Unmanned aerial vehicle FPV remote sensing audio-visual system and method

Abstract

The invention relates to the technical field of unmanned aerial vehicle FPV, in particular to an unmanned aerial vehicle FPV remote sensing audio-visual system and method.The unmanned aerial vehicle captures high-definition image data through a digital image transmission module and transmits the high-definition image data to FPV equipment through an antenna system; the FPV equipment receives the image data through an anti-interference mechanism, and decompresses the image data through an efficient codec; quickly processing the decompressed image data by using a hardware acceleration unit, and converting the decompressed image data into a format which can be displayed by FPV equipment; and the continuity and fluency of the image data are ensured through a caching and buffering mechanism. The digital image transmission module ensures the definition and detail performance of an image, the anti-interference mechanism can effectively resist external electromagnetic interference and ensure stable transmission of image data in a complex environment, the efficient codec and the hardware acceleration unit perform rapid processing on the image data, the caching and buffering mechanism ensures the continuity and smoothness of the image data, and the stability and reliability of the image data are improved. And the user experience is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) FPV technology, and in particular to an unmanned aerial vehicle (UAV) FPV remote sensing audio-visual system and method. Background Art

[0002] Drone FPV technology refers to the transmission of real-time video to a ground control station or the pilot's head-mounted display through a high-definition camera installed on the drone, allowing the pilot to control the drone in an immersive way to achieve remote reconnaissance, surveillance, filming or perform other tasks.

[0003] The existing publication number CN116736984A discloses a virtual reality experience system based on drones, including: a drone module, a G-force seat module and FPV glasses that are connected to the drone module; the drone module is used to move and capture image information corresponding to the real scene, and transmit the image information to the FPV glasses; the FPV glasses are used to display the image information; the G-force seat module is used to perform corresponding movements according to the flight data of the drone module. Through the combination of drones, G-force seats and FPV glasses, the experiencer controls the drone on the G-force seat, visually feels the landscape from the drone's perspective through the FPV glasses, and kinesthetically feels the movement brought by the drone's flight posture through the G-force seat, so that the experiencer can obtain an immersive virtual reality experience. It is widely used in many fields such as flight training, popular science education, competitive entertainment, etc., with simple operation and easy promotion.

[0004] However, the signal transmission between the drone and the FPV glasses needs to be stable and high-speed to avoid image delay or interruption. However, in actual applications, due to various factors such as frequency and power, environmental factors, communication protocols and technologies, the stability of signal transmission may be difficult to guarantee, affecting the user experience. Summary of the invention

[0005] The purpose of the present invention is to provide a UAV FPV remote sensing audio-visual system and method, which solves the problem that the stability of signal transmission between the existing UAV and FPV glasses is difficult to ensure, affecting the user experience.

[0006] To achieve the above object, the present invention provides a UAV FPV remote sensing audio-visual method, comprising the following steps:

[0007] The drone captures high-definition image data through the digital image transmission module and transmits it to the FPV device through the antenna system;

[0008] The FPV device receives image data through an anti-interference mechanism and decompresses it through an efficient codec;

[0009] The hardware acceleration unit is used to quickly process the decompressed image data and convert it into a format that can be displayed by the FPV device;

[0010] The continuity and smoothness of image data are ensured through caching and buffering mechanisms.

[0011] The drone captures high-definition image data through a digital image transmission module and transmits it to the FPV device through an antenna system. The steps also include:

[0012] After the drone camera captures high-definition image data, it transmits the image data to the digital image transmission module for processing;

[0013] The digital image transmission module compresses the image data. The compression algorithm retains the key information of the image while removing redundant data. The compressed image data is encoded and converted into a format suitable for wireless transmission.

[0014] The encoded image data is modulated onto a high-frequency carrier to form a radio signal;

[0015] The antenna system on the drone transmits the modulated radio signal to the FPV device.

[0016] The FPV device receives image data through an anti-interference mechanism and performs decompression processing through an efficient codec, and the steps further include:

[0017] The antenna system on the FPV device receives radio signals;

[0018] During reception, FPV equipment uses frequency diversity, space diversity, time diversity and other technologies to suppress interference and noise;

[0019] The received signal is pre-processed, including filtering, amplification and synchronization;

[0020] During preprocessing, signal loss during transmission is restored.

[0021] The FPV device receives image data through an anti-interference mechanism and performs decompression processing through an efficient codec, and the steps further include:

[0022] The pre-processed signal is first demodulated to restore the information on the high-frequency carrier to the baseband signal;

[0023] The demodulated signal is then decoded to restore the encoded data to the original image data;

[0024] The decoded image data is decompressed, and the decompression process performs the inverse operation according to the algorithm used during compression to restore the original image pixel data.

[0025] The decompressed image data is quickly processed by a hardware acceleration unit and converted into a format displayable by the FPV device. The steps also include:

[0026] Verify the decompressed data to ensure its integrity and accuracy;

[0027] The decompressed image data is input into the hardware acceleration unit, and the image processing algorithm is applied on the hardware acceleration unit to quickly process the image, and the algorithm includes color correction, contrast enhancement, sharpening, denoising and format conversion;

[0028] The processed image data is output from the hardware acceleration unit and converted into a format that can be directly displayed by the FPV device.

[0029] Wherein, the continuity and fluency of the image data are ensured by caching and buffering mechanisms, and the steps further include:

[0030] Load recently accessed or soon-to-be-accessed image data into the memory cache;

[0031] Use LruCache cache strategy;

[0032] When new image data arrives, the data in memory is updated according to the cache strategy to ensure that the data in the cache is always up to date.

[0033] Wherein, the continuity and fluency of the image data are ensured by caching and buffering mechanisms, and the steps further include:

[0034] During the image data transmission process, a receiving buffer is set to temporarily store the received image data;

[0035] Before sending the image data to the FPV device, set up a send buffer to temporarily store the data to be sent;

[0036] Dynamically adjust the size of the receive buffer and send buffer based on network bandwidth and device processing capabilities;

[0037] Set different priorities for different types of image data.

[0038] An unmanned aerial vehicle FPV remote sensing audio-visual system, comprising an unmanned aerial vehicle, an FPV device, an antenna system, a digital image transmission module, a codec, a hardware acceleration unit, a cache and buffer unit, and an anti-interference module;

[0039] The antenna system is respectively arranged on the wireless device and the FPV device to enhance the signal receiving capability and coverage;

[0040] The digital image transmission module is arranged on the drone and is used to capture and transmit high-definition image data in real time;

[0041] The codec is arranged between the drone and the FPV device, and is used to efficiently compress and decompress the transmitted image data;

[0042] The hardware acceleration unit is integrated into the FPV device and uses GPU acceleration or a dedicated hardware processor to quickly process image data;

[0043] The cache and buffer unit is arranged in the FPV device and is used for caching and buffering image data;

[0044] The anti-interference module is arranged on the antenna system, selects a low-interference frequency band for transmission, and adopts channel coding technology to enhance the anti-interference capability of the signal.

[0045] The present invention discloses an unmanned aerial vehicle (UAV) remote sensing audio-visual system and method. The unmanned aerial vehicle captures high-definition image data through a digital image transmission module and transmits the data to an FPV device through an antenna system. The FPV device receives the image data through an anti-interference mechanism and performs decompression processing through an efficient codec. The decompressed image data is quickly processed by a hardware acceleration unit and converted into a format displayable by the FPV device. The continuity and fluency of the image data are ensured through a cache and buffer mechanism. The digital image transmission module supports the capture and transmission of high-definition image data, ensuring the clarity and detail of the image. It adopts advanced digital image transmission technology, such as DJI FPV high-definition low-latency digital image transmission technology, which can achieve an image transmission delay of less than 28ms (in 720p / 120fps mode), greatly improving the flight experience and control accuracy. The built-in anti-interference mechanism of the FPV device can effectively resist external electromagnetic interference and ensure the stable transmission of image data in complex environments. For example, the DJI FPV image transmission sky end can support up to 8 independent communication frequency bands and support multiple aircraft flying at the same time without interfering with each other, which provides convenience for team work. The image data is quickly processed through efficient codecs and hardware acceleration units, which not only shortens the processing time, but also reduces the burden on the CPU and improves the performance of the overall system. The processed image data can be quickly converted into a format that can be displayed by the FPV device, and the continuity and smoothness of the image data are ensured through the cache and buffering mechanism, providing users with a seamless visual experience and effectively improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0047] Figure 1 It is a flowchart of the steps of the UAV FPV remote sensing audio-visual method according to the first embodiment of the present invention.

[0048] Figure 2 It is a flowchart of the steps of the drone of the first embodiment of the present invention capturing high-definition image data through the digital image transmission module and transmitting it to the FPV device through the antenna system.

[0049] Figure 3 It is a flowchart of the steps of the FPV device of the first embodiment of the present invention receiving image data through an anti-interference mechanism and performing decompression processing through a high-efficiency codec.

[0050] Figure 4 It is a flowchart of the steps of using a hardware acceleration unit to quickly process decompressed image data and convert it into a format that can be displayed by an FPV device according to the first embodiment of the present invention.

[0051] Figure 5 It is a flowchart of the steps of ensuring the continuity and fluency of image data through a cache mechanism in the first embodiment of the present invention.

[0052] Figure 6 It is a flowchart of the steps of ensuring the continuity and fluency of image data through a buffer mechanism according to the first embodiment of the present invention.

[0053] Figure 7 It is a structural block diagram of the UAV FPV remote sensing audio-visual system according to the second embodiment of the present invention.

[0054] In the figure: 201-UAV, 202-FPV equipment, 203-antenna system, 204-digital image transmission module, 205-codec, 206-hardware acceleration unit, 207-cache and buffer unit, 208-anti-interference module. DETAILED DESCRIPTION

[0055] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0056] The first embodiment of the present application is:

[0057] See also Figures 1 to 6 ,in, Figure 1 It is a flowchart of the steps of the UAV FPV remote sensing audio-visual method according to the first embodiment of the present invention. Figure 2 It is a flowchart of the steps of the drone 201 of the first embodiment of the present invention capturing high-definition image data through the digital image transmission module 204 and transmitting it to the FPV device 202 through the antenna system 203. Figure 3 It is a flowchart of the steps of the FPV device 202 of the first embodiment of the present invention receiving image data through the anti-interference mechanism and performing decompression processing through the efficient codec. Figure 4It is a flowchart of the steps of using the hardware acceleration unit 206 to quickly process the decompressed image data and convert it into a format that can be displayed by the FPV device 202 according to the first embodiment of the present invention. Figure 5 It is a flowchart of the steps of ensuring the continuity and fluency of image data through a cache mechanism in the first embodiment of the present invention. Figure 6 The present invention provides a UAV FPV remote sensing audio-visual method, comprising the following steps:

[0058] S101: The drone 201 captures high-definition image data through the digital image transmission module 204 and transmits it to the FPV device 202 through the antenna system 203;

[0059] S1011: After the camera of the drone 201 captures high-definition image data, the image data is transmitted to the digital image transmission module 204 for processing;

[0060] S1012: The digital image transmission module 204 compresses the image data. The compression algorithm retains the key information of the image and removes redundant data. The compressed image data is coded and converted into a format suitable for wireless transmission.

[0061] S1013: The encoded image data is modulated onto a high frequency carrier to form a radio signal;

[0062] S1014: The antenna system 203 on the drone 201 transmits the modulated radio signal to the FPV device 202.

[0063] Specifically, the high-definition camera on the drone 201 captures real-time image data with high resolution and high definition to meet the display requirements of the FPV device 202. The digital image transmission module 204 first efficiently compresses the captured image data to reduce the amount of data for fast transmission. The compression algorithm ensures that the image quality loss is within an acceptable range while maintaining a high fidelity. The compressed image data is encoded to increase the anti-interference ability and transmission efficiency of the data. At the same time, the data is interleaved to improve the fault tolerance during the transmission process. The encoded image data is modulated onto a signal suitable for wireless transmission, usually modulated by a high-frequency carrier to convert the image data into a high-frequency electromagnetic wave. The antenna system 203 on the drone 201 transmits the modulated high-frequency electromagnetic wave signal and transmits it through an aerial wireless channel. The transmitted signal needs to take into account the polarization, gain and directivity of the antenna to ensure that the signal can be stably and efficiently transmitted to the FPV device 202.

[0064] S102: The FPV device 202 receives the image data through an anti-interference mechanism and performs decompression processing through an efficient codec;

[0065] S1021: The antenna system 203 on the FPV device 202 receives a radio signal;

[0066] S1022: During the receiving process, the FPV device 202 uses frequency diversity, space diversity, time diversity and other technologies to suppress interference and noise;

[0067] S1023: Preprocessing the received signal, including filtering, amplification and synchronization;

[0068] S1024: during the preprocessing process, recover the signal lost during the transmission process;

[0069] S1025: The pre-processed signal is first demodulated to restore the information on the high frequency carrier to a baseband signal;

[0070] S1026: The demodulated signal is decoded to restore the encoded data to the original image data;

[0071] S1027: The decoded image data is decompressed. The decompression process is performed inversely according to the algorithm used during compression to restore the original image pixel data.

[0072] Specifically, the antenna system 203 on the PV device first receives the radio signal from the drone 201. During the reception process, the FPV device 202 will use a variety of anti-interference mechanisms to ensure the stability and reliability of the signal. These mechanisms include frequency diversity, space diversity, time diversity and other technologies, as well as the use of advanced signal processing technology to suppress interference and noise. Among them, frequency diversity is a technology that uses channels of different frequencies to transmit the same information to improve the anti-interference ability and reliability of the system. By sending the same data on different frequencies, when a certain frequency channel is interfered with, the data of other frequency channels can still be received normally, thereby ensuring the integrity of the data. Space diversity is the use of multiple antennas separated by a certain distance in space to receive signals to reduce the influence of signal fading and interference. Since the signal will be affected by factors such as multipath effects and building shielding during the propagation process, the signal will fade. By arranging multiple antennas in a dispersed manner in space, signals from different paths can be received and synthesized into a more stable signal through signal processing technology. Time diversity is a method of using time intervals to send multiple copies of the same data to improve the reliability of data transmission. By sending the same data copy at different time points, when the data at a certain time point cannot be received due to interference or fading, the data copies at other time points can still be received and used to restore the original data. The received signal will undergo a series of preprocessing steps, such as filtering, amplification, synchronization, etc., to improve the quality and stability of the signal. During the preprocessing process, the FPV device 202 will try to restore the signal loss caused by factors such as attenuation and distortion during the transmission process. The preprocessed signal is first demodulated to restore the information on the high-frequency carrier to the baseband signal. The demodulated signal is then decoded to restore the encoded data to the original image data. In this process, efficient codecs play a key role. Codecs use advanced algorithms and technologies, such as Huffman coding, run-length coding, JPEG / H.264 / H.265 and other video compression standards to achieve efficient compression and decompression of image data. The decoded image data is usually in a compressed format, and in order to be displayed, it needs to be decompressed. The decompression process will perform the inverse operation according to the algorithm used during compression to restore the original image pixel data. High-efficiency codecs ensure that image quality and detail are maintained during the decompression process while reducing processing time and resource consumption.

[0073] S103: using the hardware acceleration unit 206 to quickly process the decompressed image data and convert it into a format that can be displayed by the FPV device 202;

[0074] S1031: Verify the decompressed data to ensure its integrity and accuracy;

[0075] S1032: inputting the decompressed image data into the hardware acceleration unit 206, applying an image processing algorithm on the hardware acceleration unit 206 to quickly process the image, the algorithm including color correction, contrast enhancement, sharpening, denoising and format conversion;

[0076] S1033: Output the processed image data from the hardware acceleration unit 206 and convert it into a format that can be directly displayed by the FPV device 202.

[0077] Specifically, ensure that the image data received from the drone 201 has been decompressed and restored to the original image pixel data. Verify the decompressed data to ensure its integrity and accuracy. According to the performance requirements and image processing requirements of the FPV device 202, select a suitable hardware acceleration unit 206, such as a GPU (graphics processing unit), a DSP (digital signal processor) or a dedicated image processing chip. These hardware acceleration units 206 usually have high-performance parallel processing capabilities, which can significantly improve the speed and efficiency of image processing.

[0078] The decompressed image data is input into the hardware acceleration unit 206. This is usually achieved through a dedicated data interface or memory mapping. Image processing algorithms are applied to the hardware acceleration unit 206 to quickly process the image. These algorithms include: Color correction: adjust the color balance and saturation of the image to make it more in line with the visual habits of the human eye. Contrast enhancement: improve the contrast of the image to make the image clearer. Sharpening: enhance the edge details of the image to make the image sharper. Denoising: remove noise and artifacts in the image to improve image quality. Format conversion: convert the image data into a format that can be displayed by the FPV device 202, such as a specific resolution, color depth, and encoding method. Accelerated processing: use the parallel processing capabilities and dedicated algorithms of the hardware acceleration unit 206 to quickly process the image data. This can significantly reduce processing time and improve real-time performance. The processed image data is output from the hardware acceleration unit 206. This is also achieved through a dedicated data interface or memory mapping. If necessary, the processed image data is further converted into a format that can be directly displayed by the FPV device 202. This may include adjusting parameters such as resolution, color depth, encoding method, etc. to ensure compatibility and display effect with FPV device 202. The converted image data is sent to the display screen of FPV device 202 for display. Ensure that parameters such as image quality, refresh rate and color performance meet user requirements.

[0079] S104: Ensure the continuity and fluency of image data through caching and buffering mechanisms.

[0080] S1041: Loading the image data that was recently accessed or is about to be accessed into the memory cache;

[0081] S1042: adopt LruCache cache strategy;

[0082] S1043: When new image data arrives, update the data in the memory according to the cache strategy to ensure that the data in the cache is always up to date.

[0083] Specifically, first, load the image data that was recently accessed or is about to be accessed into the memory cache. The memory cache provides fast data access speed and can quickly respond to the display needs of FPV glasses. Use efficient caching strategies such as LruCache (least recently used) to ensure that the data in the cache is the most likely to be accessed again. When new image data arrives, update the data in the memory according to the caching strategy to ensure that the data in the cache is always up to date. You can also use local caching: store image data in local storage devices (such as SD cards, solid-state drives, etc.) as a supplement to the memory cache. When the memory cache is insufficient, data can be quickly loaded from the local cache. Clean up old data in the local cache regularly to free up storage space and optimize cache performance.

[0084] S1044: during the image data transmission process, setting a receiving buffer to temporarily store the received image data;

[0085] S1045: Before sending the image data to the FPV device 202, a sending buffer is set to temporarily store the data to be sent;

[0086] S1046: dynamically adjusting the sizes of the receiving buffer and the sending buffer according to factors such as network bandwidth and device processing capability;

[0087] S1047: Setting different priorities for different types of image data.

[0088] Specifically, during the image data transmission process, a receiving buffer is set to temporarily store the image data received from the drone 201 or other transmission devices. This can smooth out fluctuations in the data transmission process and reduce image interruptions caused by network delays or transmission errors. Before sending the image data to the FPV glasses, a sending buffer is set to temporarily store the data to be sent. This can ensure the continuity and smoothness of the data and reduce image freezes caused by differences in device processing speeds. The sizes of the receiving buffer and the sending buffer are dynamically adjusted according to factors such as network bandwidth and device processing power. Ensure that the buffer can accommodate enough data to ensure continuity without wasting resources due to being too large. Set different priorities for different types of image data. For example, image data with higher real-time requirements can be processed and sent first; while non-real-time data can be appropriately delayed.

[0089] The cache and buffer mechanisms are combined to form a complete image data transmission and processing system. The cache mechanism is used to increase data access speed, and the buffer mechanism is used to smooth data transmission fluctuations, jointly ensuring the continuity and fluency of image data.

[0090] The digital image transmission module 204 supports the capture and transmission of high-definition image data, ensuring the clarity and detail of the image. It adopts advanced digital image transmission technology, such as DJI FPV high-definition low-latency digital image transmission technology, which can achieve an image transmission delay of less than 28ms (in 720p / 120fps mode), greatly improving the flight experience and control accuracy. The built-in anti-interference mechanism of the FPV device 202 can effectively resist external electromagnetic interference and ensure the stable transmission of image data in complex environments. For example, the DJIFPV image transmission sky end can support up to 8 independent communication frequency bands and support multiple aircraft flying at the same time without interfering with each other, which provides convenience for team work. The image data is quickly processed through the efficient codec and hardware acceleration unit 206, which not only shortens the processing time, but also reduces the burden on the CPU and improves the performance of the overall system. The processed image data can be quickly converted into a format that can be displayed by the FPV device 202, and the continuity and smoothness of the image data are ensured through the cache and buffering mechanism, providing users with a seamless visual experience and effectively improving the user experience.

[0091] The second embodiment of the present application is:

[0092] Based on the first embodiment, please refer to Figure 7 ,in, Figure 7 1 is a block diagram of a UAV FPV remote sensing audiovisual system according to a second embodiment of the present invention. A UAV FPV remote sensing audiovisual system according to this embodiment includes a UAV 201, an FPV device 202, an antenna system 203, a digital image transmission module 204, a codec 205, a hardware acceleration unit 206, a cache and buffer unit 207, and an anti-interference module 208.

[0093] For this specific implementation, the antenna system 203 is respectively provided on the wireless machine and the FPV device 202 to enhance the signal receiving capability and coverage;

[0094] The digital image transmission module 204 is disposed on the drone 201 and is used to capture and transmit high-definition image data in real time;

[0095] The codec 205 is disposed between the drone 201 and the FPV device 202 and is used to efficiently compress and decompress the transmitted image data;

[0096] The hardware acceleration unit 206 is integrated into the FPV device 202 and uses GPU acceleration or a dedicated hardware processor to quickly process image data;

[0097] The cache and buffer unit 207 is arranged in the FPV device 202, and is used for caching and buffering image data;

[0098] The anti-interference module 208 is disposed on the antenna system 203, selects a low-interference frequency band for transmission, and uses channel coding technology to enhance the anti-interference capability of the signal.

[0099] A drone FPV remote sensing audio-visual system using this embodiment, the antenna system 203 is respectively deployed on the drone 201 and the FPV device 202, and is the portal for signal transmission. The antenna at the drone 201 end is responsible for transmitting the high-definition image signal emitted by the digital image transmission module 204, and the antenna at the FPV device 202 end is responsible for receiving these signals. The anti-interference module 208 is integrated in the antenna system 203, which analyzes the electromagnetic spectrum of the surrounding environment and intelligently selects the frequency band with lower interference for transmission, thereby reducing signal interference and attenuation. At the same time, channel coding technology (such as forward error correction code FEC) is used to add redundant information to the signal so that the original data can be restored when the signal is partially damaged, further enhancing the anti-interference ability and reliability of the signal. The digital image transmission module 204 is the core component on the drone 201, which is responsible for real-time capture of high-definition image data captured by the camera of the drone 201, and converts it into a digital format suitable for wireless transmission. This module is closely integrated with other systems on the drone 201 (such as flight control system, camera control system) to ensure the real-time and accuracy of image data. The codec 205 is arranged on the communication link between the drone 201 and the FPV device 202, and is a bridge for data transmission. The encoder efficiently compresses the high-definition image data at the drone 201 end to reduce the bandwidth required for data transmission and reduce latency. The compressed data is transmitted to the FPV device 202 via a wireless channel, and then decompressed by the decoder to restore the original high-definition image. This process significantly improves the efficiency and reliability of data transmission. The hardware acceleration unit 206 is integrated in the FPV device 202, and uses GPU acceleration or a dedicated hardware processor to quickly process the received image data. These processes include but are not limited to image decoding, color correction, sharpening, denoising, etc., which are intended to improve image quality and viewing experience. The presence of the hardware acceleration unit 206 reduces the burden on the CPU, allowing the FPV device 202 to display high-definition images more smoothly. The cache and buffer unit 207 is arranged inside the FPV device 202 for caching and buffering image data. Since there may be delays, packet loss and other problems in the wireless transmission process, the cache and buffer unit 207 can temporarily store the received data and output it at an appropriate time, so as to smoothly display the image and reduce the phenomenon of screen freeze or frame skipping caused by data interruption. In addition, the cache unit can also be used to realize the pre-fetching and playback functions of data to improve the user experience.

[0100] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A UAV FPV remote sensing audio-visual method, It is characterized in that The following steps are involved: The drone captures high-definition image data through the digital image transmission module and transmits it to the FPV device through the antenna system; The FPV device receives image data through an anti-interference mechanism and decompresses it through an efficient codec; The hardware acceleration unit is used to quickly process the decompressed image data and convert it into a format that can be displayed by the FPV device; The continuity and smoothness of image data are ensured through caching and buffering mechanisms.

2. The UAV FPV remote sensing audio-visual method as claimed in claim 1, It is characterized in that The drone captures high-definition image data through a digital image transmission module and transmits it to the FPV device through an antenna system. The steps also include: After the drone camera captures high-definition image data, it transmits the image data to the digital image transmission module for processing; The digital image transmission module compresses the image data. The compression algorithm retains the key information of the image while removing redundant data. The compressed image data is encoded and converted into a format suitable for wireless transmission. The encoded image data is modulated onto a high-frequency carrier to form a radio signal; The antenna system on the drone transmits the modulated radio signal to the FPV device.

3. The UAV FPV remote sensing audio-visual method as claimed in claim 2, It is characterized in that The FPV device receives the image data through the anti-interference mechanism and decompresses it through the efficient codec, and the steps further include: The antenna system on the FPV device receives radio signals; During reception, FPV equipment uses frequency diversity, space diversity, time diversity and other technologies to suppress interference and noise; The received signal is pre-processed, including filtering, amplification and synchronization; During preprocessing, signal loss during transmission is restored.

4. The UAV FPV remote sensing audio-visual method as claimed in claim 3, It is characterized in that The FPV device receives the image data through the anti-interference mechanism and decompresses it through the efficient codec, and the steps further include: The pre-processed signal is first demodulated to restore the information on the high-frequency carrier to the baseband signal; The demodulated signal is then decoded to restore the encoded data to the original image data; The decoded image data is decompressed, and the decompression process performs the inverse operation according to the algorithm used during compression to restore the original image pixel data.

5. The UAV FPV remote sensing audio-visual method as claimed in claim 4, It is characterized in that The decompressed image data is quickly processed by a hardware acceleration unit and converted into a format displayable by the FPV device. The steps further include: Verify the decompressed data to ensure its integrity and accuracy; The decompressed image data is input into the hardware acceleration unit, and the image processing algorithm is applied on the hardware acceleration unit to quickly process the image, and the algorithm includes color correction, contrast enhancement, sharpening, denoising and format conversion; The processed image data is output from the hardware acceleration unit and converted into a format that can be directly displayed by the FPV device.

6. The UAV FPV remote sensing audio-visual method as claimed in claim 5, It is characterized in that The continuity and fluency of the image data are ensured by caching and buffering mechanisms, and the steps further include: Load recently accessed or soon-to-be-accessed image data into the memory cache; Use LruCache cache strategy; When new image data arrives, the data in memory is updated according to the cache strategy to ensure that the data in the cache is always up to date.

7. The UAV FPV remote sensing audio-visual method as claimed in claim 5, It is characterized in that The continuity and fluency of the image data are ensured by caching and buffering mechanisms, and the steps further include: During the image data transmission process, a receiving buffer is set to temporarily store the received image data; Before sending the image data to the FPV device, set up a send buffer to temporarily store the data to be sent; Dynamically adjust the size of the receive buffer and send buffer based on network bandwidth and device processing capabilities; Set different priorities for different types of image data.

8. An unmanned aerial vehicle FPV remote sensing audio-visual system, suitable for the unmanned aerial vehicle FPV remote sensing audio-visual method as claimed in claim 1, It is characterized in that Including drones, FPV equipment, antenna systems, digital image transmission modules, codecs, hardware acceleration units, cache and buffer units, and anti-interference modules; The antenna system is respectively arranged on the wireless device and the FPV device to enhance the signal receiving capability and coverage; The digital image transmission module is arranged on the drone and is used to capture and transmit high-definition image data in real time; The codec is arranged between the drone and the FPV device, and is used to efficiently compress and decompress the transmitted image data; The hardware acceleration unit is integrated into the FPV device and uses GPU acceleration or a dedicated hardware processor to quickly process image data; The cache and buffer unit is arranged in the FPV device and is used for caching and buffering image data; The anti-interference module is arranged on the antenna system, selects a low-interference frequency band for transmission, and adopts channel coding technology to enhance the anti-interference capability of the signal.

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