Unmanned aerial vehicle dynamic communication supervision method and system

Abstract

The invention relates to an unmanned aerial vehicle dynamic communication supervision method and system, and the method comprises the steps: building a reference communication database based on an impact factor set, determining a monitoring time interval based on an environment collection instruction, obtaining communication data based on the monitoring time interval, retrieving a plurality of reference communication schemes in the reference communication database through the communication data, obtaining a target communication scheme based on a plurality of reference communication schemes, obtaining an initial communication scheme of a target unmanned aerial vehicle, updating the initial communication scheme by using the target communication scheme and a scheme updating unit, obtaining a public key and a private key based on a scheme evaluation value corresponding to the target communication scheme, a monitoring time interval and the target communication scheme, and sending the public key and the private key to the target unmanned aerial vehicle. And encrypting the initial sending signal by using the public key to obtain an initial encrypted signal, and decrypting the initial encrypted signal by using the private key to obtain a target encrypted signal for driving the target unmanned aerial vehicle. According to the invention, the intelligent degree of unmanned aerial vehicle communication supervision and the communication security can be improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method and system for dynamic communication supervision of unmanned aerial vehicles. Background Art

[0002] With the development of drone technology, drones are increasingly used in civil and commercial fields. Correspondingly, the flight safety and communication security of drones are becoming more and more important. Therefore, safe and intelligent supervision of drone communications is of great significance to ensure their safety.

[0003] At present, static communication supervision methods are mostly used for drone communications.

[0004] Although the above methods can achieve the supervision of drone communications, the use environment of drones is diverse in actual applications, and different environmental characteristics may have different effects on drone communications. Therefore, static supervision cannot adapt to environmental changes. The intelligence and security of drone communication supervision need to be improved. Summary of the invention

[0005] The present invention provides a method and system for dynamic communication supervision of unmanned aerial vehicles, the main purpose of which is to improve the intelligence level of unmanned aerial vehicle communication supervision and the security of communication.

[0006] To achieve the above-mentioned purpose, the present invention provides a method for monitoring dynamic communication of unmanned aerial vehicles, comprising:

[0007] Identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a plan construction unit and a plan update unit;

[0008] Confirming receipt of a solution construction instruction from a solution construction unit, and acquiring an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes a plurality of impact factor groups, and each impact factor group includes one or more impact factors;

[0009] constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups;

[0010] Confirming receipt of an environment collection instruction from an environment collection unit, confirming a monitoring time interval based on the environment collection instruction, and acquiring communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal;

[0011] Retrieving a plurality of reference communication schemes from a reference communication database using the communication data, and acquiring a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes, wherein the scheme evaluation values ​​correspond one to one to the reference communication schemes;

[0012] According to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme updating unit;

[0013] Acquire a public key and a private key based on a scheme evaluation value corresponding to the target communication scheme, a monitoring time interval, and the target communication scheme, and use the public key to perform an encryption operation on a pre-acquired target transmission signal to obtain an initial encrypted signal;

[0014] After the private key and the initial encrypted signal are sent to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

[0015] Optionally, constructing a plurality of fitting factor groups based on the influencing factor group set includes:

[0016] In a combined form, one or more influencing factors corresponding to each influencing factor group in the influencing factor group set are used to obtain a fitting factor group, wherein the fitting factor group is as follows:

[0017] N={y 1a ,y 2b ,…,y nc}

[0018] Where N represents the fitting factor group, y 1a represents the ath impact factor corresponding to the first impact factor group in the impact factor group set, y 2b represents the bth impact factor corresponding to the second impact factor group in the impact factor group set, y nc represents the cth impact factor corresponding to n impact factor groups in the impact factor group set, and n represents that there are n impact factor groups in the impact factor group set;

[0019] The fitting factor groups are aggregated to obtain multiple fitting factor groups.

[0020] Optionally, the identifying a reference communication database based on the plurality of fitting factor groups comprises:

[0021] Extract fitting factor groups from the multiple fitting factor groups in sequence, and perform the following operations on the extracted fitting factor groups:

[0022] A reference data set is identified based on the extracted fitting factor group, wherein the reference data set includes a plurality of reference data, and the reference data includes a transmitted signal, a received signal, a signal delay, a transmitted signal characteristic value, and a received signal characteristic value;

[0023] Extract reference data from the reference data set in sequence, and perform the following operations on the extracted reference data:

[0024] Acquire a signal recognition model set for identifying a signal transmission state, wherein the signal recognition model set includes at least three signal recognition models, the signal recognition models in the signal recognition model set are stored in a pre-built storage unit, and the signal transmission state is: a line-of-sight transmission state or a non-line-of-sight transmission state;

[0025] Randomly extract three signal recognition models from the signal recognition model set to obtain three target recognition models, and obtain a recognition state set using the three target recognition models, a transmitted signal corresponding to the reference data, and a received signal corresponding to the reference data, wherein the recognition state set includes three signal recognition states, and the signal recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state;

[0026] Using the line-of-sight transmission state and the non-line-of-sight transmission state, respectively counting the number of signal recognition states in the recognition state set to obtain a first statistical number and a second statistical number, using the first statistical number and the second statistical number to confirm the target transmission state, and using the target transmission state to perform an identification operation on the extracted reference data to obtain identification data;

[0027] A reference communication database is identified based on the identification data.

[0028] Optionally, the confirming a reference communication database based on the identification data includes:

[0029] comparing the characteristic value of the transmitted signal with the characteristic value of the received signal;

[0030] If the characteristic value of the transmitted signal is equal to the characteristic value of the received signal, the identification data is confirmed as the first transmission data, and the number of the first transmission data and the number of reference data in the reference data set are counted respectively to obtain a first transmission number and a first reference number;

[0031] Calculating a target transmission probability using the first transmission quantity and the first reference quantity, wherein the target transmission probability is a ratio of the first transmission quantity to the first reference quantity;

[0032] A signal transmission tree structure is constructed with signal transmission as a root node, each of the multiple fitting factor groups as a first child node, and a target transmission state second child node corresponding to the identification data;

[0033] A reference communication database is constructed based on the target transmission probability and the signal transmission tree structure.

[0034] Optionally, constructing a reference communication database based on the target transmission probability and the signal transmission tree structure includes:

[0035] Extracting an initial analysis data set from the signal transmission tree structure, wherein the initial analysis data set is identification data corresponding to the second child node, and using a preset delay threshold to identify a target analysis data set in the initial analysis data set, wherein the target analysis data set includes a plurality of target analysis data, and the signal delays corresponding to the target analysis data are all less than or equal to the delay threshold;

[0036] Obtaining a delay probability using the target analysis data set and the initial analysis data set, and obtaining a delay mean value according to the target analysis data set, wherein the delay mean value is the mean value of signal delays corresponding to multiple target analysis data in the target analysis data set;

[0037] The delay probability, the delay mean and the target transmission probability are used to perform an identification operation on the second subnode to obtain an identified second subnode, and the identified second subnode is used to update the second subnode corresponding to the initial analysis data set to obtain a reference communication database.

[0038] Optionally, determining a monitoring time interval based on the environment collection instruction includes:

[0039] Parsing the environment acquisition instruction to obtain a detection angle set, wherein the detection angle set includes multiple detection angles, and using the detection angle set to obtain a detection distance set, wherein the detection distance set includes multiple detection distances, and the detection distances correspond to the detection angles one by one;

[0040] The monitoring time interval is calculated based on the detection distance set, wherein the monitoring time interval is as follows:

[0041] if min(l1,l2,…,l e )≥l0,t=t0

[0042]

[0043] Among them, min means taking the minimum value, l1, l2, l j , l eThey respectively represent the first detection distance, the second detection distance, the jth detection distance and the eth detection distance in the detection distance set, l0 is the preset distance threshold, t0 is the preset interval time threshold, e means that there are e detection distances in the detection distance set, and t represents the monitoring time interval.

[0044] Optionally, the retrieving a plurality of reference communication schemes from a reference communication database using the environment data includes:

[0045] Randomly extracting three reference recognition models from the signal recognition model set, and confirming a reference recognition state based on an initial transmitted signal, an initial received signal, and the three extracted reference recognition models, wherein the reference recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state;

[0046] Using the reference identification state, multiple target second sub-nodes are retrieved from a reference communication database, wherein the target transmission state corresponding to the target second sub-node is the reference identification state, and wherein the fitting factor group corresponding to each of the multiple target second sub-nodes is the reference communication scheme.

[0047] Optionally, the acquiring a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes comprises:

[0048] The following operations are performed for each of the multiple reference communication schemes:

[0049] A comprehensive evaluation relationship is constructed, and the scheme evaluation value is calculated using the comprehensive evaluation relationship and the reference communication scheme, where the comprehensive evaluation relationship is as follows:

[0050]

[0051] Among them, Z represents the scheme evaluation value, θ, γ, ω, and β are all preset coefficients, α1 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the line-of-sight transmission state, α2 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the non-line-of-sight transmission state, P represents the transmission power, d represents the transmission distance, and p1 represents the delay probability. represents the mean delay, p2 represents the target transmission probability, C represents the reference energy consumption value, and the reference energy consumption value is related to the initial communication scheme and the reference communication scheme.

[0052] Optionally, the acquiring a public key and a private key based on the scheme evaluation value, the monitoring time interval and the target communication scheme includes:

[0053] The first prime number is calculated using the scheme evaluation value, the monitoring time interval, the target communication scheme and the pre-constructed first prime number relationship expression, wherein the first prime number relationship expression is as follows:

[0054] s=random<[[Z] [t] +H1+H2+H3]>

[0055] Wherein, s represents the first prime number, [] represents a rounding operation, H1, H2, and H3 represent the data volume of the three reference recognition models corresponding to the target communication scheme in the storage unit, < > represents taking a prime number, and random represents taking a random number;

[0056] The second prime number is calculated based on the first prime number and the pre-constructed second prime number relationship, wherein the second prime number relationship is as follows:

[0057]

[0058] Wherein, S represents the second prime number, and A is the preset coefficient;

[0059] A public key and a private key are obtained using the first prime number and the second prime number.

[0060] To achieve the above object, the present invention also provides a UAV dynamic communication monitoring system, comprising:

[0061] A communication database construction module is used to identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a solution construction unit and a solution update unit;

[0062] Confirming receipt of a solution construction instruction from a solution construction unit, and acquiring an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes a plurality of impact factor groups, and each impact factor group includes one or more impact factors;

[0063] constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups;

[0064] The UAV dynamic monitoring module is used to confirm the receipt of the environment collection instruction from the environment collection unit, confirm the monitoring time interval based on the environment collection instruction, and obtain the communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal;

[0065] a communication scheme confirmation module, configured to retrieve a plurality of reference communication schemes from a reference communication database using the communication data, and obtain a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes, wherein the scheme evaluation values ​​correspond one to one with the reference communication schemes;

[0066] According to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme updating unit;

[0067] A communication signal dynamic encryption and update module, used to obtain a public key and a private key based on the scheme evaluation value corresponding to the target communication scheme, the monitoring time interval and the target communication scheme, and use the public key to perform an encryption operation on the pre-acquired target transmission signal to obtain an initial encrypted signal;

[0068] After the private key and the initial encrypted signal are sent to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

[0069] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0070] A memory storing at least one instruction; and a processor executing the instructions stored in the memory to implement the above-mentioned method for dynamic communication supervision of unmanned aerial vehicles.

[0071] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned method for dynamic communication supervision of unmanned aerial vehicles.

[0072] The present invention first confirms receiving a scheme construction instruction from a scheme construction unit, and obtains an influencing factor group set based on the scheme construction instruction, wherein the influencing factor group set includes multiple influencing factor groups, and each influencing factor group includes one or more influencing factors. It can be seen that when considering the parameters that may affect the communication mode of the target drone, the present invention does not only consider the regulation of a certain parameter, but comprehensively considers multiple parameters that may affect the communication state of the target drone, thereby laying a foundation for improving the intelligence of the target drone communication supervision. The present invention constructs multiple fitting factor groups based on the influencing factor group set, and confirms the reference communication database based on the multiple fitting factor groups. It can be seen that the present invention combines different fitting factor groups to obtain different reference data sets, and obtains the relevant reference parameters corresponding to the fitting factor group according to the signal recognition state of the reference data in the reference data set, wherein the relevant reference parameters include the target transmission state, the target transmission probability, the delay probability and the delay mean, so as to improve the intelligence level when dynamically supervising the drone communication. The present invention confirms receipt of an environment collection instruction from an environment collection unit, confirms a monitoring time interval based on the environment collection instruction, and obtains communication data of a target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal. It can be seen that the present invention takes into account the environment in which the UAV is located when obtaining the monitoring time interval, and obtains the monitoring time interval according to the environment in which the UAV is located, and dynamically obtains the monitoring time interval to improve the intelligence level of dynamic supervision of UAV communications. The present invention uses the communication data to retrieve multiple reference communication schemes in a reference communication database, and obtains multiple scheme evaluation values ​​based on the multiple reference communication schemes, wherein the scheme evaluation values ​​correspond to the reference communication schemes one by one, and according to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, and an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and a scheme update unit. It can be seen that the present invention combines the environment in which the UAV is located, dynamically updates the communication scheme, and when updating the communication scheme, calculates the scheme evaluation values ​​corresponding to different communication schemes, and by setting the scheme evaluation threshold, avoids excessive updating of the communication scheme, thereby improving the intelligence level of UAV communication supervision.The present invention obtains a public key and a private key based on the scheme evaluation value, the monitoring time interval and the target communication scheme corresponding to the target communication scheme, uses the public key to perform an encryption operation on the pre-acquired target sending signal to obtain an initial encrypted signal, sends the private key and the initial encrypted signal to the target UAV, performs a decryption operation on the initial encrypted signal using the private key to obtain a target encrypted signal, drives the target UAV based on the target encrypted signal, and returns to the step of confirming the monitoring time interval based on the environment acquisition instruction to achieve supervision of the target UAV communication. It can be seen that the embodiment of the present invention, on the basis of dynamically updating the communication scheme, combines the relevant parameters in different time periods to solve the public key used to encrypt the initial sending signal, thereby improving the security of the UAV during communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A schematic diagram of the process flow of the unmanned aerial vehicle dynamic communication supervision method provided by the present invention;

[0074] Figure 2 A functional module diagram of the unmanned aerial vehicle dynamic communication monitoring system provided by the present invention;

[0075] Figure 3 A schematic diagram of the structure of an electronic device for implementing the method for dynamic communication supervision of unmanned aerial vehicles provided by the present invention.

[0076] Description of reference numerals:

[0077] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0078] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0079] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0080] Embodiment 1:

[0081] This embodiment provides a method for supervising the dynamic communication of unmanned aerial vehicles. The execution subject of the method for supervising the dynamic communication of unmanned aerial vehicles includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for supervising the dynamic communication of unmanned aerial vehicles can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0082] Reference Figure 1FIG. 1 is a flow chart of a method for monitoring dynamic communication of a UAV provided in an embodiment. In this embodiment, the method for monitoring dynamic communication of a UAV includes:

[0083] S1. Identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a plan construction unit and a plan update unit.

[0084] The target UAV refers to a UAV that needs to be supervised for communication, and the communication supervision system refers to a system that can supervise the communication status of the target UAV, wherein the type of the communication supervision system can be a mini program and an APP, and the communication supervision system includes: an environment collection unit, a solution construction unit, and a solution update unit. Please refer to the subsequent embodiments for the specific application of the unit.

[0085] For example, when Xiao Zhang is driving a drone to perform operations, due to the complex and changeable environment, he needs to monitor the communication status of the drone in order to improve the response speed of the drone, thereby reducing the probability of drone failure due to slow response speed or abnormal response of the drone.

[0086] Furthermore, the embodiments of the present invention are mainly aimed at improving the security of drone communications and the intelligence level of drone communication scheme supervision.

[0087] S2. Confirm receipt of a solution construction instruction from a solution construction unit, and obtain an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes multiple impact factor groups, and each impact factor group includes one or more impact factors.

[0088] The influencing factors refer to factors that can affect the communication status of the drone, including but not limited to: the frequency band of the signal, the modulation mode of the signal, and the channel of the signal. Each influencing factor group includes one or more influencing factors.

[0089] Furthermore, when the UAV is communicating, the selection of different influencing factors may have an impact on the UAV's communication, and in different application scenarios, the channels composed of different influencing factors for UAV communication transmission may have different energy consumption, time required for signal propagation, and stability of signal propagation.

[0090] S3. Constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups.

[0091] It should be explained that the multiple fitting factor groups are constructed based on the influencing factor group set, including:

[0092] In a combined form, one or more influencing factors corresponding to each influencing factor group in the influencing factor group set are used to obtain a fitting factor group, wherein the fitting factor group is as follows:

[0093] N={y 1a ,y 2b ,…,y nc}

[0094] Where N represents the fitting factor group, y 1a represents the ath impact factor corresponding to the first impact factor group in the impact factor group set, y 2b represents the bth impact factor corresponding to the second impact factor group in the impact factor group set, y nc represents the cth impact factor corresponding to n impact factor groups in the impact factor group set, and n represents that there are n impact factor groups in the impact factor group set;

[0095] The fitting factor groups are aggregated to obtain multiple fitting factor groups.

[0096] Exemplarily, the influencing factor group set includes 3 influencing factor groups in total, wherein the 3 influencing factor groups are: channel, frequency band and modulation mode, wherein the influencing factor group corresponding to the channel includes only one influencing factor, which is: radio wave, the influencing factor group corresponding to the frequency band includes two influencing factors, and the two influencing factors are 2.4GHZ and 5.8GHZ respectively, the influencing factor group corresponding to the modulation mode includes 3 influencing factors, and the 3 influencing factors are: amplitude modulation, frequency modulation and phase modulation respectively, then 6 fitting factor groups can be obtained using the 3 influencing factor groups.

[0097] It is understandable that the fitting factor group is a combination of influencing factors that can be used to adjust the communication status of the drone. Since the factors affecting the signal quality of the drone during communication include not only adjustable factors, but also unadjustable factors, these factors include but are not limited to: environmental factors, building factors, etc. Therefore, when supervising the communication status of the drone, the environment in which the drone is located also needs to be considered.

[0098] It should be understood that the step of identifying a reference communication database based on the plurality of fitting factor groups includes:

[0099] Extract fitting factor groups from the multiple fitting factor groups in sequence, and perform the following operations on the extracted fitting factor groups:

[0100] A reference data set is identified based on the extracted fitting factor group, wherein the reference data set includes a plurality of reference data, and the reference data includes a transmitted signal, a received signal, a signal delay, a transmitted signal characteristic value, and a received signal characteristic value;

[0101] Extract reference data from the reference data set in sequence, and perform the following operations on the extracted reference data:

[0102] Acquire a signal recognition model set for identifying a signal transmission state, wherein the signal recognition model set includes at least three signal recognition models, the signal recognition models in the signal recognition model set are stored in a pre-built storage unit, and the signal transmission state is: a line-of-sight transmission state or a non-line-of-sight transmission state;

[0103] Randomly extract three signal recognition models from the signal recognition model set to obtain three target recognition models, and obtain a recognition state set using the three target recognition models, a transmitted signal corresponding to the reference data, and a received signal corresponding to the reference data, wherein the recognition state set includes three signal recognition states, and the signal recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state;

[0104] Using the line-of-sight transmission state and the non-line-of-sight transmission state, respectively counting the number of signal recognition states in the recognition state set to obtain a first statistical number and a second statistical number, using the first statistical number and the second statistical number to confirm the target transmission state, and using the target transmission state to perform an identification operation on the extracted reference data to obtain identification data;

[0105] A reference communication database is identified based on the identification data.

[0106] It should be explained that confirming the reference data set based on the extracted fitting factor group refers to retrieving a set of drone communication data with the same influencing factors as the influencing factors corresponding to the fitting factor group in the pre-acquired drone communication data set. Optionally, the drone communication data set is the DroneRFa data set. The transmitted signal refers to the signal sent by the user to the drone, and the received signal refers to the transmitted signal received by the drone. Generally speaking, ideally, the transmitted signal should be the same as the received signal, but due to the existence of environmental factors and other factors, the transmitted signal may be different from the received signal.

[0107] It is understandable that the signal delay refers to the absolute difference between the time corresponding to the sending signal and the time corresponding to the receiving signal. Here, it is used to characterize the response speed of the drone to the signal. The shorter the signal delay, the faster the response speed of the drone to the signal under the fitting factor group. The sending signal characteristic value and the receiving signal characteristic value refer to the characteristic value corresponding to the sending signal and the characteristic value corresponding to the receiving signal, respectively. In the embodiment of the present invention, the sending signal characteristic value and the receiving signal characteristic value are used to verify whether the sending signal is the same as the receiving signal. Optionally, the sending signal characteristic value is a first CRC value calculated using the sending signal and a pre-built CRC algorithm, and the receiving signal characteristic value is a second CRC value calculated using the receiving signal and the CRC algorithm. The CRC (Cyclic Redundancy Check) algorithm is a cyclic redundancy check, which is an algorithm used to detect whether errors occur during data transmission or storage.

[0108] Furthermore, the line-of-sight transmission state refers to the state in which the signal of the drone is directly transmitted from the transmitting point to the receiving point without any obstacles blocking the transmission process. The non-line-of-sight transmission state refers to the state in which the signal of the drone is blocked by obstacles during the transmission process or the signal needs to be transmitted by reflection, refraction, scattering, etc. Optionally, the signal recognition model is a support vector machine, a convolutional neural network, or an XGBoost algorithm.

[0109] It should be understood that different signal transmission states correspond to different situations. Therefore, classifying reference data in combination with signal transmission states can improve the accuracy of monitoring drone communications. The technology of using target recognition models, sending signals, and receiving signals to identify signal transmission states is a prior art and will not be repeated here. Using the first statistical quantity and the second statistical quantity to confirm the target transmission state includes: using a pre-built filtering relationship, the first statistical quantity, and the second statistical quantity to confirm the target statistical quantity, wherein the signal transmission state corresponding to the target statistical quantity is the target transmission state, and the filtering relationship is as follows:

[0110] m=max(T1,T2)

[0111] Among them, m represents the target statistical quantity, max represents the maximum value, T1 and T2 represent the first statistical quantity and the second statistical quantity respectively.

[0112] Exemplarily, the identification state set includes: non-line-of-sight transmission state, non-line-of-sight transmission state and line-of-sight transmission state, then the statistical number of line-of-sight transmission states is 1, and the statistical number of non-line-of-sight transmission states is 2. Here, the number of line-of-sight transmission states is the first statistical number, and the number of non-line-of-sight transmission states is the second statistical number. Then, the target transmission state confirmed by using the first statistical number and the second statistical number is the non-line-of-sight transmission state.

[0113] It is understandable that the purpose of using the target transmission state to perform the identification operation on the extracted reference data is to improve the speed of retrieving the reference data in combination with the actual use scenario of the drone, thereby improving the speed of supervising the drone communication, and when there is new reference data, it is convenient to update the reference communication database. For the specific implementation method, please refer to the subsequent embodiments. For example: using line-of-sight transmission and non-line-of-sight transmission to represent the line-of-sight transmission state and the non-line-of-sight transmission state respectively, and using the target transmission state to perform identification on the reference data, obtaining line-of-sight transmission-reference data or non-line-of-sight transmission-reference data, wherein the line-of-sight transmission-reference data and the non-line-of-sight transmission-reference data are both identification data.

[0114] Further, the identifying a reference communication database based on the identification data includes:

[0115] comparing the characteristic value of the transmitted signal with the characteristic value of the received signal;

[0116] If the characteristic value of the transmitted signal is equal to the characteristic value of the received signal, the identification data is confirmed as the first transmission data, and the number of the first transmission data and the number of reference data in the reference data set are counted to obtain a first transmission number and a first reference number;

[0117] Calculating a target transmission probability using the first transmission quantity and the first reference quantity, wherein the target transmission probability is a ratio of the first transmission quantity to the first reference quantity;

[0118] A signal transmission tree structure is constructed with signal transmission as a root node, each of the multiple fitting factor groups as a first child node, and a target transmission state second child node corresponding to the identification data;

[0119] A reference communication database is constructed based on the target transmission probability and the signal transmission tree structure.

[0120] Among them, the first transmission data refers to the identification data that the sending signal is the same as the receiving signal. The signal transmission tree structure is used to characterize the distribution of reference data in the reference data set under the tree structure. The technology of constructing a tree structure using signal transmission, fitting factor group, target transmission state and target transmission probability is a prior art and will not be repeated here. Generally speaking, in the tree structure, the relationship between the first child node and the first child node, and the relationship between the second child node and the second child node are both brother relationships, and the relationship between the first child node and the second child node is a parent-child relationship.

[0121] In this embodiment, the reference data set includes 10 reference data in total, and 8 reference data among the 10 reference data are successfully transmitted data, which are the first transmitted data. The target transmission probability calculated using the first transmission number and the first reference number is 0.8.

[0122] It should be explained that the construction of a reference communication database based on the target transmission probability and the signal transmission tree structure includes:

[0123] Extracting an initial analysis data set from the signal transmission tree structure, wherein the initial analysis data set is identification data corresponding to the second child node, and using a preset delay threshold to identify a target analysis data set in the initial analysis data set, wherein the target analysis data set includes a plurality of target analysis data, and the signal delays corresponding to the target analysis data are all less than or equal to the delay threshold;

[0124] Obtaining a delay probability using the target analysis data set and the initial analysis data set, and obtaining a delay mean value according to the target analysis data set, wherein the delay mean value is the mean value of signal delays corresponding to multiple target analysis data in the target analysis data set;

[0125] The delay probability, the delay mean and the target transmission probability are used to perform an identification operation on the second subnode to obtain an identified second subnode, and the identified second subnode is used to update the second subnode corresponding to the initial analysis data set to obtain a reference communication database.

[0126] Further, the method for obtaining the delay probability is the same as the method for obtaining the target transmission probability, and can achieve the same effect, which is not repeated here. The method for performing an identification operation on the second subnode using the delay probability, the delay mean and the target transmission probability is the same as the method for performing an identification operation on the extracted reference data using the target transmission state, and can achieve the same effect, which is not repeated here.

[0127] S4. Confirm receipt of an environment collection instruction from an environment collection unit, confirm a monitoring time interval based on the environment collection instruction, and acquire communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal.

[0128] It is understandable that determining the monitoring time interval based on the environment collection instruction includes:

[0129] Parsing the environment acquisition instruction to obtain a detection angle set, wherein the detection angle set includes multiple detection angles, and using the detection angle set to obtain a detection distance set, wherein the detection distance set includes multiple detection distances, and the detection distances correspond to the detection angles one by one;

[0130] The monitoring time interval is calculated based on the detection distance set, wherein the monitoring time interval is as follows:

[0131] if min(l1,l2,…,l e )≥l0,t=t0

[0132]

[0133] Among them, min means taking the minimum value, l1, l2, l j , l e They respectively represent the first detection distance, the second detection distance, the jth detection distance and the eth detection distance in the detection distance set, l0 is the preset distance threshold, t0 is the preset interval time threshold, e means that there are e detection distances in the detection distance set, and t represents the monitoring time interval.

[0134] It should be explained that the detection angle set is a set of angles at which the target UAV detects the environment. Optionally, the detection distance is obtained by using a laser radar to obtain the detection distance in the direction corresponding to the detection angle, wherein the detection distance is the distance of the target UAV from the obstacle in the environment in the direction corresponding to the detection angle. The definition of the initial transmission signal is the same as the definition of the transmission signal, which will not be repeated here. The definition of the initial reception signal is the same as the definition of the reception signal, which will not be repeated here.

[0135] S5. Retrieve multiple reference communication schemes from a reference communication database using the communication data, and obtain multiple scheme evaluation values ​​based on the multiple reference communication schemes, wherein the scheme evaluation values ​​correspond to the reference communication schemes one by one.

[0136] It is understandable that the step of retrieving a plurality of reference communication schemes from a reference communication database using the environment data includes:

[0137] Randomly extracting three reference recognition models from the signal recognition model set, and confirming a reference recognition state based on an initial transmitted signal, an initial received signal, and the three extracted reference recognition models, wherein the reference recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state;

[0138] Using the reference identification state, multiple target second sub-nodes are retrieved from a reference communication database, wherein the target transmission state corresponding to the target second sub-node is the reference identification state, and wherein the fitting factor group corresponding to each of the multiple target second sub-nodes is the reference communication scheme.

[0139] It should be explained that the method of confirming the reference identification state based on the initial transmission signal, the initial reception signal and the three extracted reference identification models is the same as the method of confirming the target transmission state using the transmission signal, the reception signal and the three target identification models, which will not be repeated here. Generally, before retrieving the reference communication scheme, the search conditions can be set in combination with the software facilities and hardware facilities carried by the target UAV, so as to reduce the energy consumption required for the search process when retrieving the reference communication scheme.

[0140] Further, the acquiring multiple scheme evaluation values ​​based on the multiple reference communication schemes includes:

[0141] The following operations are performed for each of the multiple reference communication schemes:

[0142] A comprehensive evaluation relationship is constructed, and the scheme evaluation value is calculated using the comprehensive evaluation relationship and the reference communication scheme, where the comprehensive evaluation relationship is as follows:

[0143]

[0144] Among them, Z represents the scheme evaluation value, θ, γ, ω, and β are all preset coefficients, α1 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the line-of-sight transmission state, α2 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the non-line-of-sight transmission state, P represents the transmission power, d represents the transmission distance, and p1 represents the delay probability. represents the mean delay, p2 represents the target transmission probability, C represents the reference energy consumption value, and the reference energy consumption value is related to the initial communication scheme and the reference communication scheme.

[0145] Among them, the energy consumption correction coefficient is a coefficient used to correct the energy consumption required for signal transmission under different conditions. Optionally, the energy consumption correction coefficient is obtained by: obtaining the mean value of the energy consumption corresponding to the reference data in the reference data set, and obtaining the mean value of the energy consumption of the reference data under theoretical conditions corresponding to the transmission distance and transmission power, and calculating the ratio of the two to obtain the energy consumption correction coefficient. The technology of evaluating energy consumption by sending signals and receiving signals is a prior art and will not be repeated here. Optionally, the coordinates of the target drone and the coordinates of the user are obtained respectively, where the coordinates of the user refer to the coordinates of the operator of the target drone, and the Euclidean distance between the coordinates of the target drone and the coordinates of the user is calculated to obtain the transmission distance. The reference energy consumption value here represents the energy consumption value required when switching from the initial communication scheme to the reference communication scheme. Optionally, the reference energy consumption value is obtained by an orthogonal experiment.

[0146] It should be understood that the smaller the delay probability, the higher the reliability of the signal when the fitting factor group is used to transmit the signal, that is, the signal is less likely to be delayed. The smaller the mean delay, the less time required to transmit the signal using the fitting factor group. The greater the target transmission probability, the smaller the probability of packet loss or data damage when the fitting factor group is used to transmit the signal. Therefore, the smaller the scheme evaluation value, the more suitable the fitting factor group corresponding to the scheme evaluation value is for the current environment in which the target UAV is located.

[0147] S6. According to multiple scheme evaluation values, a target communication scheme is identified from multiple reference communication schemes, wherein the target communication scheme is a reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme update unit.

[0148] The definition of the initial communication scheme is the same as that of the reference communication scheme, that is, after the relevant data of the drone during communication is set, the scheme determined by the relevant data, where the relevant data is the data corresponding to the influencing factor. Updating the initial communication scheme using the target communication scheme and the scheme updating unit means selecting different data from the data corresponding to the initial communication scheme and the data corresponding to the target communication scheme, and updating the data in the initial communication scheme using the different data corresponding to the target communication scheme.

[0149] Exemplarily, the frequency band of the signal in the initial communication scheme is 2.4GHZ, the modulation method is amplitude modulation, and the channel is radio waves. The frequency band of the signal in the target communication scheme is 5.8GHZ, the modulation method is phase modulation, and the signal is radio waves. The frequency band and modulation method in the initial communication scheme are updated using the frequency band and modulation method in the target communication scheme, so that the frequency band of the updated communication scheme is 5.8GHZ, and the modulation method is phase modulation.

[0150] S7. Obtain a public key and a private key based on the scheme evaluation value corresponding to the target communication scheme, the monitoring time interval and the target communication scheme, and use the public key to perform an encryption operation on the pre-acquired target sending signal to obtain an initial encrypted signal.

[0151] It should be explained that the obtaining of the public key and the private key based on the scheme evaluation value, the monitoring time interval and the target communication scheme includes:

[0152] The first prime number is calculated using the scheme evaluation value, the monitoring time interval, the target communication scheme and the pre-constructed first prime number relationship expression, wherein the first prime number relationship expression is as follows:

[0153] s=random<[[Z] [t] +H1+H2+H3]>

[0154] Wherein, s represents the first prime number, [] represents a rounding operation, H1, H2, and H3 represent the data volume of the three reference recognition models corresponding to the target communication scheme in the storage unit, < > represents taking a prime number, and random represents taking a random number;

[0155] The second prime number is calculated based on the first prime number and a pre-constructed second prime number relationship, wherein the second prime number relationship is as follows:

[0156]

[0157] Wherein, S represents the second prime number, and A is the preset coefficient;

[0158] A public key and a private key are obtained using the first prime number and the second prime number.

[0159] Furthermore, the technology of obtaining the public key and the private key using the first prime number and the second prime number is an existing technology and will not be described in detail here. Optionally, the method of obtaining prime numbers is: the sieve of Eratosthenes method. The same effect can be achieved by using other technologies and will not be described in detail here. The technology of performing encryption operations on the initial transmission signal using the public key is an existing technology and will not be described in detail here. The target transmission signal refers to the transmission signal to be sent for controlling the drone, and the difference between the target transmission signal and the initial transmission signal is that the target transmission signal has not been executed, and the initial transmission signal has been executed.

[0160] S8. After sending the private key and the initial encrypted signal to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

[0161] It is understandable that the technology of using a private key to perform a decryption operation on an initial encrypted signal is a prior art and will not be described in detail here.

[0162] Therefore, the influencing factor group set of this embodiment includes multiple influencing factor groups, which take into account multiple parameters that may affect the communication status of the target UAV, thereby laying a foundation for improving the intelligence of the communication supervision of the target UAV. At the same time, different reference data sets are obtained in combination with different fitting factor groups to improve the intelligence level in dynamic supervision of UAV communications.

[0163] Furthermore, when obtaining the monitoring time interval, this embodiment takes into account the environment in which the UAV is located, and obtains the monitoring time interval based on the environment in which the UAV is located. By dynamically obtaining the monitoring time interval, the intelligence level of dynamic supervision of UAV communications is improved, and the target communication scheme and the scheme update unit are used to update the initial communication scheme, so as to dynamically update the communication scheme in combination with the environment in which the UAV is located. When updating the communication scheme, the scheme evaluation value corresponding to different communication schemes is calculated, and by setting the scheme evaluation threshold, excessive updating of the communication scheme is avoided, thereby improving the intelligence level of UAV communication supervision.

[0164] In addition, this embodiment also drives the target UAV based on the target encrypted signal, and returns to the step of confirming the monitoring time interval based on the environmental collection instruction, so as to dynamically update the communication scheme and combine the relevant parameters in different time periods to solve the public key used to encrypt the initial sending signal, thereby improving the security of the UAV during communication.

[0165] Embodiment 2:

[0166] like Figure 2 As shown, this embodiment provides a functional module diagram of a UAV dynamic communication supervision system.

[0167] The unmanned aerial vehicle dynamic communication supervision system 100 of the present invention can be installed in an electronic device. According to the functions to be implemented, the unmanned aerial vehicle dynamic communication supervision system 100 can include a communication database construction module 101, a unmanned aerial vehicle dynamic monitoring module 102, a communication scheme confirmation module 103 and a communication signal dynamic encryption and update module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0168] The communication database construction module 101 is used to identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a solution construction unit and a solution update unit;

[0169] Confirming receipt of a solution construction instruction from a solution construction unit, and acquiring an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes a plurality of impact factor groups, and each impact factor group includes one or more impact factors;

[0170] constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups;

[0171] The UAV dynamic monitoring module 102 is used to confirm the receipt of the environment collection instruction from the environment collection unit, confirm the monitoring time interval based on the environment collection instruction, and obtain the communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal;

[0172] The communication scheme confirmation module 103 is used to retrieve multiple reference communication schemes from a reference communication database using the communication data, and obtain multiple scheme evaluation values ​​based on the multiple reference communication schemes, wherein the scheme evaluation values ​​correspond to the reference communication schemes one by one;

[0173] According to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme updating unit;

[0174] The communication signal dynamic encryption and update module 104 is used to obtain a public key and a private key based on the scheme evaluation value corresponding to the target communication scheme, the monitoring time interval and the target communication scheme, and use the public key to perform an encryption operation on the pre-acquired target transmission signal to obtain an initial encrypted signal;

[0175] After the private key and the initial encrypted signal are sent to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

[0176] In detail, each module in the unmanned aerial vehicle dynamic communication monitoring system 100 in the embodiment of the present invention is used in the same manner as described above. Figure 1 The technical means are the same as the UAV dynamic communication supervision method described in, and can produce the same technical effects, so I will not go into details here.

[0177] like Figure 3 , is a schematic diagram of the structure of an electronic device for implementing a method for dynamic communication supervision of a drone provided by an embodiment of the present invention.

[0178] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as the unmanned aerial vehicle dynamic communication supervision method program described in Example 1.

[0179] The memory 11 includes at least one type of readable storage medium, including flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, disk, optical disk, etc.

[0180] In some embodiments, the processor 10 can be composed of an integrated circuit, which uses various interfaces and lines to connect the various components of the entire electronic device, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules stored in the memory 11 (such as the unmanned aerial vehicle dynamic communication supervision method program described in Example 1, etc.), and calling the data stored in the memory 11.

[0181] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus.

[0182] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0183] The unmanned aerial vehicle dynamic communication supervision method program stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, the unmanned aerial vehicle dynamic communication supervision method described in Example 1 can be implemented.

[0184] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0185] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can implement the method for dynamic communication supervision of the unmanned aerial vehicle described in Example 1.

[0186] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0187] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for monitoring dynamic communication of unmanned aerial vehicles, characterized in that: The method comprises: Identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a plan construction unit and a plan update unit; Confirming receipt of a solution construction instruction from a solution construction unit, and acquiring an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes a plurality of impact factor groups, and each impact factor group includes one or more impact factors; constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups; Confirming receipt of an environment collection instruction from an environment collection unit, confirming a monitoring time interval based on the environment collection instruction, and acquiring communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal; Retrieving a plurality of reference communication schemes from a reference communication database using the communication data, and acquiring a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes, wherein the scheme evaluation values ​​correspond one to one to the reference communication schemes; According to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme updating unit; Acquire a public key and a private key based on a scheme evaluation value corresponding to the target communication scheme, a monitoring time interval, and the target communication scheme, and use the public key to perform an encryption operation on a pre-acquired target transmission signal to obtain an initial encrypted signal; After the private key and the initial encrypted signal are sent to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

2. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 1, characterized in that: The step of constructing a plurality of fitting factor groups based on the influencing factor group set includes: In a combined form, one or more influencing factors corresponding to each influencing factor group in the influencing factor group set are used to obtain a fitting factor group, wherein the fitting factor group is as follows: N={and 1a ,and 2b ,…,and nc } Where N represents the fitting factor group, y 1a represents the ath impact factor corresponding to the first impact factor group in the impact factor group set, y 2b represents the bth impact factor corresponding to the second impact factor group in the impact factor group set, y nc represents the cth impact factor corresponding to n impact factor groups in the impact factor group set, and n represents that there are n impact factor groups in the impact factor group set; The fitting factor groups are aggregated to obtain multiple fitting factor groups.

3. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 2, characterized in that: The step of determining a reference communication database based on the plurality of fitting factor groups comprises: Extract fitting factor groups from the multiple fitting factor groups in sequence, and perform the following operations on the extracted fitting factor groups: A reference data set is identified based on the extracted fitting factor group, wherein the reference data set includes a plurality of reference data, and the reference data includes a transmitted signal, a received signal, a signal delay, a transmitted signal characteristic value, and a received signal characteristic value; Extract reference data from the reference data set in sequence, and perform the following operations on the extracted reference data: Acquire a signal recognition model set for identifying a signal transmission state, wherein the signal recognition model set includes at least three signal recognition models, the signal recognition models in the signal recognition model set are stored in a pre-built storage unit, and the signal transmission state is: a line-of-sight transmission state or a non-line-of-sight transmission state; Randomly extract three signal recognition models from the signal recognition model set to obtain three target recognition models, and obtain a recognition state set using the three target recognition models, a transmitted signal corresponding to the reference data, and a received signal corresponding to the reference data, wherein the recognition state set includes three signal recognition states, and the signal recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state; Using the line-of-sight transmission state and the non-line-of-sight transmission state, respectively counting the number of signal recognition states in the recognition state set to obtain a first statistical number and a second statistical number, using the first statistical number and the second statistical number to confirm the target transmission state, and using the target transmission state to perform an identification operation on the extracted reference data to obtain identification data; A reference communication database is identified based on the identification data.

4. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 3, characterized in that: The step of confirming a reference communication database based on the identification data comprises: comparing the characteristic value of the transmitted signal with the characteristic value of the received signal; If the characteristic value of the transmitted signal is equal to the characteristic value of the received signal, the identification data is confirmed as the first transmission data, and the number of the first transmission data and the number of reference data in the reference data set are counted respectively to obtain a first transmission number and a first reference number; Calculating a target transmission probability using the first transmission quantity and the first reference quantity, wherein the target transmission probability is a ratio of the first transmission quantity to the first reference quantity; A signal transmission tree structure is constructed with signal transmission as a root node, each of the multiple fitting factor groups as a first child node, and a target transmission state second child node corresponding to the identification data; A reference communication database is constructed based on the target transmission probability and the signal transmission tree structure.

5. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 4, characterized in that: The constructing a reference communication database based on the target transmission probability and the signal transmission tree structure includes: Extracting an initial analysis data set from the signal transmission tree structure, wherein the initial analysis data set is identification data corresponding to the second child node, and using a preset delay threshold to identify a target analysis data set in the initial analysis data set, wherein the target analysis data set includes a plurality of target analysis data, and the signal delays corresponding to the target analysis data are all less than or equal to the delay threshold; Obtaining a delay probability using the target analysis data set and the initial analysis data set, and obtaining a delay mean value according to the target analysis data set, wherein the delay mean value is the mean value of signal delays corresponding to multiple target analysis data in the target analysis data set; The delay probability, the delay mean and the target transmission probability are used to perform an identification operation on the second subnode to obtain an identified second subnode, and the identified second subnode is used to update the second subnode corresponding to the initial analysis data set to obtain a reference communication database.

6. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 5, characterized in that: The determining of the monitoring time interval based on the environment collection instruction includes: Parsing the environment acquisition instruction to obtain a detection angle set, wherein the detection angle set includes multiple detection angles, and using the detection angle set to obtain a detection distance set, wherein the detection distance set includes multiple detection distances, and the detection distances correspond to the detection angles one by one; The monitoring time interval is calculated based on the detection distance set, wherein the monitoring time interval is as follows: if min(l1,l2,…,l e )≥l0,t=t0 Among them, min means taking the minimum value, l1, l2, l j , l e They respectively represent the first detection distance, the second detection distance, the jth detection distance and the eth detection distance in the detection distance set, l0 is the preset distance threshold, t0 is the preset interval time threshold, e means that there are e detection distances in the detection distance set, and t represents the monitoring time interval.

7. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 6, characterized in that: The step of retrieving a plurality of reference communication schemes from a reference communication database using the environment data comprises: Randomly extracting three reference recognition models from the signal recognition model set, and confirming a reference recognition state based on an initial transmitted signal, an initial received signal, and the three extracted reference recognition models, wherein the reference recognition state is a line-of-sight transmission state or a non-line-of-sight transmission state; Using the reference identification state, multiple target second sub-nodes are retrieved from a reference communication database, wherein the target transmission state corresponding to the target second sub-node is the reference identification state, and wherein the fitting factor group corresponding to each of the multiple target second sub-nodes is the reference communication scheme.

8. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 7, characterized in that: The acquiring a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes comprises: The following operations are performed for each of the multiple reference communication schemes: A comprehensive evaluation relationship is constructed, and the scheme evaluation value is calculated using the comprehensive evaluation relationship and the reference communication scheme, where the comprehensive evaluation relationship is as follows: Among them, Z represents the scheme evaluation value, θ, γ, ω, and β are all preset coefficients, α1 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the line-of-sight transmission state, α2 represents the energy consumption correction coefficient when the target transmission state corresponding to the reference communication scheme is the non-line-of-sight transmission state, P represents the transmission power, d represents the transmission distance, and p1 represents the delay probability. represents the mean delay, p2 represents the target transmission probability, C represents the reference energy consumption value, and the reference energy consumption value is related to the initial communication scheme and the reference communication scheme.

9. The method for monitoring dynamic communication of unmanned aerial vehicles according to claim 8, characterized in that: The obtaining of the public key and the private key based on the scheme evaluation value, the monitoring time interval and the target communication scheme includes: The first prime number is calculated using the scheme evaluation value, the monitoring time interval, the target communication scheme and the pre-constructed first prime number relationship expression, wherein the first prime number relationship expression is as follows: s=random<[[Z] [t] +H1+H2+H3]> Wherein, s represents the first prime number, [] represents a rounding operation, H1, H2, and H3 represent the data volume of the three reference recognition models corresponding to the target communication scheme in the storage unit, <> represents taking a prime number, and random represents taking a random number; The second prime number is calculated based on the first prime number and a pre-constructed second prime number relationship, wherein the second prime number relationship is as follows: Wherein, S represents the second prime number, and A is the preset coefficient; A public key and a private key are obtained using the first prime number and the second prime number.

10. A UAV dynamic communication monitoring system, characterized in that: The system comprises: A communication database construction module is used to identify the target UAV to be supervised and the communication supervision system, wherein the communication supervision system includes: an environment collection unit, a solution construction unit and a solution update unit; Confirming receipt of a solution construction instruction from a solution construction unit, and acquiring an impact factor group set based on the solution construction instruction, wherein the impact factor group set includes a plurality of impact factor groups, and each impact factor group includes one or more impact factors; constructing a plurality of fitting factor groups based on the influencing factor group set, and confirming a reference communication database based on the plurality of fitting factor groups; The UAV dynamic monitoring module is used to confirm the receipt of the environment collection instruction from the environment collection unit, confirm the monitoring time interval based on the environment collection instruction, and obtain the communication data of the target UAV based on the monitoring time interval, wherein the communication data includes: an initial transmission signal and an initial reception signal; a communication scheme confirmation module, configured to retrieve a plurality of reference communication schemes from a reference communication database using the communication data, and obtain a plurality of scheme evaluation values ​​based on the plurality of reference communication schemes, wherein the scheme evaluation values ​​correspond one to one with the reference communication schemes; According to the multiple scheme evaluation values, a target communication scheme is identified from the multiple reference communication schemes, wherein the target communication scheme is the reference communication scheme corresponding to the smallest scheme evaluation value, and the scheme evaluation value corresponding to the target communication scheme is greater than a preset scheme evaluation threshold, an initial communication scheme of the target UAV is obtained, and the initial communication scheme is updated using the target communication scheme and the scheme updating unit; A communication signal dynamic encryption and update module, used to obtain a public key and a private key based on the scheme evaluation value corresponding to the target communication scheme, the monitoring time interval and the target communication scheme, and use the public key to perform an encryption operation on the pre-acquired target transmission signal to obtain an initial encrypted signal; After the private key and the initial encrypted signal are sent to the target UAV, the initial encrypted signal is decrypted using the private key to obtain the target encrypted signal, the target UAV is driven based on the target encrypted signal, and the step of confirming the monitoring time interval based on the environment acquisition instruction is returned to achieve supervision of the target UAV communication.

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