant transmission.

[0015] Optionally, in the fault detection and adaptive repair steps, the buoy node continuously monitors its own operating status, including power level, communication status, and hardware fault detection, through embedded sensors, and automatically sends a fault alarm signal to adjacent nodes when a fault is detected. The adjacent nodes readjust the network topology according to a preset network reconstruction algorithm to ensure that the detection task of the faulty node is taken over by other nodes, thereby ensuring the continuity and stability of the detection network.

[0016] Optionally, an intelligent power management unit is integrated into the buoy node to monitor the battery status of the buoy node in real time, optimize the detection and communication working mode of the buoy through adaptive energy allocation, give priority to the normal operation of the core detection function when the buoy is low on power, and extend the service life of the buoy by reducing the communication frequency and shutting down secondary sensor modules.

[0017] Optionally, the heuristic algorithm calculates the optimal network topology structure specifically including:

[0018] The heuristic algorithm calculates the optimal network topology structure using the shortest path algorithm, based on distance, signal strength, transmission delay and remaining power heuristic calculation, taking into account all factors to calculate the optimal path weight in the network;

[0019] Let N be the set of nodes in the sonar buoy network, i and j be two nodes in the network, and w ij is the connection weight from node i to node j, and the calculation formula is:

[0020] Among them, d ij is the physical distance between node i and node j, S ij is the signal strength between node i and node j, t ij is the transmission delay between node i and node j, E j is the remaining power of node j, α, β, γ, δ are the importance weights of distance, signal strength, transmission delay and remaining power respectively, and α+β+γ+δ=1.

[0021] Beneficial effects of the present invention:

[0022] The present invention realizes seamless coverage of the detection area by constructing a dynamic and adaptive sonar buoy network, calculates the layout spacing between buoys, ensures that the sonar buoys can adaptively adjust their positions according to the ocean environment and target characteristics, avoids the generation of detection blind spots, and through collaborative detection and data sharing, multiple buoy nodes can simultaneously detect the same target and comprehensively evaluate its position and motion trajectory, significantly improving the detection accuracy. It is particularly suitable for multi-target detection in large sea areas, and solves the problems of insufficient detection coverage and limited accuracy of a single buoy in the prior art.

[0023] The present invention calculates the optimal network topology through a heuristic algorithm, comprehensively considers multiple factors such as the distance between buoy nodes, signal strength, transmission delay, and node power, effectively improves the communication stability of the buoy network, and introduces a multi-path data transmission and backup mechanism to ensure that when a certain communication path fails, data can still be transmitted to the receiving end through other paths to avoid data loss or delay, significantly improves the reliability and efficiency of detection data transmission, and solves the problem that single-path communication is susceptible to interference in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0027] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0028] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0029] like Figure 1 As shown, the networked collaborative detection and communication method of aviation sonar buoys includes the following steps:

[0030] S1, construction of sonar buoy deployment network: multiple sonar buoys are deployed in the target sea area according to predetermined rules. The spacing between the buoys is dynamically adjusted according to the detection area and target characteristics to ensure seamless coverage and maximize detection effect;

[0031] S2, adaptive networking and communication optimization: buoy nodes are adaptively networked through wireless communication modules, and the connection relationship between buoys is dynamically adjusted according to signal strength, delay and power parameters to form an optimized communication network structure;

[0032] S3, collaborative detection and data sharing: buoys work together through built-in detection modules, share sonar detection data in real time, and comprehensively evaluate the position and speed information of marine targets;

[0033] S4, multi-path data transmission and backup: The buoy network adopts a multi-path transmission strategy to transmit the detection data to the receiving device through multiple communication paths, reducing the impact of a single path failure on data transmission;

[0034] S5, fault detection and adaptive repair: When a buoy node encounters a communication failure or low battery, it automatically detects and reconfigures the network topology to ensure that the detection mission is not interrupted.

[0035] In the construction step of the sonar buoy network, the spacing of the buoys is dynamically calculated based on a preset mathematical model. The mathematical model takes parameters such as the buoy's detection radius, target movement speed, and ocean environment noise level as input variables. By solving the optimal spacing configuration function, it ensures that there are no blind spots in the detection area and maximizes the effective detection range of the buoy.

[0036] In the adaptive networking and communication optimization steps, the buoy node compares the signal strength, data transmission delay and remaining power of each adjacent node when networking, and calculates the optimal network topology through a heuristic algorithm to ensure communication stability and optimal utilization of resources, avoiding excessive loading of a single node.

[0037] In the collaborative detection and data sharing step, the collaborative detection of buoy nodes is run based on a distributed computing framework. Through real-time transmission and summary analysis of the detection data of each buoy, Kalman filtering is used in combination with historical detection data to perform multi-level prediction and correction of the target's position, speed and motion trajectory, in order to improve the detection accuracy and response speed.

[0038] In the multi-path data transmission and backup steps, the buoy node's communication adopts multi-band frequency hopping technology, which specifically includes sending detection data in the high frequency band and the low frequency band at the same time, and dynamically switching the frequency band during the communication process to avoid signal interference and path blocking. At the same time, multi-path redundant transmission is used to ensure high reliability and low latency of data transmission.

[0039] In the fault detection and adaptive repair steps, the buoy node continuously monitors its own operating status through embedded sensors, including power level, communication status, and hardware fault detection, and automatically sends a fault alarm signal to adjacent nodes when a fault is detected. The adjacent nodes readjust the network topology according to the preset network reconstruction algorithm to ensure that the detection task of the faulty node is taken over by other nodes, thereby ensuring the continuity and stability of the detection network.

[0040] The buoy node has an integrated intelligent power management unit to monitor the battery status of the buoy node in real time, optimize the detection and communication working modes of the buoy through adaptive energy allocation, prioritize the normal operation of the core detection function when the buoy is low on power, and extend the service life of the buoy by reducing the communication frequency and shutting down secondary sensor modules.

[0041] The heuristic algorithm calculates the optimal network topology structure specifically including:

[0042] The heuristic algorithm calculates the optimal network topology structure using the shortest path algorithm, based on distance, signal strength, transmission delay and remaining power heuristic calculation, taking into account all factors to calculate the optimal path weight in the network;

[0043] Let N be the set of nodes in the sonar buoy network, i and j be two nodes in the network, and w ij is the connection weight from node i to node j, and the calculation formula is:

[0044] Among them, d ij is the physical distance between node i and node j, S ij is the signal strength between node i and node j, t ij is the transmission delay between node i and node j, E j is the remaining power of node j, α, β, γ, δ are the importance weights of distance, signal strength, transmission delay and remaining power respectively, and α+β+γ+δ=1;

[0045] d ij : The longer the physical distance, the higher the connection cost, so the weight increases;

[0046] The higher the signal strength, the better the connection quality, so the weight is lower;

[0047] t ij : The lower the transmission delay, the faster the communication speed, the better the connection quality, and the lower the weight;

[0048] The higher the remaining power of node j, the stronger the connection stability and the lower the weight.

[0049] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0050] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A networked collaborative detection and communication method for aviation sonar buoys, characterized in that: The following steps are involved: S1, construction of sonar buoy deployment network: multiple sonar buoys are deployed in the target sea area according to predetermined rules. The spacing between the buoys is dynamically adjusted according to the detection area and target characteristics to ensure seamless coverage and maximize detection effect; S2, adaptive networking and communication optimization: buoy nodes are adaptively networked through wireless communication modules, and the connection relationship between buoys is dynamically adjusted according to signal strength, delay and power parameters to form an optimized communication network structure; S3, collaborative detection and data sharing: buoys work together through built-in detection modules, share sonar detection data in real time, and comprehensively evaluate the position and speed information of marine targets; S4, multi-path data transmission and backup: The buoy network adopts a multi-path transmission strategy to transmit the detection data to the receiving device through multiple communication paths, reducing the impact of a single path failure on data transmission; S5, fault detection and adaptive repair: When a buoy node encounters a communication failure or low battery, it automatically detects and reconfigures the network topology to ensure that the detection mission is not interrupted.

2. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: In the steps of constructing the sonar buoy network, the spacing of the buoys is dynamically calculated based on a preset mathematical model. The mathematical model takes parameters such as the buoy's detection radius, target movement speed, and ocean environment noise level as input variables. By solving the optimal spacing configuration function, it ensures that there are no blind spots in the detection area and maximizes the effective detection range of the buoy.

3. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: In the adaptive networking and communication optimization steps, the buoy node compares the signal strength, data transmission delay and remaining power of each adjacent node when networking, and calculates the optimal network topology through a heuristic algorithm to ensure communication stability and optimal utilization of resources, avoiding excessive loading of a single node.

4. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: In the collaborative detection and data sharing steps, the collaborative detection of buoy nodes is run based on a distributed computing framework. Through real-time transmission and summary analysis of the detection data of each buoy, Kalman filtering is used in combination with historical detection data to perform multi-level prediction and correction of the target's position, speed and motion trajectory, so as to improve the detection accuracy and response speed.

5. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: In the multi-path data transmission and backup steps, the buoy node communicates using multi-band frequency hopping technology, which specifically includes sending detection data in the high frequency band and the low frequency band at the same time, and dynamically switching the frequency band during the communication process to avoid signal interference and path blocking, while ensuring high reliability and low latency of data transmission through multi-path redundant transmission.

6. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: In the fault detection and adaptive repair steps, the buoy node continuously monitors its own operating status through embedded sensors, including power level, communication status, and hardware fault detection, and automatically sends a fault alarm signal to adjacent nodes when a fault is detected. The adjacent nodes readjust the network topology according to the preset network reconstruction algorithm to ensure that the detection task of the faulty node is taken over by other nodes, thereby ensuring the continuity and stability of the detection network.

7. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 1, characterized in that: The buoy node has an integrated intelligent power management unit to monitor the battery status of the buoy node in real time, optimize the detection and communication working modes of the buoy through adaptive energy allocation, prioritize the normal operation of the core detection function when the buoy is low on power, and extend the service life of the buoy by reducing the communication frequency and shutting down secondary sensor modules.

8. The method for networked collaborative detection and communication of aviation sonar buoys according to claim 3, characterized in that: The heuristic algorithm calculates the optimal network topology structure specifically including: The heuristic algorithm calculates the optimal network topology structure using the shortest path algorithm, based on distance, signal strength, transmission delay and remaining power heuristic calculation, taking into account all factors to calculate the optimal path weight in the network; Let N be the set of nodes in the sonar buoy network, i and j be two nodes in the network, and w ij is the connection weight from node i to node j, and the calculation formula is: Among them, d ij is the physical distance between node i and node j, S ij is the signal strength between node i and node j, t ij is the transmission delay between node i and node j, E j is the remaining power of node j, α, β, γ, δ are the importance weights of distance, signal strength, transmission delay and remaining power respectively, and α+β+γ+δ=1.

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