A data processing method, device, apparatus, and storage medium

Abstract

The application belongs to the technical field of sensing integration, and particularly relates to a data processing method, device, equipment and storage medium. The method comprises the following steps: acquiring sensing data by a first unmanned aerial vehicle; determining a channel environment of a current channel of the sensing data and environment data of a region where the first unmanned aerial vehicle is located according to the sensing data; determining a target waveform modulation scheme matched with the environment of the current channel according to the channel environment and a waveform modulation strategy; modulating the environment data according to the target waveform modulation scheme and sending the modulated environment data to a first server; acquiring the environment data sent by the first unmanned aerial vehicle by the first server; pre-processing the modulated environment data to obtain abnormal data; and sending the abnormal data to a second unmanned aerial vehicle. Therefore, higher efficient and reasonable waveform adaptation is realized according to the differentiated real-time channel environment, the transmission comprehensive efficiency in the communication process is improved, the calculation amount of the server is reduced, and the service performance of the server is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of integrated sensing and communication, and in particular to a data processing method and device, equipment and storage medium. BACKGROUND

[0002] Currently, with the continuous evolution of 5G to 6G in terms of technology and business, in order to improve the end-to-end information processing capability, future communication systems should have both communication and sensing capabilities, so integrated sensing and communication (ISAC) has become a key development technology for future communication systems. An unmanned aerial vehicle (UAV) is a non-personnel aircraft that is controlled by using radio remote control equipment and self-provided program control devices. With the widespread use of unmanned aerial vehicles in the field of intelligent transportation, when unmanned aerial vehicles fly in high dynamic flight environments, they face complex environmental changes such as landslides, road collapses, and traffic accidents. Real-time environmental changes occur in the communication channel of the unmanned aerial vehicle. At this time, if a single waveform is still used for communication, the transmission comprehensive efficiency of the unmanned aerial vehicle in the communication process will be low. At the same time, when the unmanned aerial vehicle detects abnormal environmental changes, it cannot timely inform other unmanned aerial vehicles of the abnormal environmental changes in the region, increasing the computational load of the server.

[0003] The existing data processing method is mostly to construct an integrated waveform optimization model through the topological relationship between the unmanned aerial vehicle and the communication user and the sensing target, and obtain a beamforming vector of an integrated waveform that can simultaneously carry communication symbol information and sense the target to be measured.

[0004] However, in the above method, only the waveform that can realize integrated sensing and communication is obtained, and the problems of low transmission comprehensive efficiency caused by using a single waveform for communication when the unmanned aerial vehicle faces environmental changes, and the problem of not being able to timely inform other unmanned aerial vehicles of abnormal environmental changes in the region, increasing the computational load of the server, are not solved. SUMMARY

[0005] The present application provides a data processing method, device, equipment and storage medium to solve the problems of low communication transmission comprehensive efficiency and server overload in the existing data processing method.

[0006] In one aspect, the present application provides a data processing method applied to a first unmanned aerial vehicle, comprising:

[0007] Obtaining sensing data, the sensing data being obtained by a radio frequency transceiver module, an airborne radar and an airborne camera device;

[0008] determine a channel environment of a current channel of the perception data and environment data of a region where the first unmanned aerial vehicle is located according to the perception data;

[0009] determine a target waveform modulation scheme matching the environment of the current channel according to the channel environment and a waveform modulation strategy, the target waveform modulation scheme being used to instruct to modulate the environment data in a target waveform, the waveform modulation strategy being determined according to transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms;

[0010] modulate the environment data according to the target waveform modulation scheme and send the modulated environment data to a first server.

[0011] Optionally, before the perception data is acquired, the method further includes:

[0012] acquire waveform information of a plurality of waveforms in a preset time period, the waveform information including: waveform transmission bit error rate, perception accuracy, number of complex number operation units during modulation or demodulation, probability of being selected under different channel environments, and adaptation to different channel environments;

[0013] determine transmission comprehensive performance of each waveform under different channel environments according to the waveform information;

[0014] determine a candidate waveform corresponding to each channel environment according to the transmission comprehensive performance of each waveform under different channel environments, the transmission comprehensive performance of the candidate waveform being greater than that of other waveforms under each channel environment;

[0015] formulate the waveform modulation strategy according to the candidate waveform corresponding to each channel environment.

[0016] Optionally, the determining of the transmission comprehensive performance of each waveform under different channel environments according to the waveform information includes:

[0017] the transmission comprehensive performance of the waveform under different channel environments is determined by using the following formula:

[0018]

[0019] wherein, E i is the transmission comprehensive performance of the waveform i under each channel environment within time from 0 to T, F i is the adaptation of the waveform i under each channel environment, S i is the perception accuracy of the waveform i under each channel environment, e i is the waveform transmission bit error rate of the waveform i under each channel environment, C i is the number of complex number operation units of the waveform i during modulation or demodulation under each channel environment, and p iThe selected probability of the waveform i in each channel environment.

[0020] Optionally, the determining of the candidate waveform corresponding to each channel environment according to the transmission comprehensive performance of each waveform in different channel environments comprises:

[0021] According to a plurality of channel environments, the transmission comprehensive performance is classified to obtain a transmission comprehensive performance set of a plurality of waveforms in each channel environment;

[0022] The maximum comprehensive performance in each channel environment is determined from the transmission comprehensive performance set of the plurality of waveforms.

[0023] For each channel environment, the waveform corresponding to the maximum comprehensive performance is taken as a candidate waveform.

[0024] In a second aspect, the application provides a data processing method applied to a first server, comprising:

[0025] Obtaining environment data modulated according to a target waveform modulation scheme and sent by a first unmanned aerial vehicle;

[0026] Pretreating the modulated environment data to obtain abnormal data, the abnormal data being used to indicate an abnormality existing in the region where the first unmanned aerial vehicle is located.

[0027] Sending the abnormal data to a second unmanned aerial vehicle, the second unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the first server, and the second unmanned aerial vehicle being different from the first unmanned aerial vehicle.

[0028] Optionally, the method further comprises:

[0029] Generating abnormal information according to the abnormal data and sending the abnormal information to a second server, so that the second server performs deep processing on the abnormal information, and when it is confirmed that the abnormal information is correct, sends the abnormal data to a third unmanned aerial vehicle, the third unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the second server, and the third unmanned aerial vehicle not being in communication connection with the first server.

[0030] In a third aspect, the application provides a data processing device applied to a first unmanned aerial vehicle, the device comprising:

[0031] An acquisition module, configured to acquire sensing data, the sensing data being acquired by a radio frequency transceiver module, an airborne radar and an airborne shooting device;

[0032] A determination module, configured to determine, according to the sensing data, a channel environment of a current channel of the sensing data and environment data of a region where the first unmanned aerial vehicle is located.

[0033] The determining module is further configured to determine a target waveform modulation scheme matching the environment of the current channel according to the channel environment and a waveform modulation strategy, the target modulation scheme being used to instruct to modulate the environment data according to a target waveform, and the waveform modulation strategy being determined according to transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms.

[0034] The processing module is configured to modulate the environment data according to the target waveform modulation scheme.

[0035] The sending module is configured to send the modulated environment data to a first server.

[0036] Optionally, the obtaining module is further configured to obtain waveform information of a plurality of waveforms in a preset time period, the waveform information including: waveform transmission bit error rate, sensing accuracy, number of complex operation units during modulation or demodulation, probability of being selected under different channel environments, and adaptation to different channel environments.

[0037] The processing module is further configured to determine transmission comprehensive performance of each waveform under different channel environments according to the waveform information.

[0038] The processing module is further configured to determine a candidate waveform corresponding to each channel environment according to the transmission comprehensive performance of each waveform under different channel environments, and the transmission comprehensive performance of the candidate waveform is greater than that of other waveforms under each channel environment.

[0039] Optionally, the processing module is specifically configured to: perform classification processing on the transmission comprehensive performance according to a plurality of channel environments to obtain a transmission comprehensive performance set of a plurality of waveforms under each channel environment; determine a maximum comprehensive performance under each channel environment from the transmission comprehensive performance set of the plurality of waveforms; and take a waveform corresponding to the maximum comprehensive performance as a candidate waveform for each channel environment.

[0040] Optionally, the processing module is further configured to formulate the waveform modulation strategy according to the candidate waveform corresponding to each channel environment.

[0041] Optionally, the processing module is further configured to determine the transmission comprehensive performance of the waveform under different channel environments by using the following formula:

[0042]

[0043] wherein, E i is the transmission comprehensive performance of the waveform i under each channel environment within time from 0 to T, F i is the adaptation of the waveform i under each channel environment, S i is the sensing accuracy of the waveform i under each channel environment, and e iC is the waveform transmission error rate of waveform i in each channel environment i P is the number of complex number operation units of waveform i in each channel environment when modulating or demodulating i is the selected probability of waveform i in each channel environment.

[0044] In a fourth aspect, the present application provides a data processing apparatus, applied to a first server, comprising:

[0045] An acquisition module, configured to acquire environment data modulated according to a target waveform modulation scheme and sent by a first unmanned aerial vehicle;

[0046] A processing module, configured to pre-process the modulated environment data to obtain abnormal data, the abnormal data being used to indicate an abnormality existing in a region where the first unmanned aerial vehicle is located.

[0047] A sending module, configured to send the abnormal data to a second unmanned aerial vehicle, the second unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the first server, and the second unmanned aerial vehicle being different from the first unmanned aerial vehicle.

[0048] Optionally, the processing module is further configured to generate abnormal information according to the abnormal data.

[0049] The sending module is further configured to send the abnormal information to a second server, so that the second server performs deep processing on the abnormal information, and sends the abnormal data to a third unmanned aerial vehicle when confirming that the abnormal information is correct, the third unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the second server, and the third unmanned aerial vehicle not being in communication connection with the first server.

[0050] In a fifth aspect, the present application provides a data processing device, comprising:

[0051] A memory;

[0052] A processor;

[0053] The memory stores computer execution instructions.

[0054] The processor executes the computer execution instructions stored in the memory, so as to implement the data processing method in the above first aspect and various possible implementation manners of the first aspect, or the data processing method in the above second aspect and various possible implementation manners of the second aspect.

[0055] In a sixth aspect, the present application provides a computer readable storage medium, which stores a computer program, the computer program being executed by a processor to implement the data processing method in the above first aspect and various possible implementation manners of the first aspect, or the data processing method in the above second aspect and various possible implementation manners of the second aspect.

[0056] The data processing method provided in the application is applied to a first unmanned aerial vehicle. The method comprises the following steps: acquiring sensing data; determining a channel environment of a current channel of the sensing data and environment data of a region where the first unmanned aerial vehicle is located according to the sensing data; determining a target waveform modulation scheme matched with the environment of the current channel according to the channel environment and a waveform modulation strategy; modulating the environment data according to the target waveform modulation scheme and sending the modulated environment data to a first server; and thereby realizing that, when an abnormal target is detected, the unmanned aerial vehicle utilizes communication and sensing integration technology, performs more efficient and reasonable waveform adaptation according to a differentiated real-time channel environment, and improves transmission efficiency in the communication process. BRIEF DESCRIPTION OF DRAWINGS

[0057] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0058] Figure 1 A scene schematic diagram of the data processing method provided in the application;

[0059] Figure 2 A flowchart of the data processing method provided in the application Figure One ;

[0060] Figure 3 A flowchart of the data processing method provided in the application Figure Two ;

[0061] Figure 4 A flowchart of the data processing method provided in the application Figure Three ;

[0062] Figure 5 A structure schematic diagram of the data processing device provided in the application Figure One ;

[0063] Figure 6 A structure schematic diagram of the data processing device provided in the application Figure Two ;

[0064] Figure 7 A structure schematic diagram of the data processing device provided in the application

[0065] The specific embodiments of the application have been shown in the above drawings, and will be described in more detail hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the application in any way, but to illustrate the concept of the application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0066] In order to make the purposes, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in conjunction with the drawings in the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the scope of protection of the present application.

[0067] The terms "first", "second", "third", "fourth" and the like in the description, claims, and drawings of the present application, and the above-described drawings (if any) are used to distinguish similar objects, and do not necessarily have to be described in a specific order or chronological order. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented, for example, in an order other than that illustrated or described herein.

[0068] In the embodiments of the present application, the words "exemplary" or "for example" are used to mean example, instance, or illustration. Any embodiment or design presented as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or advantageous than other embodiments or design solutions. Rather, the use of "exemplary" or "for example" is intended to present relevant concepts in a concrete manner.

[0069] Traditional communication technology and sensing technology are developed and evolved independently. Common communication technologies such as 4G and 5G, and common sensing technologies such as measuring the speed of a car and detecting changes in the environment. This makes it difficult to meet the actual needs of applications such as unmanned aerial vehicle target detection, which require access to two independent networks to meet the actual needs, resulting in high costs and information that cannot be strictly synchronized. Integrated sensing and communication technology (ISAC) is currently a hot research topic in the field of communication, which means that communication technology and sensing technology are integrated, and the surrounding environment is perceived while communicating, thereby providing better services.

[0070] An unmanned aerial vehicle (UAV) is a non-crewed aircraft that is controlled by radio remote control equipment and self-provided program control devices. With the widespread use of unmanned aerial vehicles in the field of intelligent transportation, when the unmanned aerial vehicle flies in a high dynamic flight environment, it faces complex environmental changes such as landslides, road collapses, and traffic accidents. Real-time environmental changes occur in the communication channel of the unmanned aerial vehicle. At this time, if a single waveform that does not change is still used for communication, it will result in low transmission comprehensive efficiency of the unmanned aerial vehicle in the communication process. At the same time, when the unmanned aerial vehicle detects abnormal environmental changes, it cannot timely inform other unmanned aerial vehicles of the abnormal environmental changes in the region, increasing the computational load of the server.

[0071] The existing data processing method is mostly to construct an integrated waveform optimization model by the topological relationship between the unmanned aerial vehicle and the communication user and the perceived target, so as to obtain a beamforming vector of an integrated waveform capable of simultaneously bearing communication symbol information and perceiving the target to be measured.

[0072] However, in the above method, only the waveform capable of realizing the integration of communication and perception is obtained, and the problems of low transmission comprehensive efficiency caused by the single waveform used for communication when the unmanned aerial vehicle faces environmental changes and the problem of increasing the calculation amount of the server caused by the inability to timely inform other unmanned aerial vehicles of abnormal environmental changes in the region are not solved.

[0073] In view of the above problems, the present application provides a data processing method, Figure 1 The scene diagram of the data processing method provided by the present application is shown. It should be noted that Figure 1 The shown is only an example of an application scenario to which the data processing method of the present application can be applied, to help those skilled in the art understand the technical content of the present application, but does not mean that the embodiments of the present application cannot be used in other devices, systems, environments or scenarios.

[0074] As Figure 1 shown, the unmanned aerial vehicle 1 is in communication connection with the server 2, and the server 2 is in communication connection with the server 3. The server 2 may, for example, be an edge server in communication connection with the unmanned aerial vehicle 1, that is, the server 2 is the closest server to the unmanned aerial vehicle 1; the server 3 may, for example, be a server of the unmanned aerial vehicle platform of the unmanned aerial vehicle 1.

[0075] It can be understood that the unmanned aerial vehicle will be in communication connection with the closest edge server when performing a task. Each server 2 is in communication connection with multiple unmanned aerial vehicles, and the server 3 can be in communication connection with all unmanned aerial vehicles performing a task and issue instructions to the corresponding unmanned aerial vehicles.

[0076] The unmanned aerial vehicle 1 can detect abnormal road conditions during flight, which may, for example, include road collapse, traffic accident, etc., and can obtain the detected perception data through a radio frequency transceiver module, an airborne radar and an airborne camera (not shown), and send the obtained perception data to the closest edge server 2. Figure 1

[0077] After obtaining the perception data sent by the unmanned aerial vehicle 1, the edge server 2 will preprocess the perception data and execute corresponding programs according to the preprocessing result. At the same time, the edge server 2 can also feed back the result obtained by preprocessing to the unmanned aerial vehicle platform server 3, so that the unmanned aerial vehicle platform server 3 sends instructions to other unmanned aerial vehicles.

[0078] ​The data processing method provided in the application formulates a waveform modulation strategy according to the transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms, determines a target waveform modulation scheme matched with a current channel environment according to current channel environment information obtained by a first unmanned aerial vehicle and the waveform modulation strategy, modulates environment data of a region where the unmanned aerial vehicle is located according to the target waveform modulation scheme, and sends the modulated environment data to a first server in communication connection with the first unmanned aerial vehicle. The method utilizes communication and perception integrated technology, realizes more efficient and reasonable waveform adaptation of the unmanned aerial vehicle according to a differential real-time channel environment when an abnormal target is detected, and improves transmission efficiency in the communication process.

[0079] The technical solutions of the application and how the technical solutions solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the application will be described below with reference to the drawings.

[0080] Figure 2 is a flow of the data processing method provided in the embodiments of the application Figure One The execution subject of the embodiment may, for example, be an unmanned aerial vehicle 1 as shown in the embodiments, as shown in the embodiments, the data processing method shown in the embodiment includes: Figure 1 Figure 2 S101: Obtain perception data, wherein the perception data is obtained by a radio frequency transceiver module, an airborne radar, and an airborne camera.

[0081] S101: Obtain perception data, wherein the perception data is obtained by a radio frequency transceiver module, an airborne radar, and an airborne camera.

[0082] The perception data may, for example, include communication perception data and video perception data. When the perception data is communication perception data, the communication perception data is obtained by the radio frequency transceiver module and the airborne radar; when the perception data is video perception data, the video perception data is obtained by the airborne camera.

[0083] In this step, the first unmanned aerial vehicle can detect the road environment in real time through the radio frequency transceiver module, the airborne radar, and the airborne camera.

[0084] S102: Determine a channel environment of a current channel of the perception data and environment data of a region where the first unmanned aerial vehicle is located according to the perception data.

[0085] The channel refers to a medium or channel for transmitting information in a communication system, and the channel environment refers to the environment of the channel for transmitting signals. The environment data of the region where the first unmanned aerial vehicle is located is used to indicate the surrounding space information of the region.

[0086] ​It can be understood that when the environment of the first unmanned aerial vehicle changes abnormally, the communication channel of the unmanned aerial vehicle also changes in real time, that is, the sensing data obtained by the radio frequency transceiver module, the airborne radar and the airborne camera of the first unmanned aerial vehicle can obtain the channel environment of the current channel and the environment data of the region where the first unmanned aerial vehicle is located.

[0087] Since the sensing data includes the channel environment data of the current channel and the environment data of the region where the first unmanned aerial vehicle is located and other data, the sensing data can be classified after being obtained to separate the sensing data of different types, so as to obtain the channel environment of the current channel and the environment data of the region where the first unmanned aerial vehicle is located.

[0088] The step of determining the channel environment of the current channel is to select the optimal waveform to modulate the data, so as to improve the transmission efficiency of the transmitted data; and the step of determining the environment data is to enable the server to determine whether the region where the first unmanned aerial vehicle is located is abnormal according to the environment data.

[0089] S103: determining a target waveform modulation scheme matching the environment of the current channel according to the channel environment and the waveform modulation strategy, the target waveform modulation scheme being used to instruct to modulate the environment data according to a target waveform, and the waveform modulation strategy being determined according to the transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms.

[0090] The waveform modulation strategy is used to indicate the corresponding relationship between different channel environments and different waveforms; for example, it can include that when the channel environment is under high communication load demand, the first unmanned aerial vehicle can adopt a multicarrier waveform as the waveform modulation strategy, and when the channel environment is under low communication load demand, the first unmanned aerial vehicle can adopt a single-carrier waveform as the waveform modulation strategy.

[0091] The target waveform is used to indicate the waveform that best matches the channel environment of the current channel. That is, under the channel environment of the current channel, data transmission using the target waveform can obtain the highest transmission comprehensive performance.

[0092] It can be understood that the waveform modulation strategy is a selection mechanism for modulating waveforms in the face of different channel environments, reflects the correlation between channel environments and waveform selection, and is determined according to the transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms. The target waveform modulation scheme refers to the waveform modulation scheme matching the environment of the current channel determined according to the environment of the current channel and the waveform modulation strategy.

[0093] Since different channel environments have their corresponding waveform modulation strategies, the target waveform modulation scheme matching the environment of the current channel can be determined according to the channel environment and the waveform modulation strategy.

[0094] The following example illustrates the waveform modulation strategy derived from a cooperative game theory model:

[0095] Game player: The first type of drone can transmit and receive various waveforms i;

[0096] Game strategy: The overall transmission efficiency e of each waveform i under various channel conditions. i ;

[0097] Utility function: Utility function u i Let r represent the preference of the i-th player. The overall transfer performance is used for evaluation, and all strategy combinations are denoted as r = (r1, r2…r…). n The game utility is u = [u1(r1), u2(r2)...u] n (r n )).

[0098] Initial utility: The initial perceived quality that must be ensured in a game theory model. Initial utility is defined as denoted as... Obtain current utility The transmission error rate is Since the utility under the optimal game strategy must be greater than the initial utility, we can conclude that u > u. 0 , Let the utility set be E, then the game setting is available. <E,u 0 > This indicates that the waveform selection problem is defined as a Nash solution. And u * ( <E,u 0 >) represents the Nash equilibrium point.

[0099] Utility Function: In the utility formula upon which waveform selection is based, considering the stability of the UAV hardware, this model uses the transmission bit error rate as the determining coefficient. Assume E... r The overall performance of a frame is given by ΔD, where ΔD is the distortion caused by transmission errors. The relationship can be expressed as ΔD = E. r ·β, where β is related to the characteristics of different waveforms.

[0100] Different waveforms produce different efficiencies. The above formula can show the mathematical relationship between the two. Under the goal of maximizing overall efficiency, ΔD should be made as small as possible. This formula can be used to assist in the calculation of the subsequent Nash solution.

[0101] To simplify the game theory model, the utility function for the i-th frame is defined as u. i =1 / D i D i This represents the overall performance for each frame. Based on the Nash bargaining model, the cooperative game waveform selection scheme can be obtained, i.e., r. * .

[0102] S104: modulate the environmental data according to the target waveform modulation scheme, and send the modulated environmental data to a first server.

[0103] The first server may be an edge server, which is the closest server to the position of the first UAV.

[0104] In this step, when the target waveform modulation scheme that best matches the channel environment of the current channel is determined, the target waveform modulation scheme is used to modulate the environmental data, thereby improving the transmission comprehensive performance when the first UAV interacts with the first server.

[0105] Because the transmission distance is shorter, the transmission efficiency is higher, and the transmission distance is longer, the transmission efficiency is lower, so sending the modulated environmental data to the edge server closest to the first UAV can reduce the data transmission delay and shorten the communication time, thereby improving the data transmission efficiency.

[0106] The data processing method provided in this embodiment includes: acquiring perception data by a first UAV, determining a channel environment of a current channel of the perception data and environmental data of a region where the first UAV is located according to the perception data; determining a target waveform modulation scheme that matches the current channel environment according to the channel environment and a waveform modulation strategy; modulating the environmental data according to the target waveform modulation scheme, and sending the modulated environmental data to a first server; thereby realizing that when the first UAV detects an abnormal target, the communication and perception integration technology is used to perform more efficient and reasonable waveform adaptation according to the differentiated real-time channel environment, and the transmission comprehensive performance in the communication process is improved.

[0107] Figure 3 The data processing method provided in this embodiment Figure Two This embodiment is based on Figure 2 The data processing method is described in detail. As shown in Figure 3 The data processing method provided in this embodiment includes:

[0108] S201: acquiring waveform information of a plurality of waveforms in a preset time period, the waveform information including: waveform transmission bit error rate, perception accuracy, number of complex operation units during modulation or demodulation, probability of being selected under different channel environments, and adaptation to different channel environments.

[0109] The preset time period may be, for example, a time period in which the UAV has performed a flight task, or a time period in which the flight task is performed in the historical data of the first UAV. The waveform transmission error rate is an index for measuring the accuracy of data transmission within a specified time, and is a commonly used data communication transmission quality index. The sensing accuracy refers to the degree of coincidence between the detected data and the real event in the target area of the communication network, and is related to parameters such as communication transmission rate. The number of complex operation units during modulation or demodulation is exponentially related to the transmission energy consumption parameter, and is related to the complexity of different waveforms. The probability of selection in different channel environments is related to the behavior decision made by the UAV after obtaining the sensing data according to the current channel environment. The behavior decision of the UAV in different channel environments may include, for example, high-speed movement, low-speed movement, hovering, high or low obstacle avoidance demand.

[0110] The adaptation of different channel environments may be preset according to experience values, for example, the UAV may match a multicarrier waveform in a high communication load demand, and may match a single-carrier waveform in a low communication load demand.

[0111] In this step, the waveform information obtained may include waveform information of one waveform, or may include waveform information of multiple waveforms. The waveform information of multiple waveforms within a preset time period may be obtained through a UAV radio frequency transceiver module and an airborne radar.

[0112] S202: According to the waveform information, determine the transmission comprehensive performance of each waveform in different channel environments.

[0113] The transmission comprehensive performance is used to evaluate the matching degree of the waveform and the current channel environment.

[0114] The transmission comprehensive performance is related to the waveform transmission error rate, the sensing accuracy, the number of complex operation units during modulation or demodulation, the probability of selection in different channel environments, and the adaptation of different channel environments. Among them, the waveform transmission error rate has a greater impact on the transmission comprehensive performance.

[0115] In this step, the transmission comprehensive performance of the waveform in different channel environments may be determined by using the following formula:

[0116]

[0117] wherein E i is the transmission comprehensive performance of waveform i in each channel environment within time period 0 to T, F i is the adaptation of waveform i in each channel environment, S i is the sensing accuracy of waveform i in each channel environment, e i is the waveform transmission error rate of waveform i in each channel environment, and C ip is the number of complex number operation units of waveform i in the modulation or demodulation in each channel environment i p is the selected probability of waveform i in each channel environment.

[0118] F i The step value of the function can be determined by the following formula:

[0119]

[0120] Wherein, the transmission comprehensive performance of each waveform in different channel environments cannot be greater than the theoretical maximum transmission comprehensive performance, and the bandwidth resource allocated to each waveform is less than the total bandwidth resource.

[0121] The theoretical maximum transmission comprehensive performance is the transmission comprehensive performance of error-free transmission under ideal conditions, satisfying the Shannon formula, under the condition of no interference in the channel.

[0122] S203: According to the transmission comprehensive performance of each waveform in different channel environments, determine the candidate waveform corresponding to each channel environment, in each channel environment, the transmission comprehensive performance of the candidate waveform is greater than that of other waveforms.

[0123] It can be understood that in each channel environment, different waveforms have different transmission comprehensive performance values, when the transmission comprehensive performance value of a certain waveform is greater than that of other waveforms, the waveform is the corresponding candidate waveform in the channel environment, that is, the waveform with the maximum transmission comprehensive performance value in the current channel environment.

[0124] Optionally, the specific implementation mode of determining the candidate waveform corresponding to each channel environment can be, for example: according to a plurality of channel environments, the transmission comprehensive performance is classified and processed to obtain a plurality of waveform transmission comprehensive performance sets in each channel environment; from the plurality of waveform transmission comprehensive performance sets, the maximum comprehensive performance in each channel environment is determined; for each channel environment, the waveform corresponding to the maximum comprehensive performance is taken as the candidate waveform.

[0125] Wherein, the transmission comprehensive performance set of a plurality of waveforms is obtained by summing the comprehensive performance of all selectable waveforms in a preset period.

[0126] In this step, the following formula can be used to obtain the transmission comprehensive performance set of a plurality of waveforms in each channel environment:

[0127]

[0128] Wherein, E N E is the transmission comprehensive performance of N waveforms in each channel environment from 0 to T, and E iis the transmission comprehensive performance of the waveform i in each channel environment at time T.

[0129] Through the above formula, the transmission comprehensive performance set of multiple waveforms in each channel environment can be determined, and then the maximum comprehensive performance in each channel environment is determined from the transmission comprehensive performance set of multiple waveforms, and the waveform corresponding to the maximum comprehensive performance is taken as the candidate waveform.

[0130] The candidate waveform can be the following waveforms:

[0131] (1) OFDM, anti-multipath, low complexity, high PAPR, belonging to the multi-carrier type;

[0132] (2) GFDM, anti-multipath, low complexity, low PAPR, belonging to the multi-carrier type;

[0133] (3) PSWF, anti-multipath, high complexity, high PAPR, belonging to the multi-carrier type;

[0134] (4) OTFS, anti-multipath, anti-Doppler, high complexity, high PAPR, belonging to the multi-carrier type;

[0135] (5) SC-FDE, low complexity, low PAPR, belonging to the single-carrier type

[0136] S204: Formulate the waveform modulation strategy according to the candidate waveform corresponding to each channel environment.

[0137] Wherein, there is an association relationship between the waveform modulation strategy and the candidate waveform. Different channel environments have a waveform with the maximum transmission comprehensive performance value corresponding thereto, i.e. a target waveform, and through the target waveform, the waveform modulation strategy can be formulated to determine the target waveform modulation scheme matching the current channel environment. For specific methods of formulating the waveform modulation strategy, refer to the waveform modulation method in the prior art.

[0138] S205: Obtain the perception data, which is obtained through the radio frequency transceiver module, the airborne radar and the airborne shooting device.

[0139] Step S205 is similar to step S101 described above, and will not be repeated here.

[0140] S206: Determine the channel environment of the current channel of the perception data and the environmental data of the region where the first unmanned aerial vehicle is located according to the perception data.

[0141] Step S206 is similar to step S102 described above, and will not be repeated here.

[0142] S207: Determine a target waveform modulation scheme matching the environment of the current channel according to the channel environment and the waveform modulation strategy, the target waveform modulation scheme being used to instruct to modulate the environment data according to a target waveform, and the waveform modulation strategy being determined according to the transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms.

[0143] Step S207 is similar to step S103 described above, and will not be described here again.

[0144] S208: Modulate the environment data according to the target waveform modulation scheme, and send the modulated environment data to the first server.

[0145] Step S208 is similar to step S104 described above, and will not be described here again.

[0146] The data processing method provided by the embodiment of the application comprises the following steps: acquiring waveform information of a plurality of waveforms in a preset time period; determining transmission comprehensive performance of each waveform in different channel environments according to the waveform information; determining a candidate waveform corresponding to each channel environment according to the transmission comprehensive performance of each waveform in the different channel environments; formulating the waveform modulation strategy according to the candidate waveform corresponding to each channel environment; acquiring sensing data; determining a channel environment of a current channel of the sensing data and environment data of a region where the first unmanned aerial vehicle is located according to the sensing data; determining a target waveform modulation scheme matching the environment of the current channel according to the channel environment and the waveform modulation strategy; modulating the environment data according to the target waveform modulation scheme, and sending the modulated environment data to the first server; thereby realizing, by the method based on the cooperative game theory, higher efficient and reasonable waveform adaptation according to the differentiated real-time channel environment by using the communication and sensing integrated technology when the unmanned aerial vehicle detects an abnormal target, and improving the transmission efficiency in the communication process.

[0147] Figure 4 is a flow of the data processing method provided by the embodiment of the application Figure Three The execution subject of the embodiment may, for example, be Figure 1 The first server 2 shown in the embodiment, as shown in Figure 4 The data processing method shown in the embodiment comprises the following steps:

[0148] S301: Acquire environment data modulated according to a target waveform modulation scheme and sent by a first unmanned aerial vehicle.

[0149] The first server may, for example, be an edge server, which is a server closest to the first unmanned aerial vehicle in communication distance; and the environment data may, for example, be video sensing data or communication sensing data.

[0150] In this step, the first UAV sends the video sensing data and the communication sensing data modulated according to the target waveform modulation scheme to the edge server.

[0151] S302: Preprocessing the modulated environmental data to obtain abnormal data, the abnormal data being used to indicate an abnormality existing in the region where the first UAV is located.

[0152] Preprocessing refers to a preliminary semantic sensing analysis and understanding of the modulated environmental data.

[0153] Since the original data volume of the environmental data is large and the UAV application system is sensitive to time delay, the preliminary semantic sensing analysis and understanding of the environmental data can improve the communication sensing efficiency.

[0154] In this step, the environmental data is classified and graded according to the importance of the environmental data, and then the environmental data is subjected to a preliminary semantic sensing analysis and understanding, thereby obtaining abnormal data.

[0155] S303: Sending the abnormal data to a second UAV, the second UAV being a UAV in communication connection with the first server, and the second UAV being different from the first UAV.

[0156] The second UAV may be, for example, another UAV in communication connection with the edge server.

[0157] It can be understood that the first server is in communication connection with a plurality of UAVs. Since the bandwidth resources of each edge server are limited, if each UAV sends abnormal data to the edge server in communication connection therewith, the calculation amount of the edge server will be overloaded, and the loading speed of the edge server will be affected. Therefore, after the first server preprocesses the environmental data sent by the first UAV and obtains abnormal data, the first server can synchronously send the abnormal data to other UAVs in communication connection therewith, so that the other UAVs learn the abnormality existing in the region where the first UAV is located, and the second UAV is avoided from sending the same data as the abnormal data to the first server, thereby reducing the calculation amount of the first server itself and improving the loading speed.

[0158] Optionally, after step S303, the method further includes: generating abnormal information according to the abnormal data, and sending the abnormal information to a second server.

[0159] The second server may be, for example, a UAV platform server, the UAV platform server being in communication connection with a third UAV, and the third UAV may be, for example, another UAV not in communication connection with the first server.

[0160] It can be understood that when the first server sends the abnormal data sent by the first unmanned aerial vehicle to the second unmanned aerial vehicle in communication connection therewith, the third unmanned aerial vehicle not in communication connection with the first server cannot obtain the abnormal data of the region where the first unmanned aerial vehicle is located. Based on this, when the third unmanned aerial vehicle obtains the same environmental data of the region, the third unmanned aerial vehicle will still send the environmental data to the nearest edge server, so that the edge server pre-processes the environmental data. This will cause the computing power of the edge server to increase, thereby occupying the limited bandwidth resources of the edge server.

[0161] Therefore, after the first server determines that there is an abnormality in the region where the first unmanned aerial vehicle is located, the first server also needs to send the abnormal data to the second server, so that the second server performs deep processing on the abnormal information, and sends the abnormal data to the third unmanned aerial vehicle when confirming that the abnormal information is correct. This step makes the edge server no longer need to do repeated calculation, reduces the calculation amount of the edge server in communication connection with the third unmanned aerial vehicle, and also realizes the verification of the abnormal data, ensuring the correctness of the data.

[0162] The data processing method provided by the embodiment of the application reduces the calculation amount of the edge server and improves the service performance of the edge server by obtaining environmental data modulated according to a target waveform modulation scheme and sent by a first unmanned aerial vehicle, pre-processing the modulated environmental data to obtain abnormal data, sending the abnormal data to a second unmanned aerial vehicle, generating abnormal information according to the abnormal data, and sending the abnormal information to a second server.

[0163] Figure 5 The structure of the data processing device provided by the application is shown in Figure One The data processing device 300 provided by the embodiment of the application is applied to a first unmanned aerial vehicle. As shown in Figure 5 The data processing device 300 provided by the embodiment of the application comprises:

[0164] The acquisition module is configured to acquire perception data, wherein the perception data is acquired by a radio frequency transceiver module, an airborne radar, and an airborne camera.

[0165] The determination module is configured to determine a channel environment of a current channel of the perception data and environmental data of a region where the first unmanned aerial vehicle is located according to the perception data.

[0166] The determination module is further configured to determine a target waveform modulation scheme matched with the environment of the current channel according to the channel environment and a waveform modulation strategy, wherein the target modulation scheme is used to instruct to modulate the environmental data according to a target waveform, and the waveform modulation strategy is determined according to transmission comprehensive performance between a plurality of channel environments and a plurality of waveforms.

[0167] The processing module is configured to modulate the environmental data according to the target waveform modulation scheme.

[0168] The sending module is configured to send the modulated environmental data to a first server.

[0169] Optionally, the obtaining module is further configured to obtain waveform information of a plurality of waveforms in a preset time period, the waveform information including: waveform transmission bit error rate, sensing accuracy, number of complex number operation units during modulation or demodulation, probability of being selected under different channel environments, and adaptation to different channel environments.

[0170] The processing module is further configured to determine transmission comprehensive performance of each waveform under different channel environments according to the waveform information.

[0171] The processing module is further configured to determine a candidate waveform corresponding to each channel environment according to the transmission comprehensive performance of each waveform under different channel environments, the transmission comprehensive performance of the candidate waveform being greater than that of other waveforms under each channel environment.

[0172] Optionally, the processing module is specifically configured to: perform classification processing on the transmission comprehensive performance according to a plurality of channel environments to obtain a transmission comprehensive performance set of a plurality of waveforms under each channel environment; determine a maximum comprehensive performance under each channel environment from the transmission comprehensive performance set of the plurality of waveforms; and take a waveform corresponding to the maximum comprehensive performance as the candidate waveform for each channel environment.

[0173] Optionally, the processing module is further configured to formulate the waveform modulation strategy according to the candidate waveform corresponding to each channel environment.

[0174] Figure 6 Structure of a data processing apparatus provided in the present application Figure Two applied to a first server. As shown in Figure 6 the data processing apparatus 400 provided in the present embodiment includes:

[0175] The obtaining module is configured to obtain environmental data modulated according to a target waveform modulation scheme and sent by a first unmanned aerial vehicle.

[0176] The processing module is configured to pre-process the modulated environmental data to obtain abnormal data, the abnormal data being used to indicate an abnormality existing in a region where the first unmanned aerial vehicle is located.

[0177] The sending module is configured to send the abnormal data to a second unmanned aerial vehicle, the second unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the first server, and the second unmanned aerial vehicle being different from the first unmanned aerial vehicle.

[0178] Optionally, the processing module is further configured to generate abnormal information according to the abnormal data.

[0179] The sending module is further configured to send the abnormal information to a second server, so that the second server performs deep processing on the abnormal information, and sends the abnormal data to a third unmanned aerial vehicle when it is confirmed that the abnormal information is correct, the third unmanned aerial vehicle being an unmanned aerial vehicle in communication connection with the second server, and the third unmanned aerial vehicle not being in communication connection with the first server.

[0180] Figure 7 A structural schematic diagram of a data processing device provided by the present application is shown in FIG. 1. Figure 7 As shown in FIG. 1, the present application provides a data processing device 400, which comprises a receiver 401, a sender 402, a processor 403 and a memory 404.

[0181] The receiver 401 is configured to receive instructions and data.

[0182] The sender 402 is configured to send instructions and data.

[0183] The memory 404 is configured to store computer-executed instructions.

[0184] The processor 403 is configured to execute the computer-executed instructions stored in the memory 404, so as to realize each step performed by the data processing method in the above-mentioned embodiments. For details, please refer to the related description in the foregoing data processing method embodiments.

[0185] Optionally, the memory 404 can be independent or integrated with the processor 403.

[0186] When the memory 404 is independently arranged, the electronic device further comprises a bus for connecting the memory 404 and the processor 403.

[0187] The present application further provides a computer-readable storage medium, which stores computer-executed instructions, and when the processor executes the computer-executed instructions, the data processing method performed by the data processing device is realized.

[0188] Those of ordinary skill in the art will realize and understand that all or certain steps in the methods disclosed above, the functional modules / units in the systems and devices can be implemented as software, firmware, hardware and appropriate combinations thereof. In hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Certain physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on a computer readable medium, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Further, it is common knowledge to those of ordinary skill in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.

[0189] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the application be limited only by the scope of the claims, which will follow, and that reasonable equivalents thereof are included. The specification and examples given are intended as illustrative only and are not intended to limit the true scope and spirit of the application.

[0190] It is to be understood that the application is not limited to the precise construction here described and as shown in the attached drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is to be limited only by the claims appended hereto.

Claims

1. A data processing method, characterized in that, Applied to a first unmanned aerial vehicle, the method includes: The sensing data is acquired through a radio frequency transceiver module, airborne radar, and airborne imaging device. Based on the perceived data, determine the channel environment of the current channel of the perceived data and the environmental data of the area where the first UAV is located; Based on the channel environment and waveform modulation strategy, a target waveform modulation scheme matching the current channel environment is determined. The target waveform modulation scheme is used to indicate that the environmental data is modulated according to the target waveform. The waveform modulation strategy is determined based on the comprehensive transmission performance between multiple channel environments and multiple waveforms. The environmental data is modulated according to the target waveform modulation scheme, and the modulated environmental data is sent to a first server. The first server is used to obtain abnormal data based on the modulated environmental data and send the abnormal data to a second drone, and to generate abnormal information based on the abnormal data and send the abnormal information to the second server, so that the second server, after confirming that the abnormal information is correct, sends the abnormal data to a third drone. The abnormal data is used to indicate an anomaly in the area where the first drone is located. The second drone is a drone that is communicatively connected to the first server, and the second drone is different from the first drone. The third drone is a drone that is communicatively connected to the second server, and the third drone is not communicatively connected to the first server.

2. The method according to claim 1, characterized in that, Before acquiring the perceived data, the method further includes: The waveform information of various waveforms within a preset time period is obtained. The waveform information includes: waveform transmission bit error rate, sensing accuracy, number of complex operation units during modulation or demodulation, probability of being selected under different channel environments, and adaptability to different channel environments. Based on the waveform information, determine the overall transmission performance of each waveform under different channel environments; Based on the overall transmission performance of each waveform under different channel environments, candidate waveforms are determined for each channel environment. Under each channel environment, the overall transmission performance of the candidate waveform is greater than that of other waveforms. The waveform modulation strategy is formulated based on the candidate waveforms corresponding to each channel environment.

3. The method according to claim 2, characterized in that, The step of determining the overall transmission performance of each waveform under different channel environments based on the waveform information includes: The overall transmission performance of the waveform under different channel environments is determined using the following formula: in, Waveform from time 0 to time T Overall transmission performance under each channel environment Waveform Adaptability in each channel environment Waveform Sensing accuracy in each channel environment Waveform Waveform transmission bit error rate under each channel environment, Waveform The number of complex operation units during modulation or demodulation in each channel environment. Waveform The probability of being selected in each channel environment.

4. The method according to claim 2, characterized in that, The step of determining candidate waveforms for each channel environment based on the overall transmission performance of each waveform under different channel environments includes: Based on various channel environments, the overall transmission performance is classified and processed to obtain a set of overall transmission performance for various waveforms under each channel environment; From the set of comprehensive transmission performance of the various waveforms, determine the maximum comprehensive performance under each channel environment; For each channel environment, the waveform corresponding to the maximum overall performance is selected as a candidate waveform.

5. A data processing method, characterized in that, Applied to a first server, the method includes: Acquire environmental data transmitted by the first UAV after modulation according to the target waveform modulation scheme; The modulated environmental data is preprocessed to obtain abnormal data, which is used to indicate the anomalies in the area where the first UAV is located. The abnormal data is sent to a second drone, which is a drone that communicates with the first server and is different from the first drone. The method further includes: generating abnormal information based on the abnormal data, and sending the abnormal information to a second server so that the second server performs in-depth processing on the abnormal information, and when confirming that the abnormal information is correct, sending the abnormal data to a third drone, wherein the third drone is a drone that is connected to the second server and is not connected to the first server. The target waveform modulation scheme is a target waveform modulation scheme that matches the current channel environment, determined based on the current channel environment and waveform modulation strategy of the sensing data. The waveform modulation strategy is determined based on the comprehensive transmission efficiency between multiple channel environments and multiple waveforms. The sensing data is acquired through the radio frequency transceiver module, airborne radar, and airborne imaging device of the first UAV, and is used to acquire the channel environment and environmental data of the area where the first UAV is located.

6. A data processing apparatus, characterized in that, Applied to a first unmanned aerial vehicle, the device includes: The acquisition module is used to acquire sensing data, which is acquired through a radio frequency transceiver module, airborne radar, and airborne imaging device. The determination module is used to determine the channel environment of the current channel of the sensing data and the environmental data of the area where the first UAV is located, based on the sensing data. The determining module is further configured to determine a target waveform modulation scheme that matches the current channel environment based on the channel environment and waveform modulation strategy. The target modulation scheme is used to indicate that the environmental data is modulated according to the target waveform. The waveform modulation strategy is determined based on the comprehensive transmission performance between multiple channel environments and multiple waveforms. The processing module is used to modulate the environmental data according to the target waveform modulation scheme; A sending module is used to send modulated environmental data to a first server; the first server is used to obtain abnormal data based on the modulated environmental data and send the abnormal data to a second drone, and to generate abnormal information based on the abnormal data and send the abnormal information to the second server, so that the second server, after confirming that the abnormal information is correct, sends the abnormal data to a third drone; the abnormal data is used to indicate an anomaly existing in the area where the first drone is located; the second drone is a drone that is communicatively connected to the first server, and the second drone is different from the first drone; the third drone is a drone that is communicatively connected to the second server, and the third drone is not communicatively connected to the first server.

7. A data processing apparatus, characterized in that, Applied to a first server, the device includes: The acquisition module is used to acquire environmental data transmitted by the first UAV after modulation according to the target waveform modulation scheme; The target waveform modulation scheme is a target waveform modulation scheme that matches the current channel environment, determined based on the current channel environment and waveform modulation strategy of the sensing data. The waveform modulation strategy is determined based on the comprehensive transmission efficiency between multiple channel environments and multiple waveforms. The sensing data is acquired through the radio frequency transceiver module, airborne radar, and airborne imaging device of the first UAV, and is used to acquire the channel environment and environmental data of the area where the first UAV is located. The processing module is used to preprocess the modulated environmental data to obtain abnormal data, which is used to indicate the anomalies in the area where the first UAV is located. The sending module is used to send the abnormal data to a second drone, which is a drone that communicates with the first server and is different from the first drone. The processing module is also used to generate abnormal information based on the abnormal data; The sending module is further configured to send the abnormal information to the second server, so that the second server can perform in-depth processing on the abnormal information, and when the abnormal information is confirmed to be correct, send the abnormal data to the third drone, wherein the third drone is a drone that is connected to the second server and is not connected to the first server.

8. A data processing device, characterized in that, include: Memory; processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the data processing method as described in any one of claims 1-4 or 5.

9. A computer storage medium, characterized in that, The computer storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the data processing method as described in any one of claims 1-4 or 5.

Images