Data processing method and device for unmanned aerial vehicle image transmission

Abstract

The application discloses a data processing method and device for unmanned aerial vehicle image transmission. The method comprises the following steps: in the process of FPV unmanned aerial vehicle image transmission, obtaining signal detection data to be processed, wherein the signal detection data to be processed is data for representing detection of unmanned aerial vehicle simulation image transmission signals; performing signal screening processing on the signal detection data to be processed based on time-frequency conversion to obtain unmanned aerial vehicle image transmission signal data; and performing signal processing on the unmanned aerial vehicle image transmission signal data based on video signal recovery to obtain image transmission video data. Through the above software-defined radio method, the FPV unmanned aerial vehicle simulation image transmission is digitally analyzed, the problem that a special IC chip is difficult to support multi-frequency bands and multiple types in a digital analysis process is solved, and digital analysis of multiple types of unmanned aerial vehicle image transmission is realized.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) communication, and more specifically, to a data processing method and apparatus for UAV image transmission. Background Technology

[0002] FPV (First-Person View) drones are drones controlled in real-time from a first-person perspective. Pilots see live footage transmitted from the drone's camera through a head-mounted display or screen, providing an immersive flight experience. They are primarily used for racing, aerial photography, and aerobatic maneuvers. Analog video transmission is the most traditional wireless video transmission technology for FPV drones, sending camera footage in real-time to the pilot's glasses or screen via analog signals.

[0003] Currently, the FPV image transmission modules used in drones primarily employ proprietary protocols, standard protocols such as PAL and NTSC, or variations thereof, across frequency bands ranging from hundreds of MHz to several gigabits. Using dedicated IC chips makes it difficult to cover non-standard standards and the entire frequency band.

[0004] Therefore, existing UAV image transmission technologies suffer from the problem of difficulty in achieving digital analysis processes that support multiple frequency bands and various standards. Summary of the Invention

[0005] The main objective of this application is to provide a data processing method and apparatus for UAV image transmission, which solves the problem that dedicated IC chips in the prior art cannot support multiple frequency bands and multiple standards in the digital parsing process, and realizes digital parsing of image transmission from multiple types of UAVs.

[0006] To achieve the above objectives, the first aspect of this application proposes a data processing method for image transmission in unmanned aerial vehicles (UAVs), applied to FPV UAVs, to realize the digital analysis of simulated image transmission from FPV UAVs, including:

[0007] Acquire signal detection data to be processed, wherein the signal detection data to be processed is data used to represent the detection of simulated image transmission signals of the UAV;

[0008] The signal detection data to be processed is subjected to signal filtering processing based on time-frequency conversion to obtain UAV image transmission signal data;

[0009] The UAV image transmission signal data is processed based on video signal recovery to obtain image transmission video data.

[0010] Furthermore, the UAV image transmission signal data undergoes signal processing based on video signal recovery to obtain image transmission video data, including:

[0011] The UAV image transmission signal data is demodulated based on modulation features to obtain process composite video signal data;

[0012] The composite video signal data of the process is subjected to signal decoding processing to obtain the pixel data of the video image to be processed;

[0013] The pixel data of the video image to be processed is subjected to image signal recovery processing to obtain the video transmission data.

[0014] Furthermore, the UAV image transmission signal data undergoes demodulation processing based on modulation features to obtain composite video signal data, including:

[0015] The UAV image transmission signal data is processed based on signal features to obtain signal feature data;

[0016] The signal feature data is subjected to modulation feature extraction processing to obtain signal modulation feature data, wherein the signal modulation feature data is feature data used to represent the modulation mode of the UAV image transmission signal;

[0017] The UAV image transmission signal data is subjected to inverse demodulation processing based on the signal modulation feature data to obtain the process composite video signal data.

[0018] Further, the composite video signal data of the process is subjected to signal decoding processing to obtain the pixel data of the video image to be processed, including:

[0019] The composite video signal data of the process is subjected to synchronization signal extraction processing to obtain synchronization signal data;

[0020] The synchronization signal data is processed to determine the signal standard, thereby obtaining signal standard characteristic data;

[0021] The pixel data of the video image to be processed is determined based on the synchronization signal data and the signal standard feature data.

[0022] Further, image signal recovery processing is performed on the pixel data of the video image to be processed to obtain the transmitted video data, including:

[0023] The pixel data of the video image to be processed is subjected to color synchronization signal extraction processing based on channel estimation to obtain color synchronization signal data;

[0024] The color synchronization signal data is subjected to chroma demodulation processing based on phase change characteristics to obtain chroma demodulated data;

[0025] The pixel data of the video image to be processed is subjected to color difference signal extraction processing to obtain process color difference signal data;

[0026] The process color difference signal data is calibrated to obtain calibrated color difference signal data;

[0027] The chroma demodulation data and the standard color difference signal data are subjected to image restoration processing to obtain the image transmission video data.

[0028] Furthermore, the signal detection data to be processed is subjected to signal filtering processing based on time-frequency conversion to obtain UAV image transmission signal data, including:

[0029] The frequency domain feature extraction process based on time-frequency conversion is performed on the detection data of the signal to be processed to obtain the frequency domain feature data to be processed;

[0030] The frequency domain feature data to be processed is subjected to signal filtering processing based on a preset frequency domain feature threshold to obtain target frequency domain feature data, wherein the target frequency domain feature data is used to represent the frequency domain feature data to be processed that meets the preset frequency domain feature threshold;

[0031] The signal corresponding to the target frequency domain feature data is resampled to obtain the UAV image transmission signal data.

[0032] According to a second aspect of this application, a data processing device for image transmission in unmanned aerial vehicles (UAVs) is proposed, applied to FPV UAVs, to realize the digital analysis of analog image transmission from FPV UAVs, including:

[0033] A signal detection module is used to acquire signal detection data to be processed, wherein the signal detection data to be processed is data used to represent the detection of simulated image transmission signals of the UAV;

[0034] The signal filtering module is used to perform time-frequency conversion-based signal filtering processing on the signal detection data to be processed, so as to obtain UAV image transmission signal data.

[0035] The video signal recovery module is used to perform signal processing based on video signal recovery on the image transmission signal data of the UAV to obtain image transmission video data.

[0036] Furthermore, the video signal recovery module includes:

[0037] The signal demodulation module is used to perform demodulation processing on the UAV image transmission signal data based on modulation features to obtain process composite video signal data;

[0038] The signal decoding module is used to perform signal decoding processing on the composite video signal data of the process to obtain the pixel data of the video image to be processed;

[0039] The image signal recovery module is used to perform image signal recovery processing on the pixel data of the video image to be processed, so as to obtain the video transmission data.

[0040] According to a third aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing the computer to perform the above-described data processing method for UAV image transmission.

[0041] According to a fourth aspect of this application, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the above-described data processing method for UAV image transmission.

[0042] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0043] In this application, during the FPV drone image transmission process, signal detection data to be processed is acquired, wherein the signal detection data to be processed is data representing the detected simulated image transmission signal of the drone; the signal detection data to be processed is subjected to signal filtering processing based on time-frequency conversion to obtain drone image transmission signal data; the drone image transmission signal data is subjected to signal processing based on video signal recovery to obtain image transmission video data. By using the above-described software-defined radio method to digitally analyze the simulated image transmission of the FPV drone, the problem of existing technologies where dedicated IC chips cannot support multiple frequency bands and multiple standards in the digital analysis process is solved, thus realizing the digital analysis of image transmission from multiple types of drones. Attached Figure Description

[0044] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings:

[0045] Figure 1 A flowchart of a data processing method for UAV image transmission provided in this application;

[0046] Figure 2 A flowchart of a data processing method for UAV image transmission provided in this application;

[0047] Figure 3 A flowchart of a data processing method for UAV image transmission provided in this application;

[0048] Figure 4 A schematic diagram of a data processing device for UAV image transmission provided in this application;

[0049] Figure 5 A schematic diagram of a data processing device for UAV image transmission provided in this application;

[0050] Figure 6 A schematic diagram of an electronic device provided in this application. Detailed Implementation

[0051] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0052] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0053] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0054] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in certain circumstances to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0055] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linked," and "socketing" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0056] In existing technologies, the FPV image transmission modules used in UAVs currently primarily employ proprietary protocols, standard protocols such as PAL and NTSC, or variations thereof, with frequency bands ranging from hundreds of MHz to several gigabits. Using dedicated IC chips makes it difficult to cover non-standard standards and the entire frequency band. To address the problem that dedicated IC chips in existing technologies cannot support multi-band and multi-standard digital analysis processes, this application proposes a data processing method for UAV image transmission. This method uses SDR (Single-Dial Reduction) to process the signal analysis of UAV image transmission signals, enabling digital analysis of FPV signals across multiple frequency bands and multiple standard and non-standard standards.

[0057] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed, applied to FPV UAV simulated image transmission, to achieve digital analysis of FPV UAV simulated image transmission. By employing an AD / DA chip and a chip with a mixer, such as a chip with a mixer covering 70MHz-8GHz, the entire frequency band spectrum is detected. The detection of the entire frequency band spectrum includes setting the frequency of the acquired time-domain signal to be greater than 27MHz and the bandwidth to be greater than 12MHz, to achieve rapid scanning of the entire frequency band spectrum.

[0058] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed, applied to FPV UAVs, to achieve digital analysis of simulated image transmission from FPV UAVs. Figure 1 A flowchart of a data processing method for UAV image transmission provided in this application is shown below. Figure 1 As shown, the method includes the following steps:

[0059] S101: Acquire the detection data of the signal to be processed;

[0060] The signal detection data to be processed is the data used to represent the detection of the simulated image transmission signal of the UAV; the signal detection data to be processed is the signal detection data obtained by scanning the full frequency band spectrum as described above. The signal detection data to be processed includes the data of the simulated image transmission signal of the UAV. By performing signal filtering processing on the signal detection data to be processed, the UAV image transmission signal data is obtained.

[0061] S102: Perform time-frequency conversion-based signal filtering processing on the signal detection data to be processed to obtain UAV image transmission signal data;

[0062] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed. Figure 2 A flowchart of a data processing method for UAV image transmission provided in this application is shown below. Figure 2 As shown, the method includes the following steps:

[0063] S201: Perform frequency domain feature extraction processing based on time-frequency conversion on the detection data of the signal to be processed to obtain the frequency domain feature data to be processed;

[0064] S202: Perform signal filtering processing on the frequency domain feature data to be processed based on a preset frequency domain feature threshold to obtain the target frequency domain feature data;

[0065] The target frequency domain feature data is the frequency domain feature data to be processed that meets the preset frequency domain feature threshold.

[0066] S203: Resample the signal corresponding to the target frequency domain feature data to obtain the UAV image transmission signal data.

[0067] In an optional embodiment of this application, the frequency domain signal after time-frequency conversion is determined based on bandwidth. For example, it is determined that the frequency domain signal with a bandwidth of about 6M is an FPV drone signal. The signal determined to be an FPV drone is resampled, and the sampling rate of 27M is changed to 12M. The signal determined to be an FPV drone is resampled according to the changed sampling rate to obtain the drone image transmission signal data.

[0068] S103: Perform signal processing based on video signal recovery on the UAV image transmission signal data to obtain image transmission video data.

[0069] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed. Figure 3 A flowchart of a data processing method for UAV image transmission provided in this application is shown below. Figure 3 As shown, the method includes the following steps:

[0070] S301: Demodulate the UAV image transmission signal data based on modulation features to obtain process composite video signal data;

[0071] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed, including:

[0072] The UAV image transmission signal data is processed based on signal feature recognition to obtain signal feature data; the signal feature data is processed by modulation feature extraction to obtain signal modulation feature data, wherein the signal modulation feature data is feature data used to represent the modulation mode of the UAV image transmission signal; the UAV image transmission signal data is processed by inverse demodulation based on the signal modulation feature data to obtain process composite video signal data.

[0073] The UAV image transmission signal data is processed based on a first signal feature to obtain first signal feature data; the UAV image transmission signal data is processed based on a second signal feature to obtain second signal feature data; the UAV image transmission signal data is processed based on a third signal feature to obtain third signal feature data; the first signal feature data, the second signal feature data, and the third signal feature data are respectively the amplitude feature data, frequency feature data, and phase feature data of the UAV image transmission signal;

[0074] The signal modulation characteristics of the aforementioned first, second, and third signal characteristic data are determined to identify the signal modulation mode of the UAV image transmission signal. The UAV image transmission signal is then inversely demodulated based on the determined signal modulation mode. The frequency, amplitude, and phase characteristic data of the UAV image transmission signal are analyzed to determine the modulation mode corresponding to changes in these data. For example, FM modulation involves a constant signal amplitude but a changing frequency; AM modulation involves a changing signal amplitude but a fixed carrier frequency; and PM modulation involves a phase jump. The method for determining the signal modulation mode based on the aforementioned frequency, amplitude, and phase characteristic data can be as follows: Analyzing the frequency, amplitude, and phase characteristic data using machine learning algorithms to obtain signal modulation characteristic data; and then analyzing the UAV image transmission signal using peak spectral density calculation to obtain the signal modulation characteristic data.

[0075] S302: Perform signal decoding processing on the composite video signal data to obtain the pixel data of the video image to be processed;

[0076] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed to perform video signal decoding processing on the decoded UAV image transmission signal. The method includes:

[0077] Synchronization signal extraction processing is performed on the composite video signal data to obtain synchronization signal data; signal standard determination processing is performed on the synchronization signal data to obtain signal standard feature data; and the pixel data of the video image to be processed is determined based on the synchronization signal data and the signal standard feature data.

[0078] In an optional embodiment of this application, after performing the aforementioned SDR decoding processing on the UAV image transmission signal data, a Composite Video Broadcast Signal (CVBS signal) is obtained. This CVBS signal is then decoded. Synchronization signal extraction processing is performed on the CVBS signal based on SDR. For example, SDR determines a signal amplitude higher than a normalized threshold of 0.5 (high) and lower than 0.5 (low) to obtain the number of frame synchronizations and line synchronizations. Based on the data obtained from the synchronization signal extraction, the signal standard data is determined. The standard is determined to be PAL, NTSC, or other non-standard standards based on the frame synchronization interval and number. The CVBS signal is then decoded based on the synchronization signal data and the signal standard characteristic data to obtain the video image pixel data to be processed.

[0079] S303: Perform image signal recovery processing on the pixel data of the video image to be processed to obtain the video transmission data.

[0080] In some optional embodiments of this application, a data processing method for UAV image transmission is proposed to achieve image signal recovery. The method includes:

[0081] The process involves: extracting color synchronization signals from the pixel data of the video image to be processed based on channel estimation to obtain color synchronization signal data; performing chroma demodulation processing based on phase change characteristics on the color synchronization signal data to obtain chroma demodulated data; extracting color difference signals from the pixel data of the video image to be processed to obtain process color difference signal data; calibrating the process color difference signal data to obtain calibrated color difference signal data; and performing image restoration processing on the chroma demodulated data and the standard color difference signal data to obtain the video transmission data.

[0082] Chromaticity demodulation processing based on phase change characteristics is performed on color synchronization signal data to obtain chroma demodulated data. This includes: extracting chroma phase change characteristics from the color synchronization signal data; determining demodulation parameters based on these characteristics; analyzing the color synchronization phase change line by line and dynamically selecting demodulation parameters to achieve chroma demodulation of the signal. Channel estimation is then performed, using time-frequency domain channel estimation to remove noise and recover the time domain to obtain the color synchronization signal; the phase change of each line is analyzed to obtain chroma demodulation parameters, and chroma demodulation is achieved based on these parameters.

[0083] In another optional embodiment of this application, color difference signals are extracted from the pixel data of the video image to be processed to obtain color difference signals. Based on the amplitude and color of the front and rear shoulders of the color difference signals, phase calibration is performed on the color difference to obtain calibrated color difference signal data. After completing the above color demodulation and color difference calibration processing, the RGB image is recovered based on YUV / YIQ and other information to obtain the image transmission video data, thus realizing the parsing of the UAV image transmission signal.

[0084] In some optional embodiments of this application, a data processing device for UAV image transmission is proposed, applied to an FPV UAV, to realize the digital analysis of analog image transmission from the FPV UAV. Figure 4 A schematic diagram of a data processing device for UAV image transmission provided in this application is shown below. Figure 4 As shown, the device includes:

[0085] The signal detection module 41 is used to acquire signal detection data to be processed, wherein the signal detection data to be processed is data used to represent the detection of the simulated image transmission signal of the UAV;

[0086] Signal filtering module 42 is used to perform time-frequency conversion-based signal filtering processing on the signal detection data to be processed to obtain UAV image transmission signal data;

[0087] The video signal recovery module 43 is used to perform signal processing based on video signal recovery on the image transmission signal data of the UAV to obtain image transmission video data.

[0088] In some optional embodiments of this application, a data processing apparatus for UAV image transmission is proposed. Figure 5 A schematic diagram of another data processing device for UAV image transmission provided in this application, such as Figure 5 As shown, the device includes:

[0089] The signal demodulation module 51 is used to perform demodulation processing on the UAV image transmission signal data based on modulation features to obtain process composite video signal data.

[0090] Signal decoding module 52 is used to perform signal decoding processing on the composite video signal data of the process to obtain the pixel data of the video image to be processed;

[0091] The image signal recovery module 53 is used to perform image signal recovery processing on the pixel data of the video image to be processed, so as to obtain the video transmission data.

[0092] The specific methods of execution of each unit in the above embodiments have been described in detail in the embodiments of the method, and will not be elaborated here.

[0093] This application also provides an electronic device, such as... Figure 6 As shown, the electronic device includes one or more processors 61 and a memory 62. Figure 6 Take a processor 61 as an example.

[0094] The controller may also include an input device 63 and an output device 64.

[0095] The processor 61, memory 62, input device 63, and output device 64 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0096] Processor 61 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips. The general-purpose processor can be a microprocessor or any conventional processor.

[0097] The memory 62, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the control method in this embodiment. The processor 61 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 62, that is, it implements the data processing for UAV image transmission in the above method embodiment.

[0098] The memory 62 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the use of the processing device operated by the server. Furthermore, the memory 62 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 62 may optionally include memory remotely located relative to the processor 61, and these remote memories may be connected to a network connection device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0099] Input device 63 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the server's processing device. Output device 64 may include display devices such as a display screen.

[0100] One or more modules are stored in memory 62, and when executed by one or more processors 61, they perform actions such as... Figure 1 The method shown.

[0101] Those skilled in the art will understand that all or part of the processes in the above method embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes as described in the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory (FM), hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0102] In summary, during the FPV drone image transmission process, signal detection data to be processed is acquired, wherein the signal detection data to be processed is data representing the detected simulated image transmission signal of the drone; the signal detection data to be processed is subjected to signal filtering processing based on time-frequency conversion to obtain drone image transmission signal data; the drone image transmission signal data is subjected to signal processing based on video signal recovery to obtain image transmission video data. By using the above-described software-defined radio method to digitally analyze the simulated image transmission of FPV drones, the problem of existing technologies where dedicated IC chips cannot support multiple frequency bands and multiple standards in the digital analysis process is solved, thus realizing the digital analysis of image transmission from multiple types of drones.

[0103] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0104] Obviously, those skilled in the art should understand that the various units or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0105] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A data processing method for unmanned aerial vehicle image transmission, characterized in that, Be applied to FPV unmanned plane, to realize FPV unmanned plane simulation figure transmission digital analysis, including: Obtain the signal detection data to be processed, wherein the signal detection data to be processed is data for representing detecting unmanned plane simulation figure transmission signal; Perform signal screening processing based on time-frequency conversion on the signal detection data to be processed to obtain unmanned plane figure transmission signal data; Perform signal processing based on video signal recovery on the unmanned plane figure transmission signal data to obtain figure transmission video data, including: Perform demodulation processing based on modulation characteristics on the unmanned plane figure transmission signal data to obtain process composite video signal data, including: Perform recognition processing based on signal characteristics on the unmanned plane figure transmission signal data to obtain signal characteristic data, including: performing recognition processing based on signal characteristics on the unmanned plane figure transmission signal data to obtain first signal characteristic data, second signal characteristic data and third signal characteristic data, the first signal characteristic data, the second signal characteristic data and the third signal characteristic data are amplitude characteristic data, frequency characteristic data and phase characteristic data of the unmanned plane figure transmission signal respectively; Perform modulation characteristic extraction processing on the signal characteristic data to obtain signal modulation characteristic data, wherein the signal modulation characteristic data is characteristic data for representing the modulation mode of the unmanned plane figure transmission signal, and the signal modulation characteristic data is obtained by performing modulation characteristic extraction processing on the signal characteristic data, including: determining the signal modulation mode of the unmanned plane figure transmission signal by performing signal modulation characteristic determination on the first signal characteristic data, the second signal characteristic data and the third signal characteristic data;The method for determining the signal modulation mode according to the frequency characteristic data, the amplitude characteristic data and the phase characteristic data includes: analyzing the frequency characteristic data, the amplitude characteristic data and the phase characteristic data by a machine learning algorithm to obtain the signal modulation characteristic data;The signal modulation characteristic data is obtained by analyzing the unmanned plane figure transmission signal by peak spectrum degree calculation; Perform inverse demodulation processing based on the signal modulation characteristic data on the unmanned plane figure transmission signal data to obtain the process composite video signal data; Perform signal decoding processing on the process composite video signal data to obtain the video image pixel data to be processed; Perform synchronization signal extraction processing on the process composite video signal data to obtain synchronization signal data;Perform signal system judgment processing on the synchronization signal data to obtain signal system characteristic data;Determine the video image pixel data to be processed according to the synchronization signal data and the signal system characteristic data; Perform image signal recovery processing on the video image pixel data to be processed to obtain the figure transmission video data.

2. The data processing method according to claim 1, characterized in that, The signal decoding processing on the process composite video signal data to obtain the video image pixel data to be processed includes: Perform synchronization signal extraction processing on the process composite video signal data to obtain synchronization signal data; Perform signal system judgment processing on the synchronization signal data to obtain signal system characteristic data; Determine the video image pixel data to be processed according to the synchronization signal data and the signal system characteristic data.

3. The data processing method of claim 1, wherein, The image signal recovery processing is performed on the pixel data of the to-be-processed video image to obtain the video data transmitted by the image, comprising: The color synchronization signal extraction processing based on channel estimation is performed on the pixel data of the to-be-processed video image to obtain color synchronization signal data; The chroma demodulation processing based on phase change characteristics is performed on the color synchronization signal data to obtain chroma demodulation data; The color difference signal extraction processing is performed on the pixel data of the to-be-processed video image to obtain process color difference signal data; The calibration processing is performed on the process color difference signal data to obtain calibrated color difference signal data; The image recovery processing is performed on the chroma demodulation data and the calibrated color difference signal data to obtain the video data transmitted by the image.

4. The data processing method of claim 1, wherein, The signal screening processing based on time-frequency conversion is performed on the to-be-processed signal detection data to obtain the unmanned aerial vehicle image transmission signal data, comprising: The frequency domain feature extraction processing based on time-frequency conversion is performed on the to-be-processed signal detection data to obtain to-be-processed frequency domain feature data; The signal screening processing based on the preset frequency domain feature threshold is performed on the to-be-processed frequency domain feature data to obtain target frequency domain feature data, wherein the target frequency domain feature data is to-be-processed frequency domain feature data that meets the preset frequency domain feature threshold; The signal corresponding to the target frequency domain feature data is resampled to obtain the unmanned aerial vehicle image transmission signal data.

5. A data processing apparatus for unmanned aerial vehicle image transmission, characterized in that, The application is applied to the FPV unmanned aerial vehicle to realize the digital analysis of the FPV unmanned aerial vehicle simulation image transmission, comprising: A signal detection module is configured to obtain to-be-processed signal detection data, wherein the to-be-processed signal detection data is data used to represent the detection of the unmanned aerial vehicle simulation image transmission signal; A signal screening module is configured to perform signal screening processing based on time-frequency conversion on the to-be-processed signal detection data to obtain unmanned aerial vehicle image transmission signal data; A video signal recovery module is configured to perform signal processing based on video signal recovery on the unmanned aerial vehicle image transmission signal data to obtain image transmission video data, comprising: A signal demodulation module is configured to perform demodulation processing based on modulation characteristics on the unmanned aerial vehicle image transmission signal data to obtain process composite video signal data, comprising: The signal feature data is obtained by performing signal feature recognition processing on the unmanned aerial vehicle image transmission signal data, comprising: the first signal feature data, the second signal feature data, and the third signal feature data are obtained by performing signal feature recognition processing on the unmanned aerial vehicle image transmission signal data, the first signal feature data, the second signal feature data, and the third signal feature data are amplitude feature data, frequency feature data, and phase feature data of the unmanned aerial vehicle image transmission signal, respectively; The signal feature data is subjected to modulation feature extraction processing to obtain signal modulation feature data, wherein the signal modulation feature data is feature data used to represent the modulation mode of the UAV image transmission signal, and the signal modulation feature data is obtained by performing signal modulation feature determination on the first signal feature data, the second signal feature data and the third signal feature data to determine the signal modulation mode of the UAV image transmission signal; the method for determining the signal modulation mode according to the frequency feature data, the amplitude feature data and the phase feature data comprises: analyzing the frequency feature data, the amplitude feature data and the phase feature data by using a machine learning algorithm to obtain the signal modulation feature data; and the UAV image transmission signal is analyzed by using a peak spectrum degree calculation to obtain the signal modulation feature data; The UAV image transmission signal data is subjected to inverse demodulation processing based on the signal modulation feature data to obtain the process composite video signal data; A signal decoding module is configured to perform signal decoding processing on the process composite video signal data to obtain the to-be-processed video image pixel data; The process composite video signal data is subjected to synchronous signal extraction processing to obtain synchronous signal data, and the synchronous signal data is subjected to signal system judgment processing to obtain signal system feature data; and the to-be-processed video image pixel data is determined according to the synchronous signal data and the signal system feature data; An image signal recovery module is configured to perform image signal recovery processing on the to-be-processed video image pixel data to obtain the image transmission video data.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the data processing method for UAV image transmission according to any one of claims 1-4.

7. An electronic device, comprising: Comprise: At least one processor; And a memory connected with the at least one processor in communication; wherein the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to make the at least one processor execute the data processing method for UAV image transmission according to any one of claims 1-4.

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