A method and system for low-altitude wind speed networking based on unmanned aerial vehicle observation

Abstract

The application relates to the technical field of unmanned aerial vehicle networking, in particular to a medium and low altitude wind speed networking method and system based on unmanned aerial vehicle observation. The method comprises the following steps: setting multiple inspection sub-devices based on an expected observation task; obtaining feedback data packets of the inspection sub-devices, and setting an operation networking strategy according to the feedback data packets; obtaining observation data packets according to the operation networking strategy, and constructing a first four-dimensional wind field according to the observation data packets; periodically correcting networking communication parameters when the unmanned aerial vehicle group cooperatively observes by establishing multiple time intervals, improving the networking communication efficiency and recombination ability of the unmanned aerial vehicle group, and improving the wind field observation efficiency under medium and low wind speed; constructing a double communication structure through local networking, improving the communication efficiency and data processing efficiency of each unmanned aerial vehicle, and reducing the interference of single unmanned aerial vehicle failure on the overall system. The method realizes continuous and gridding detection of medium and low altitude wind speed.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) networking technology, and in particular to a networking method and system for low- and medium-altitude wind speeds based on UAV observation. Background Technology

[0002] Mid- and low-altitude wind field detection is crucial for meteorology, aviation, and other fields. Traditional observation methods, such as weather towers and wind-measuring balloons, suffer from high costs, poor flexibility, and limited coverage, making it difficult to achieve wide-area, high-precision monitoring. Using multiple drones for networked collaborative observation is an inevitable trend. However, achieving stable and efficient multi-drone networking faces a core challenge—the bottleneck of communication networking technology.

[0003] Most existing drones adopt a "star" networking method that communicates directly with ground stations. This method has exposed obvious defects in network observation: the drone's operating radius is strictly limited by the signal coverage of the ground station, and it is easy to lose contact at long distances or in complex terrain; the centralized network structure is rigid, and once the ground station fails or individual nodes go out, the entire network is easily paralyzed, lacking self-reorganization capability; all data must be relayed through the ground station, creating a communication bottleneck, which cannot meet the timeliness requirements for real-time processing and display of wind field data, and lacks low-latency direct communication links between drones, making it difficult for drone swarms to achieve real-time data sharing and dynamic collaborative path planning. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for networking low- and medium-altitude wind speeds based on UAV observation in order to solve the above-mentioned technical problems, thereby improving the networking communication efficiency and wind field observation efficiency of UAVs.

[0005] In some embodiments of this application, by establishing multiple time intervals, the networking communication parameters are periodically corrected when the UAV swarm conducts collaborative observation, thereby improving the networking communication efficiency and reorganization capability of the UAV swarm and improving the wind field observation efficiency under medium and low wind speeds.

[0006] In some embodiments of this application, a dual communication structure is constructed through local networking to improve the communication efficiency and data processing efficiency of each UAV, and reduce the interference of a single UAV failure on the overall system. This enables continuous and gridded detection of low- and mid-altitude wind speeds.

[0007] In some embodiments of this application, a method for networking mid-to-low altitude wind speeds based on UAV observations is provided, including: Multiple inspection sub-equipment are set up based on the expected observation tasks; Obtain feedback data packets from each inspection sub-device, and set the network strategy based on the feedback data packets; Observation data packets are obtained according to the network operation strategy, and a first-level four-dimensional wind field is constructed based on the observation data packets. This includes setting up multiple inspection sub-devices, including: Establish a sequence A of sub-equipment to be inspected, A = (a1, a2, ..., a3) i …a n ), where a i Let be the i-th inspection sub-device; n is the number of inspection sub-devices.

[0008] In some embodiments of this application, a network strategy is set, including: A first-level inspection cycle is generated based on the expected observation tasks; The expected flight trajectory of each inspection sub-device is obtained based on all feedback data packets; The observed fluctuation value b is generated based on all expected flight trajectories. b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; The first-level inspection cycle is divided according to the observed fluctuation value b, and the time interval sequence T is set according to the division result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. Generate network sub-strategies for each time interval in sequence; Configure and run the network strategy according to all network sub-strategies.

[0009] In some embodiments of this application, network sub-policies for each time interval are generated sequentially, including: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, a is set sequentially. i For target sub-device; Generate the network evaluation value c of the target sub-device within the target time interval; Generate the network evaluation value of each inspection sub-device in sequence; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; Preset network evaluation threshold C1; If c i >C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; generating a plurality of device subsets according to all primary anchor devices within a target time interval; generating a networking sub-strategy for the target time interval according to all the device subsets.

[0010] In some embodiments of the present application, generating a networking evaluation value c of a target sub-device within the target time interval comprises: c=e* β i *s i ; e=U1* p i ; wherein e is a networking compensation coefficient; θ1 is the number of networking indicators; β i is the influence factor of the i-th networking indicator; s i is the reference value of the i-th networking indicator of the target sub-device within the target time interval; U1 is a preset first conversion coefficient; p i is the association value between the target sub-device and the i-th inspection sub-device within the target time interval.

[0011] In some embodiments of the present application, setting an operating networking strategy according to all the networking sub-strategies comprises: establishing a networking sub-strategy sequence W, W=(w1, w2...w i ...w m ), wherein w i is the networking sub-strategy of the i-th time interval; m is the number of time intervals; sequentially setting w according to the networking sub-strategy sequence W i as a target sub-strategy; generating an adjustment fluctuation value d of the target sub-strategy; d=η1*Q1+η2*Q2; wherein η1 is a preset first weight coefficient; η2 is a preset second weight coefficient; Q1 is a first fluctuation reference value of the target sub-strategy generated based on the networking sub-strategy sequence; Q2 is a second fluctuation value of the target sub-strategy generated based on the networking sub-strategy sequence; presetting an adjustment fluctuation value threshold D1; if d>D1, generating a primary correction instruction for the target sub-strategy, and generating a primary networking strategy according to the correction result; if d<D1, setting the target sub-strategy as the primary networking strategy; generating the operating networking strategy according to all the primary networking strategies.

[0012] In some embodiments of the present application, the method further comprises: presetting a plurality of monitoring time nodes; constructing a primary anchor device sequence A1 of the current monitoring time node; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; Obtain the monitoring data packets of the target anchoring device: Generate the operational deviation value f of the target anchoring device; Preset operating deviation threshold F1; If f > F1, a first-level correction instruction is generated at the current monitoring time node; The operating deviation values ​​of each primary anchoring device are generated sequentially; Determine whether a secondary correction instruction should be generated at the current monitoring time point based on all operational deviation values.

[0013] In some embodiments of this application, generating the operating deviation value f of the target anchoring device includes: f=g*[ β i *j i ]; g=U2*[ µ i *k i ]; Where g is the deviation compensation coefficient; θ1 is the number of network indicators; β i Let j be the influencing factor of the i-th networking index; i It is the deviation value of the i-th networking index of the target anchoring device generated based on the monitoring data packet; U2 is the preset second conversion coefficient; The number of associated sub-devices for the target anchoring device; µ i Let k be the influence factor of the i-th associated sub-device; i It generates the communication efficiency deviation value of the i-th associated sub-device based on monitoring data packets.

[0014] In some embodiments of this application, a mid-to-low altitude wind speed networking system based on UAV observation is provided, comprising: The inspection unit is used to establish an inspection equipment library. The central control unit is used to set up multiple inspection sub-devices according to the expected observation tasks; The central control unit includes: The first processing module is used to acquire feedback data packets from each inspection sub-device and set the network strategy based on the feedback data packets. The second processing module is used to acquire observation data packets according to the running network strategy; The second processing module is also used to construct a first-level four-dimensional wind field based on the observation data packet; The third processing module is used to establish the inspection sub-equipment sequence A, A = (a1, a2, ... a3) i …a n ), where a i Let i be the i-th inspection sub-device; n is the number of inspection sub-devices; The first processing module is also used for: A first-level inspection cycle is generated based on the expected observation tasks; The expected flight trajectory of each inspection sub-device is obtained based on all feedback data packets; The observed fluctuation value b is generated based on all expected flight trajectories. b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; The first-level inspection cycle is divided according to the observed fluctuation value b, and the time interval sequence T is set according to the division result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. Generate network sub-strategies for each time interval in sequence; Configure and run the network strategy according to all network sub-strategies.

[0015] In some embodiments of this application, network sub-policies for each time interval are generated sequentially, including: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, a is set sequentially. i For target sub-device; Generate the network evaluation value c of the target sub-device within the target time interval; Generate the network evaluation value of each inspection sub-device in sequence; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; Preset network evaluation threshold C1; If c i>C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; Multiple device subsets are generated based on all primary anchoring devices within the target time interval; Generate a network sub-strategy for the target time interval based on a subset of all devices.

[0016] In some embodiments of this application, the central control unit further includes: The third processing module is used to preset multiple monitoring time nodes; Construct the primary anchor device sequence A1 for the current monitoring time point; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; Obtain the monitoring data packets of the target anchoring device: Generate the operational deviation value f of the target anchoring device; Preset operating deviation threshold F1; If f > F1, a first-level correction instruction is generated at the current monitoring time node; The operating deviation values ​​of each primary anchoring device are generated sequentially; Determine whether a secondary correction instruction should be generated at the current monitoring time point based on all operational deviation values.

[0017] Compared with existing technologies, the network method and system for low- and mid-altitude wind speed based on UAV observations described in this application have the following advantages: By establishing multiple time intervals, the networking communication parameters are periodically adjusted during collaborative observation by the UAV swarm, thereby improving the networking communication efficiency and reorganization capability of the UAV swarm and enhancing the wind field observation efficiency under medium and low wind speeds.

[0018] By establishing a localized network and constructing a dual communication structure, the communication efficiency and data processing efficiency of individual UAVs are improved, while reducing the interference of a single UAV failure on the overall system. This enables continuous and gridded detection of low- and mid-altitude wind speeds. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a preferred embodiment of a mid-to-low altitude wind speed networking method based on UAV observation. Detailed Implementation

[0020] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0021] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0023] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0024] like Figure 1 As shown in the preferred embodiment of this application, a method for networking mid-to-low altitude wind speeds based on UAV observation includes: S101: Multiple inspection sub-devices are set up based on the expected observation tasks; S102: Obtain feedback data packets from each inspection sub-device and set the network strategy based on the feedback data packets; S103: Obtain observation data packets according to the network strategy and construct a first-level four-dimensional wind field based on the observation data packets; This includes setting up multiple inspection sub-devices, including: Establish a sequence A of sub-equipment to be inspected, A = (a1, a2, ..., a3) i …a n ), where a i Let be the i-th inspection sub-device; n is the number of inspection sub-devices.

[0025] Specifically, the inspection sub-equipment is preferably a drone, where a single inspection sub-equipment represents a drone.

[0026] Specifically, the UAV is equipped with an airborne wind speed measurement sensor and a positioning and attitude sensing device. It generates observation data packets by collecting airspeed, ground speed and meteorological data in real time. Based on the fusion algorithm and the wind field inversion method based on airspeed vector difference and attitude correction, all observation data packets are processed, and a first-level four-dimensional wind field in the observation area is generated according to the processing results.

[0027] Specifically, multiple observation sub-paths are generated in the area to be observed according to the expected observation task. Multiple inspection sub-devices are selected from the inspection equipment library based on the observation sub-path data. Each inspection sub-device corresponds to one observation sub-path, and the observation sub-paths corresponding to each inspection sub-device are different. The observation sub-paths corresponding to each inspection sub-device are set as the corresponding expected flight trajectory.

[0028] In a preferred embodiment of this application, the network strategy is set, including: A first-level inspection cycle is generated based on the expected observation tasks; The expected flight trajectory of each inspection sub-device is obtained based on all feedback data packets; The observed fluctuation value b is generated based on all expected flight trajectories. b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; The first-level inspection cycle is divided according to the observed fluctuation value b, and the time interval sequence T is set according to the division result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. Generate network sub-strategies for each time interval in sequence; Configure and run the network strategy according to all network sub-strategies.

[0029] Specifically, the trajectory fluctuation value is set according to the number of turning operations on the expected flight trajectory. The greater the number of turning operations, the greater the possibility that the current inspection sub-equipment's relative flight position (i.e., the relative distance between it and the remaining inspection sub-equipment at the same moment) will change during the execution of the observation task. The corresponding trajectory fluctuation value will be larger, and the mapping relationship between the two can be set based on historical parameters.

[0030] Specifically, the larger the observed fluctuation value b, the shorter the duration of a single time interval. The mapping relationship between the two can be set according to historical parameters. The duration of a single time interval is set according to the observed fluctuation value b, thereby uniformly dividing the first-level observation cycle and generating multiple time intervals.

[0031] Specifically, the first-level observation cycle is the total time required to complete the expected observation task.

[0032] It is understandable that, in the above embodiments, by establishing multiple time intervals, the networking communication parameters are periodically corrected when the UAV swarm conducts collaborative observation, thereby improving the networking communication efficiency and reorganization capability of the UAV swarm and improving the wind field observation efficiency under medium and low wind speeds.

[0033] In a preferred embodiment of this application, network sub-strategies for each time interval are generated sequentially, including: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, a is set sequentially. i For target sub-device; Generate the network evaluation value c of the target sub-device within the target time interval; Generate the network evaluation value of each inspection sub-device in sequence; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; Preset network evaluation threshold C1; If c i >C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; Multiple device subsets are generated based on all primary anchoring devices within the target time interval; Generate a network sub-strategy for the target time interval based on a subset of all devices.

[0034] Specifically, each non-primary anchor device selects a primary anchor device to form a network, and sequentially generates a subset of devices for each primary anchor device (i.e., all inspection sub-devices that are networked with that primary anchor device), thereby generating a network sub-strategy for the target time interval.

[0035] Specifically, the network evaluation threshold can be set based on historical parameters. When the network evaluation value is greater than the preset network evaluation threshold, it indicates that the target sub-device has good communication efficiency with the ground and its own flight status within the target time interval, and can be used as a communication anchor point (i.e., receiving observation data packets from some inspection sub-devices, performing simple processing, and sending them to the ground platform; at the same time, it can be used as a position anchor point to determine whether each inspection sub-device has deviated from its flight status by judging its relative position with the remaining inspection sub-devices).

[0036] Specifically, by selecting multiple primary anchoring devices within the target time interval, a dual communication model is constructed (i.e., the observation data packets from the inspection sub-devices are initially fused among the various primary anchoring devices before being sent to the ground platform). This reduces the interference of a single UAV failure on the overall system and enables continuous and gridded detection of mid- and low-altitude wind speeds.

[0037] Specifically, the network evaluation value c of the target sub-device within the target time interval includes: c=e*[ β i *s i ]; e=U1*[ p i ]; Where e is the network compensation coefficient; θ1 is the number of network indicators; β i s is the influencing factor of the i-th networking index; i U1 is the reference value of the i-th networking index of the target sub-device within the target time interval; p is the preset first conversion coefficient; i This represents the association value between the target sub-device and the i-th inspection sub-device within the target time interval.

[0038] Specifically, network indicators include communication quality in the flight area, UAV flight stability, data processing efficiency, communication efficiency, trajectory fluctuation, and other parameters that affect communication network. By quantifying each network indicator, the reference values ​​of each indicator are made to be within the same range. The higher the reference value of each communication indicator, the higher the adaptability of the current inspection sub-device as a communication anchor point.

[0039] Specifically, the influence factors of each networking indicator are set according to the degree of influence on the communication networking capability. The greater the degree of influence, the larger the value of the corresponding influence factor. The mapping relationship between the two can be set according to historical parameters.

[0040] Specifically, the association value is set according to the average relative distance between the target sub-device and the current sub-device within the target time interval. The smaller the average relative distance, the larger the corresponding association value. The mapping relationship between the two can be set according to historical parameters.

[0041] Specifically, a preset first conversion coefficient is used to make the networking compensation coefficient e fall within a preset value range, and p i has a larger value, the corresponding networking compensation coefficient has a larger value, and the mapping relationship between the two can be set according to historical parameters.

[0042] In the preferred embodiment of the examples of the present application, setting the operation networking strategy according to all networking sub-strategies includes: Establish a networking sub-strategy sequence W, W=(w1, w2...w i ...w m ), where w i is the networking sub-strategy of the i-th time interval; m is the number of time intervals; Sequentially set w according to the networking sub-strategy sequence W i as the target sub-strategy; Generate an adjustment fluctuation value d of the target sub-strategy; d=η1*Q1+η2*Q2; where η1 is a preset first weight coefficient; η2 is a preset second weight coefficient; Q1 is the first fluctuation reference value of the target sub-strategy generated based on the networking sub-strategy sequence; Q2 is the second fluctuation value of the target sub-strategy generated based on the networking sub-strategy sequence; Preset an adjustment fluctuation value threshold D1; If d>D1, generate a first-level correction instruction for the target sub-strategy, and generate a first-level networking strategy according to the correction result; If d<D1, set the target sub-strategy as the first-level networking strategy; Generate the operation networking strategy according to all the first-level networking strategies.

[0043] Specifically, the first fluctuation value generates the corresponding first fluctuation value according to the difference degree between the target sub-strategy and the previous networking sub-strategy of the target sub-strategy (according to the number of first-level anchor devices and the networking relationship between each inspection sub-device), the larger the difference degree, the larger the corresponding first reference value. The mapping relationship between the two can be set according to historical parameters.

[0044] Of the same type. The second fluctuation value is set according to the difference degree between the target sub-strategy and the next networking sub-strategy of the target sub-strategy, and the value ranges of the first fluctuation value and the second fluctuation value are the same.

[0045] Specifically, the adjustment fluctuation value threshold can be set according to historical parameters. If the real-time adjustment fluctuation value is greater than the preset adjustment fluctuation value threshold, it indicates that the adjustment and switching cost of the target sub-strategy is relatively high, and timely optimization is required, so as to improve the smoothness of switching between each networking sub-strategy and reduce the overall networking regulation and control cost.

[0046] Specifically, the first and second weighting coefficients can be set based on historical parameters, and η1+η2=1.

[0047] In a preferred embodiment of this application, it further includes: Multiple monitoring time points can be preset; Construct the primary anchor device sequence A1 for the current monitoring time point; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; Obtain the monitoring data packets of the target anchoring device: Generate the operational deviation value f of the target anchoring device; Preset operating deviation threshold F1; If f > F1, a first-level correction instruction is generated at the current monitoring time node; The operating deviation values ​​of each primary anchoring device are generated sequentially; Determine whether a secondary correction instruction should be generated at the current monitoring time point based on all operational deviation values.

[0048] Specifically, the operational deviation threshold can be set based on historical parameters. If the operational deviation value is greater than the preset operational deviation threshold, it indicates that the networking communication efficiency of the device subset corresponding to the target anchoring device is poor, and timely optimization and adjustment are required according to the first-level correction instruction, transferring some inspection sub-devices within the device subset.

[0049] Specifically, a preset correction evaluation value threshold is set, and a correction evaluation value is generated based on the sum of the operating deviation values ​​of all primary anchoring devices at the current monitoring time node. If the correction evaluation value is greater than the preset correction evaluation value threshold, it indicates that the overall network communication efficiency corresponding to the current monitoring time node is poor, and a secondary correction instruction needs to be generated to optimize and adjust the network sub-strategy of the time interval corresponding to the current monitoring time node in a timely manner to improve the overall network communication efficiency.

[0050] Specifically, generating the operational deviation value f of the target anchoring device includes: f=g*[ β i *j i ]; g=U2*[ µ i *k i]; Where g is the deviation compensation coefficient; θ1 is the number of network indicators; β i Let j be the influencing factor of the i-th networking index; i It is the deviation value of the i-th networking index of the target anchoring device generated based on the monitoring data packet; U2 is the preset second conversion coefficient; The number of associated sub-devices for the target anchoring device; µ i Let k be the influence factor of the i-th associated sub-device; i It generates the communication efficiency deviation value of the i-th associated sub-device based on monitoring data packets.

[0051] Specifically, each inspection sub-device in the equipment subset corresponding to the target anchoring device is set as an associated sub-device. Based on the association value between each associated sub-device and the target anchoring device, a corresponding influence factor is set. The larger the association value, the larger the reference value of the corresponding influence factor.

[0052] Specifically, a corresponding communication efficiency deviation value is set based on the communication efficiency of each associated sub-device. The worse the communication efficiency, the larger the corresponding communication efficiency deviation value.

[0053] Specifically, the deviation value is set according to the difference between the expected value and the actual value of each network indicator of the target anchoring device at the current time node. The larger the difference, the larger the corresponding deviation value. The mapping relationship between the two can be set according to historical parameters.

[0054] Specifically, by presetting a second conversion coefficient, the deviation compensation coefficient g is made to be within a preset value range, and [ µ i *k i The larger the value of ], the larger the corresponding deviation compensation coefficient g. The mapping relationship between the two can be set according to historical parameters.

[0055] In another preferred embodiment of the mid-to-low altitude wind speed networking method based on UAV observations, based on any of the above preferred embodiments, a mid-to-low altitude wind speed networking system based on UAV observations is provided, comprising: The inspection unit is used to establish an inspection equipment library. The central control unit is used to set up multiple inspection sub-devices according to the expected observation tasks; The central control unit includes: The first processing module is used to acquire feedback data packets from each inspection sub-device and set the network strategy based on the feedback data packets. The second processing module is used to acquire observation data packets according to the running network strategy; The second processing module is also used to construct a first-level four-dimensional wind field based on the observation data packet; The third processing module is used to establish the inspection sub-equipment sequence A, A = (a1, a2, ... a3) i …a n ), where a i Let i be the i-th inspection sub-device; n is the number of inspection sub-devices; The first processing module is also used for: A first-level inspection cycle is generated based on the expected observation tasks; The expected flight trajectory of each inspection sub-device is obtained based on all feedback data packets; The observed fluctuation value b is generated based on all expected flight trajectories. b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; The first-level inspection cycle is divided according to the observed fluctuation value b, and the time interval sequence T is set according to the division result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. Generate network sub-strategies for each time interval in sequence; Configure and run the network strategy according to all network sub-strategies.

[0056] In a preferred embodiment of this application, network sub-strategies for each time interval are generated sequentially, including: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, a is set sequentially. i For target sub-device; Generate the network evaluation value c of the target sub-device within the target time interval; Generate the network evaluation value of each inspection sub-device in sequence; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; Preset network evaluation threshold C1; If c i >C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; Multiple device subsets are generated based on all primary anchoring devices within the target time interval; Generate a network sub-strategy for the target time interval based on a subset of all devices.

[0057] In a preferred embodiment of this application, the central control unit further includes: The third processing module is used to preset multiple monitoring time nodes; Construct the primary anchor device sequence A1 for the current monitoring time point; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; Obtain the monitoring data packets of the target anchoring device: Generate the operational deviation value f of the target anchoring device; Preset operating deviation threshold F1; If f > F1, a first-level correction instruction is generated at the current monitoring time node; The operating deviation values ​​of each primary anchoring device are generated sequentially; Determine whether a secondary correction instruction should be generated at the current monitoring time point based on all operational deviation values.

[0058] According to the first concept of this application, by establishing multiple time intervals, the networking communication parameters are periodically adjusted when the UAV swarm conducts collaborative observation, thereby improving the networking communication efficiency and reorganization capability of the UAV swarm and improving the wind field observation efficiency under medium and low wind speeds.

[0059] According to the second concept of this application, a dual communication structure is constructed through local networking to improve the communication efficiency and data processing efficiency of individual UAVs, and reduce the interference of a single UAV failure on the overall system. This enables continuous and gridded detection of low- and mid-altitude wind speeds.

[0060] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. A method for networking mid-to-low altitude wind speeds based on UAV observations, characterized in that, comprising: configuring a plurality of inspection sub-devices based on an expected observation task; acquiring feedback data packets of each inspection sub-device, and formulating an operating networking strategy according to the feedback data packets; wherein the formulating an operating networking strategy comprises: generating a primary inspection cycle according to the expected observation task; acquiring an expected flight trajectory of each inspection sub-device according to all the feedback data packets; generating an observation fluctuation value b according to all the expected flight trajectories; b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; segmenting the primary inspection cycle according to the observation fluctuation value b, and formulating a time interval sequence T according to the segmentation result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. sequentially generating a sub-networking strategy for each time interval; formulating the operating networking strategy according to all the sub-networking strategies; acquiring observation data packets according to the operating networking strategy, and constructing a primary four-dimensional wind field according to the observation data packets; wherein the configuring a plurality of inspection sub-devices comprises: Establish a sequence A of sub-equipment to be inspected, A = (a1, a2, ..., a3) i …a n ), where a i Let be the i-th inspection sub-device; n is the number of inspection sub-devices.

2. The method for networking mid-to-low altitude wind speeds based on UAV observation as described in claim 1, characterized in that, the sequentially generating a sub-networking strategy for each time interval comprises: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, set a sequentially. i For target sub-device; generating a networking evaluation value c of a target sub-device in a target time interval; sequentially generating a networking evaluation value for each inspection sub-device; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; presetting a networking evaluation value threshold C1; If c i >C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; generating a plurality of device subsets within the target time interval according to all primary anchoring devices; generating the sub-networking strategy for the target time interval according to all the device subsets.

3. The method for networking mid-to-low altitude wind speeds based on UAV observation as described in claim 2, characterized in that, the generating a networking evaluation value c of a target sub-device in a target time interval comprises: c=e [ b i s i ]; e=U1 [ p i ]; Where e is the network compensation coefficient; θ1 is the number of network indicators; β i s is the influencing factor of the i-th networking index; i U1 is the reference value of the i-th networking index of the target sub-device within the target time interval; p is the preset first conversion coefficient; i This represents the association value between the target sub-device and the i-th inspection sub-device within the target time interval.

4. The method for networking mid-to-low altitude wind speeds based on UAV observation as described in claim 2, characterized in that, the formulating an operating networking strategy according to all the sub-networking strategies comprises: Establish a sub-strategy sequence W, W=(w1, w2…w i …w m ), where w i Let m be the network sub-strategy for the i-th time interval; m is the number of time intervals. Based on the network sub-strategy sequence W, w is set sequentially. i For the target sub-strategy; generating an adjustment fluctuation value d of a target sub-strategy; d=η1 Q1+η2 Q2; wherein η1 is a preset first weight coefficient; η2 is a preset second weight coefficient; Q1 is a first fluctuation reference value of the generated target sub-strategy based on the sub-networking strategy sequence; Q2 is a second fluctuation value of the target sub-strategy generated based on the sub-networking strategy sequence; presetting an adjustment fluctuation value threshold D1; if d>D1, generating a primary correction instruction for the target sub-strategy, and generating a primary networking strategy according to the correction result; if d<D1, setting the target sub-strategy as the primary networking strategy; generating the operating networking strategy according to all the primary networking strategies.

5. The method for networking mid-to-low altitude wind speeds based on UAV observation as described in claim 4, characterized in that, further comprising: presetting a plurality of monitoring time nodes; constructing a primary anchoring device sequence A1 of the current monitoring time node; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; acquiring a monitoring data packet of a target anchoring device: generating an operation deviation value f of the target anchoring device; presetting an operation deviation value threshold F1; if f>F1, generating a primary correction instruction at the current monitoring time node; sequentially generating an operation deviation value for each primary anchoring device; determining whether to generate a secondary correction instruction at the current monitoring time node according to all the operation deviation values.

6. The method for networking mid-to-low altitude wind speeds based on UAV observation as described in claim 5, characterized in that, the generating an operation deviation value f of the target anchoring device comprises: f=g [ b i j i ]; g=U2 [ µ i k i ]; Where g is the deviation compensation coefficient; θ1 is the number of network indicators; β i Let j be the influencing factor of the i-th networking index; i It is the deviation value of the i-th networking index of the target anchoring device generated based on the monitoring data packet; U2 is the preset second conversion coefficient; The number of associated sub-devices for the target anchoring device; µ i Let k be the influence factor of the i-th associated sub-device; i It generates the communication efficiency deviation value of the i-th associated sub-device based on monitoring data packets.

7. A mid-to-low altitude wind speed networking system based on UAV observation, employing the mid-to-low altitude wind speed networking method based on UAV observation as described in any one of claims 1-6, characterized in that, comprising: an inspection unit, configured to establish an inspection device library; a central control unit, configured to configure a plurality of inspection sub-devices according to an expected observation task; the central control unit comprises: a first processing module, configured to acquire feedback data packets of each inspection sub-device, and formulate an operating networking strategy according to the feedback data packets; a second processing module, configured to acquire observation data packets according to the operating networking strategy; the second processing module is further configured to construct a primary four-dimensional wind field according to the observation data packets; The third processing module is used to establish the inspection sub-equipment sequence A, A = (a1, a2, ... a3) i …a n ), where a i Let i be the i-th inspection sub-device; n is the number of inspection sub-devices; the first processing module is further configured to: generate a primary inspection cycle according to the expected observation task; acquire an expected flight trajectory of each inspection sub-device according to all the feedback data packets; generate an observation fluctuation value b according to all the expected flight trajectories; b=[ v i ]; Where n is the number of inspection sub-devices; v i Let be the trajectory fluctuation value of the i-th inspection sub-device; The first-level inspection cycle is divided according to the observed fluctuation value b, and the time interval sequence T is set according to the division result; T = (t1, t2, ..., tt) i …t m ), where t i represents the i-th time interval in the first-level inspection cycle; m is the number of time intervals. Generate network sub-strategies for each time interval in sequence; Configure and run the network strategy according to all network sub-strategies.

8. The mid-to-low altitude wind speed networking system based on UAV observation as described in claim 7, characterized in that, The network sub-policies for each time interval are generated sequentially, including: Based on the time interval sequence T, t is set sequentially. i The target time interval; Based on the inspection sub-equipment sequence A, set a sequentially. i For target sub-device; Generate the network evaluation value c of the target sub-device within the target time interval; Generate the network evaluation value of each inspection sub-device in sequence; Establish a network evaluation value sequence C, C=(c1,c2…c) for the target time interval. i …c n ), where c i This represents the network evaluation value of the i-th inspection sub-device within the target time interval; Preset network evaluation threshold C1; If c i >C1, Set the i-th inspection sub-device as a first-level anchoring device in the target time interval; Multiple device subsets are generated based on all primary anchoring devices within the target time interval; Generate a network sub-strategy for the target time interval based on a subset of all devices.

9. The mid-to-low altitude wind speed networking system based on UAV observation as described in claim 8, characterized in that, The central control unit also includes: The third processing module is used to preset multiple monitoring time nodes; Construct the primary anchor device sequence A1 for the current monitoring time point; A1 = (a 11 ,a 12 …a 1i …a 1n1 ), where a 1i n1 represents the i-th primary anchoring device at the current monitoring time point; n1 represents the number of primary anchoring devices at the current monitoring time point. Based on the sequence A1 of the primary anchoring devices, a is set sequentially. 1i Anchoring equipment for the target; Obtain the monitoring data packets of the target anchoring device: Generate the operational deviation value f of the target anchoring device; Preset operating deviation threshold F1; If f > F1, a first-level correction instruction is generated at the current monitoring time node; The operating deviation values ​​of each primary anchoring device are generated sequentially; Determine whether a secondary correction instruction should be generated at the current monitoring time point based on all operational deviation values.

Images