An antenna signal transmission detection system and method based on multi-channel anti-interference

Abstract

An antenna signal transmission detection system and method based on multi-channel anti-interference, which relates to the technical field of antenna signal transmission, collects multi-source heterogeneous data sent by an unmanned aerial vehicle (UAV) to a ground receiving end and marks the collection time, and obtains the initial LDPC coding coefficients corresponding to different carrier frequencies at each three-dimensional coordinate point of the UAV; performs physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and determines whether to update the coding coefficients of the UAV in real time according to the physical environment detection result; when the initial coding coefficients corresponding to different carriers are updated to new coding coefficients, obtains the resource transmission efficiency of each carrier frequency, obtains the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feeds it back to the UAV, and when the physical environment detection result meets the requirements, performs channel detection and feeds back to the UAV according to the channel detection result, significantly improving the communication efficiency and reliability between the UAV and the ground receiving end.

Description

Technical Field

[0001] The present invention relates to the technical field of antenna signal transmission, and specifically to an antenna signal transmission detection system and method based on multi-channel anti-interference. Background Art

[0002] The prior art CN117169821A, "Radar Antenna System and Signal Processing Method", includes: a transmitting antenna group containing at least two transmitting antennas, where the at least two transmitting antennas respectively correspond to different operating frequency bands; a controller connected to the transmitting antenna group, configured to divide the Chirp transmission period into multiple period segments, allocate the multiple period segments to the at least two transmitting antennas respectively, and control the at least two transmitting antennas to transmit radar signals in a time-sharing manner within the Chirp transmission period according to the period segment allocation result.

[0003] The prior art CN101174871A, "Method and Device for Processing Signals in Beam Space of Multiple Antennas", includes performing shaped reception on signals received by multiple antennas, converting the signals received by the multiple antennas into multiple beam space reception signals; performing channel estimation based on the multiple beam space reception signals; and performing data detection on the multiple beam space reception signals according to the channel estimation result.

[0004] To better understand the advantages and beneficial effects of the above technical solutions, we can compare the existing technical background and point out its deficiencies. This can help us more clearly understand how the new technical solution solves the problems existing in the prior art.

[0005] Existing wireless communication systems have many deficiencies in aspects such as coding and modulation schemes, carrier frequency selection, real-time feedback mechanisms, data acquisition and processing, resource allocation, channel detection, and comprehensive optimization. These deficiencies limit the reliability, efficiency, and flexibility of the communication system and cannot well adapt to complex and changing physical environments. For example, traditional wireless communication systems usually adopt fixed coding and modulation schemes without considering the changes in the actual communication environment. In a changing physical environment, fixed coding and modulation schemes may lead to an increase in the bit error rate and a decrease in communication reliability. During the flight of an unmanned aerial vehicle, due to changes in environmental conditions, fixed coding and modulation schemes cannot adapt to the new channel conditions, resulting in low data transmission efficiency. Existing communication systems often lack a real-time feedback mechanism and cannot dynamically adjust transmission parameters according to the current channel state. Without a real-time feedback mechanism, the communication system cannot timely detect and correct problems in the channel, resulting in unstable data transmission quality. When an unmanned aerial vehicle is performing a task, if the channel conditions suddenly deteriorate and there is no real-time feedback mechanism to timely adjust the transmission parameters, it may lead to data loss or delay. At the same time, existing wireless communication systems often adopt static resource allocation schemes without considering the dynamic allocation of resources;

[0006] Therefore, how to significantly improve the communication performance between the UAV and the ground receiving end by means of dynamically adjusting LDPC coding coefficients, multi-carrier frequency selection, real-time feedback mechanism, dynamic resource allocation, etc. is an urgent problem for us to solve. Summary of the Invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide an antenna signal transmission detection method based on multi-channel anti-interference, including the following steps:

[0008] Step s1: Collect multi-source heterogeneous data sent by the UAV to the ground receiving end and mark the collection time, set the collection period, and the multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points;

[0009] Step s2: Obtain the three-dimensional coordinate point time series of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the three-dimensional coordinate point time series, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table;

[0010] Step s3: Perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and determine whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection results;

[0011] Step s4: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the resource transmission efficiency of each carrier frequency, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the UAV. When the physical environment detection results meet the requirements, perform channel detection and feedback to the UAV according to the channel detection results.

[0012] Further, the process of obtaining the three-dimensional coordinate point time series of the UAV in the flight area according to the flight mission of the UAV, obtaining the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the three-dimensional coordinate point time series, constructing an LDPC coding coefficient look-up table, and obtaining the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table includes:

[0013] Construct a three-dimensional coordinate system for the flight area, obtain the flight route trajectory and the trajectory route timestamp of the drone in the flight mission, obtain the time series of three-dimensional coordinate points of the drone in the three-dimensional coordinate system according to the flight route trajectory and the predetermined route trajectory time, construct a physical environment prediction model based on deep learning, obtain the predicted physical environment data corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points according to the physical environment prediction model, obtain the three-dimensional coordinate point of the ground receiving end in the three-dimensional coordinate system, and obtain the Euclidean distance between each three-dimensional coordinate point in the time series of three-dimensional coordinate points and the three-dimensional coordinate point of the ground receiving end according to the three-dimensional coordinate point of the ground receiving end, and mark the Euclidean distance as the transmission distance;

[0014] When the drone reaches a certain three-dimensional coordinate point of the flight trajectory, obtain the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point that the drone has passed before, and mark the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point that the drone has passed before as the predicted physical environment sequence of the certain three-dimensional coordinate point, and so on, to obtain the predicted physical environment sequences of each three-dimensional coordinate point of the flight trajectory;

[0015] Obtain the LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the drone at each three-dimensional coordinate point according to the predicted physical environment data sequence, transmission distance, and LDPC coding coefficient look-up table corresponding to each three-dimensional coordinate point.

[0016] Further, the process of constructing the LDPC coding coefficient look-up table includes:

[0017] Based on the idea of imitation learning, use a simulator to generate simulated training sequences corresponding to different LDPC coding parameters, set up a simulated channel, and use the drone to send the simulated training sequences corresponding to different LDPC coding parameters through different carrier frequencies to the ground receiving end under different transmission distances and physical environment data sequences conditions through the simulated channel. Perform bit error rate detection on the simulated training sequences corresponding to different LDPC coding parameters of different carrier frequencies received by the ground receiving end, obtain the bit error rates corresponding to the simulated training sequences corresponding to different LDPC coding parameters of different carrier frequencies under different transmission distances and physical environment data sequences conditions, and screen out the simulated training sequences whose corresponding bit error rates are within the preset bit error rate threshold range, and mark the simulated training sequences as qualified simulated training sequences;

[0018] Construct an LDPC coding coefficient look-up table according to the LDPC coding parameters, transmission distance, physical environment data sequence, and carrier frequency corresponding to several qualified simulated training sequences. The LDPC coding coefficient look-up table includes the LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distance conditions.

[0019] Further, the process of performing physical environment detection on the multi-source heterogeneous data received by the ground receiving end and determining whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection results includes:

[0020] When the ground receiving end receives the multi-source heterogeneous data sent by the UAV, extract the preset training sequence, baseband signal, physical environment data, and three-dimensional coordinate points in the multi-source heterogeneous data, obtain the physical environment data sequence of the three-dimensional coordinate points, compare the similarity between the physical environment data sequence and the predicted physical environment data sequence of the three-dimensional coordinate points, obtain the physical environment similarity of the three-dimensional coordinate points. If the physical environment similarity is less than the preset physical environment similarity threshold, obtain the new LDPC coding coefficients corresponding to different carrier frequencies according to the physical environment data sequence, transmission distance, and LDPC coding coefficient look-up table corresponding to the three-dimensional coordinate points, perform coding coefficient detection on the new LDPC coding coefficients corresponding to different carriers, and feedback to the UAV according to the coding coefficient detection results. If the physical environment similarity is greater than or equal to the preset physical environment similarity threshold, the UAV continues to use the initial LDPC coding coefficients corresponding to different carrier frequencies, performs channel detection, and feedback to the UAV according to the channel detection results.

[0021] Further, the process of obtaining the resource transmission efficiency of each carrier frequency when the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients includes:

[0022] When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, analyze the multi-source heterogeneous data received by the ground receiving end according to the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the coded data corresponding to the multi-source heterogeneous data encoded by the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the occupied bandwidth corresponding to the coded data, determine the occupied bandwidth corresponding to different carrier frequencies according to the occupied bandwidth corresponding to the coded data, obtain the allocated bandwidth corresponding to each carrier frequency in each channel, obtain the total allocated bandwidth of each carrier frequency according to the allocated bandwidth corresponding to each carrier frequency in each channel, and obtain the resource transmission efficiency of each carrier frequency according to the total allocated bandwidth of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency.

[0023] Further, the process of obtaining the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feeding it back to the UAV includes:

[0024] Sequentially sort each carrier frequency according to the resource transmission efficiency of each carrier frequency, obtain a carrier frequency queue, obtain the first carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth of the first carrier frequency is greater than or equal to the occupied bandwidth corresponding to the first carrier frequency. If it is greater than or equal to, mark the first carrier frequency as a high-efficiency carrier frequency and feedback it to the UAV;

[0025] If it is not greater than or equal to, obtain the bandwidth difference between the occupied bandwidth corresponding to the first carrier frequency and the total allocated bandwidth of the first carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the second carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the second carrier frequency is greater than or equal to the bandwidth to be modulated. If it is greater than or equal to, mark the first carrier frequency and the second carrier frequency as high-efficiency carrier frequencies and feedback them to the UAV. If it is not greater than or equal to, obtain the bandwidth difference between the bandwidth to be modulated and the total allocated bandwidth corresponding to the second carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the third carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the third carrier frequency is greater than or equal to the bandwidth to be modulated, and so on, until high-efficiency carrier frequencies are obtained and feedback to the UAV.

[0026] Further, when the physical environment detection result meets the requirements, the process of performing channel detection and feeding back to the UAV according to the channel detection result includes:

[0027] Compare the preset training sequences received by each channel of the ground terminal with the preset training sequences sent by the UAV to obtain the bit error rate of each channel, compare the bit error rate of each channel with the preset bit error rate threshold. If the bit error rate of the channel is not less than the preset bit error rate threshold, mark the channel as an unqualified channel and feedback it to the UAV.

[0028] An antenna signal transmission detection system based on multi-channel anti-interference includes a monitoring center, and the monitoring center is communicatively connected with a data acquisition module, a data preprocessing module, a physical environment detection module, and a data feedback module;

[0029] The data acquisition module is used to collect multi-source heterogeneous data sent by the UAV to the ground receiving end, mark the acquisition time, and set the acquisition period. The multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points;

[0030] The data preprocessing module is used to obtain the time series of three-dimensional coordinate points of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and LDPC coding coefficient look-up table;

[0031] The physical environment detection module is used to perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and judge whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection result;

[0032] The data feedback module is used to obtain the resource transmission efficiency of each carrier frequency when the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the UAV. When the physical environment detection result meets the requirements, channel detection is performed, and the UAV is feedback according to the channel detection result.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. Dynamic adaptability:

[0035] By detecting the changes in the physical environment and transmission conditions in real time and dynamically adjusting the LDPC coding coefficients, the communication system can better adapt to different environmental conditions. Adjusting the coding coefficients in time according to the physical environment detection result can reduce the bit error rate and improve the reliability of data transmission.

[0036] 2. Refined management:

[0037] By collecting multi-source heterogeneous data including preset training sequences, baseband signals, physical environment data, and three-dimensional coordinate points, and marking the collection time, the state of the communication link can be understood more comprehensively. At the same time, the time series of three-dimensional coordinate points of the UAV in the flight area is obtained. Combining the predicted physical environment data and transmission distance, the changes in communication conditions can be predicted more accurately.

[0038] 3. Resource optimization:

[0039] Construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and LDPC coding coefficient look-up table, so as to optimize resource allocation. At the same time, by obtaining the resource transmission efficiency of each carrier frequency and selecting the high-efficiency carrier frequency for transmission, the resource utilization rate can be maximized.

[0040] 4. Intelligent feedback mechanism:

[0041] Performing channel detection and providing feedback to the UAV based on the channel detection results can enable the UAV to adjust transmission parameters according to the latest channel status, further improving communication performance. At the same time, through the feedback mechanism, a closed-loop control system is formed to ensure that the communication link is always in the best state.

[0042] 5. Anti-interference ability:

[0043] By selecting different carrier frequencies, the impact of narrowband interference can be effectively dispersed, improving the anti-interference ability. Adjusting the modulation method and coding rate according to the real-time bit error rate can improve the data transmission efficiency while ensuring communication quality.

[0044] 6. Improving overall performance:

[0045] By dynamically selecting high-efficiency carrier frequencies, the data transmission rate can be increased on the premise of ensuring communication quality. At the same time, combining information from multiple aspects such as multi-source heterogeneous data collection, physical environment detection, and channel detection, comprehensive optimization can be achieved to comprehensively improve the performance of the communication system.

[0046] 7. Flexibility:

[0047] This technical solution is not only applicable to the antenna signal communication transmission between UAVs and ground receiving ends, but can also be extended to other antenna signal communication fields, such as vehicle-to-everything (V2X) and the Internet of Things (IoT).

[0048] Compared with the existing technology, the technical solution of the present invention significantly improves the communication efficiency and reliability between UAVs and ground receiving ends through means such as dynamically adjusting LDPC coding coefficients, refined management, and resource optimization. This intelligent communication system design can not only adapt to complex physical environment changes, but also ensure that the communication link always maintains the best state through a real-time feedback mechanism, thus providing a new solution for the antenna signal transmission communication between UAVs and ground receiving ends. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of a method for detecting antenna signal transmission based on multi-channel anti-interference according to an embodiment of the present application.

[0050] Figure 2 It is a schematic diagram of a system for detecting antenna signal transmission based on multi-channel anti-interference according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] Combined with the accompanying drawings in the embodiments of the present application, the technical solutions in the embodiments of the present application are clearly and completely described. Obviously, the described embodiments are part 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 skilled in the art without creative efforts belong to the scope of protection of the present application.

[0052] As Figure 1 shown, a method for detecting antenna signal transmission based on multi-channel anti-interference includes the following steps:

[0053] Step S1: Collect multi-source heterogeneous data sent by the unmanned aerial vehicle (UAV) to the ground receiving end and mark the collection time, set the collection period. The multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points.

[0054] Step S2: Obtain the time series of three-dimensional coordinate points of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table.

[0055] Step S3: Perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and determine whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection result.

[0056] Step S4: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the resource transmission efficiency of each carrier frequency, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the UAV. When the physical environment detection result meets the requirements, perform channel detection and feedback to the UAV according to the channel detection result.

[0057] It should be further noted that in the specific implementation process, the process of obtaining the time series of three-dimensional coordinate points of the UAV in the flight area according to the flight mission of the UAV, obtaining the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points, constructing an LDPC coding coefficient look-up table, and obtaining the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table includes:

[0058] Construct a three-dimensional coordinate system for the flight area, obtain the flight route trajectory and trajectory route timestamps of the UAV in the flight mission, obtain the time series of three-dimensional coordinate points of the UAV in the three-dimensional coordinate system according to the flight route trajectory and the scheduled route trajectory time, construct a physical environment prediction model based on deep learning, obtain the predicted physical environment data corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points according to the physical environment prediction model, obtain the three-dimensional coordinate points of the ground receiving end in the three-dimensional coordinate system, and obtain the Euclidean distance between each three-dimensional coordinate point in the time series of three-dimensional coordinate points and the three-dimensional coordinate points of the ground receiving end according to the three-dimensional coordinate points of the ground receiving end, and mark the Euclidean distance as the transmission distance;

[0059] When the UAV reaches a certain three-dimensional coordinate point on the flight trajectory, obtain the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point that the UAV has passed through before, and mark the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point that the UAV has passed through before as the predicted physical environment sequence of the certain three-dimensional coordinate point, and so on, to obtain the predicted physical environment sequences of each three-dimensional coordinate point on the flight trajectory;

[0060] Obtain the LDPC coding coefficient comparison table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data sequence, transmission distance, and LDPC coding coefficient comparison table corresponding to each three-dimensional coordinate point.

[0061] It should be further noted that in the specific implementation process, the process of constructing the physical environment prediction model based on deep learning includes:

[0062] Obtain the physical environment data collected at each three-dimensional coordinate point in the three-dimensional coordinate system of the flight area by several UAVs in several historical acquisition periods, use the physical environment data as the training set and the test set, input the training set into the physical environment prediction model for training until the loss function is trained stably, save the model parameters, test the physical environment prediction model through the test set until it meets the preset requirements, and output the physical environment prediction model.

[0063] It should be further noted that in the specific implementation process, the process of constructing the LDPC coding coefficient comparison table includes:

[0064] Based on the idea of imitation learning, a simulator is used to generate simulated training sequences corresponding to different LDPC coding parameters. A simulated channel is set up. Using drones, under different transmission distances and physical environment data sequence conditions, the simulated training sequences corresponding to different LDPC coding parameters are sent to the ground receiving end through different carrier frequencies via the simulated channel. For the simulated training sequences corresponding to different LDPC coding parameters with different carrier frequencies received by the ground receiving end, the bit error rate is detected, and the bit error rates corresponding to the simulated training sequences with different LDPC coding parameters and different carrier frequencies under different transmission distances and physical environment data sequence conditions are obtained. The simulated training sequences with corresponding bit error rates within the preset bit error rate threshold range are screened out, and the said simulated training sequences are marked as qualified simulated training sequences;

[0065] According to the LDPC coding parameters, transmission distances, physical environment data sequences, and carrier frequencies corresponding to several qualified simulated training sequences, an LDPC coding coefficient comparison table is constructed. The LDPC coding coefficient comparison table includes the LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distance conditions. The LDPC coding parameters include code rate, code length, decoding iteration times, and parity check matrix.

[0066] It should be further noted that in the specific implementation process, the process of detecting the physical environment of the multi-source heterogeneous data received by the ground receiving end and determining whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the drone in real time includes:

[0067] When the ground receiving end receives the multi-source heterogeneous data sent by the drone, the preset training sequence, baseband signal, physical environment data, and three-dimensional coordinate points in the multi-source heterogeneous data are extracted, and the physical environment data sequence of the three-dimensional coordinate points is obtained. The physical environment data sequence is compared with the predicted physical environment data sequence of the three-dimensional coordinate points to obtain the physical environment similarity of the three-dimensional coordinate points. If the physical environment similarity is less than the preset physical environment similarity threshold, new LDPC coding coefficients corresponding to different carrier frequencies are obtained according to the physical environment data sequence, transmission distance, and LDPC coding coefficient comparison table corresponding to the three-dimensional coordinate points, and the new LDPC coding coefficients corresponding to different carriers are subjected to coding coefficient detection, and the drone is fed back according to the coding coefficient detection result. If the physical environment similarity is greater than or equal to the preset physical environment similarity threshold, the drone continues to use the initial LDPC coding coefficients corresponding to different carrier frequencies, and channel detection is performed, and the drone is fed back according to the channel detection result.

[0068] It should be further noted that in the specific implementation process, the calculation formula for obtaining the physical environment similarity of the three-dimensional coordinate points is:

[0069]

[0070] Among them, s represents the physical environment similarity, D ij represents the value corresponding to the j-th type index in the physical environment data of the i-th three-dimensional coordinate point passed by the drone in the physical environment data sequence. The type indexes in the physical environment data include temperature, humidity, wind speed and direction, rainfall, and atmospheric particulate matter concentration, etc. DA ij represents the predicted value corresponding to the j-th type index in the physical environment data of the i-th three-dimensional coordinate point in the predicted physical environment data sequence. n1 represents the total number of three-dimensional coordinate points passed by the drone in the physical environment data sequence, n2 represents the total number of type indexes in the physical environment data, and θ represents the conversion coefficient.

[0071] It should be further noted that in the specific implementation process, when the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, the process of obtaining the resource transmission efficiency of each carrier frequency includes:

[0072] When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, analyze the multi-source heterogeneous data received by the ground receiving end according to the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the coded data corresponding to the multi-source heterogeneous data coded by the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the occupied bandwidth corresponding to the coded data, determine the occupied bandwidth corresponding to different carrier frequencies according to the occupied bandwidth corresponding to the coded data, obtain the allocated bandwidth corresponding to each carrier frequency in each channel, obtain the total allocated bandwidth of each carrier frequency according to the allocated bandwidth corresponding to each carrier frequency in each channel, and obtain the resource transmission efficiency of each carrier frequency according to the total allocated bandwidth of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency.

[0073] It should be further noted that in the specific implementation process, the calculation formula for obtaining the resource transmission efficiency of each carrier frequency according to the total allocated bandwidth of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency is:

[0074]

[0075] Among them, γ z represents the resource transmission efficiency of carrier frequency z, ef z represents the total allocated bandwidth of carrier frequency z, gf z represents the occupied bandwidth corresponding to carrier frequency z, and δ represents the conversion coefficient.

[0076] It should be further noted that in the specific implementation process, the process of obtaining the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feeding it back to the drone includes:

[0077] Sequentially sort each carrier frequency according to the resource transmission efficiency of each carrier frequency to obtain a carrier frequency queue. The greater the resource transmission efficiency, the higher the ranking in the carrier frequency queue. Obtain the first carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth of the first carrier frequency is greater than or equal to the occupied bandwidth corresponding to the first carrier frequency. If it is greater than or equal, mark the first carrier frequency as a high-efficiency carrier frequency and feedback it to the UAV. After receiving the high-efficiency carrier frequency, the UAV encodes the multi-source heterogeneous data according to the LDPC coding coefficient corresponding to the high-efficiency carrier frequency to generate encoded data, and modulates the encoded data onto the carrier frequency corresponding to the high-efficiency carrier frequency;

[0078] If it is not greater than or equal, obtain the bandwidth difference between the occupied bandwidth corresponding to the first carrier frequency and the total allocated bandwidth of the first carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the second carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the second carrier frequency is greater than or equal to the bandwidth to be modulated. If it is greater than or equal, mark the first carrier frequency and the second carrier frequency as high-efficiency carrier frequencies and feedback them to the UAV. If it is not greater than or equal, obtain the bandwidth difference between the bandwidth to be modulated and the total allocated bandwidth corresponding to the second carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the third carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the third carrier frequency is greater than or equal to the bandwidth to be modulated, and so on, until a high-efficiency carrier frequency is obtained and feedback to the UAV.

[0079] It should be further noted that in the specific implementation process, when the physical environment detection result meets the requirements, the process of performing channel detection and feeding back to the UAV according to the channel detection result includes:

[0080] Compare the preset training sequences received by each channel of the ground terminal with the preset training sequences sent by the UAV to obtain the bit error rate of each channel, compare the bit error rate of each channel with the preset bit error rate threshold. If the bit error rate of the channel is not less than the preset bit error rate threshold, mark the channel as an unqualified channel and feedback it to the UAV.

[0081] When the UAV receives an unqualified channel, re-perform the channel allocation operation.

[0082] As Figure 2 shown, an antenna signal transmission detection system based on multi-channel anti-interference includes a monitoring center, and the monitoring center is communicatively connected to a data acquisition module, a data preprocessing module, a physical environment detection module, and a data feedback module;

[0083] The data acquisition module is used to acquire multi-source heterogeneous data sent by the UAV to the ground receiving end, mark the acquisition time, and set the acquisition period. The multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points.

[0084] The data preprocessing module is used to obtain the time sequence of three-dimensional coordinate points of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time sequence of three-dimensional coordinate points, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table.

[0085] The physical environment detection module is used to perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and judge whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection result.

[0086] The data feedback module is used to obtain the resource transmission efficiency of each carrier frequency when the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the UAV. When the physical environment detection result meets the requirements, channel detection is performed, and the UAV is feedback according to the channel detection result.

[0087] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An antenna signal transmission detection method based on multi-channel anti-interference, characterized in that It includes the following steps: Step s1: Collect multi-source heterogeneous data sent by the drone to the ground receiving end, mark the collection time, and set the collection period. The multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points. Step s2: Obtain the time series of three-dimensional coordinate points of the drone in the flight area according to the flight mission of the drone, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the drone at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table. Step s3: Perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and determine whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the drone in real time according to the physical environment detection result. Step s4: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the resource transmission efficiency of each carrier frequency, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the drone. When the physical environment detection result meets the requirements, perform channel detection and feedback to the drone according to the channel detection result. The process of obtaining the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feeding it back to the drone includes: Sort the carrier frequencies in sequence according to the resource transmission efficiency of each carrier frequency to obtain a carrier frequency queue, obtain the first carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth of the first carrier frequency is greater than or equal to the occupied bandwidth corresponding to the first carrier frequency. If it is greater than or equal to, mark the first carrier frequency as the high-efficiency carrier frequency and feedback it to the drone. If it is not greater than or equal to, obtain the bandwidth difference between the occupied bandwidth corresponding to the first carrier frequency and the total allocated bandwidth of the first carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the second carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the second carrier frequency is greater than or equal to the bandwidth to be modulated. If it is greater than or equal to, mark the first carrier frequency and the second carrier frequency as the high-efficiency carrier frequencies and feedback them to the drone. If it is not greater than or equal to, obtain the bandwidth difference between the bandwidth to be modulated and the total allocated bandwidth corresponding to the second carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the total allocated bandwidth corresponding to the third carrier frequency in the carrier frequency queue, and determine whether the total allocated bandwidth corresponding to the third carrier frequency is greater than or equal to the bandwidth to be modulated, and so on, until the high-efficiency carrier frequency is obtained and feedback to the drone.

2. The method for detecting antenna signal transmission based on multi-channel anti-interference according to claim 1, wherein Obtain the time series of three-dimensional coordinate points of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and LDPC coding coefficient look-up table. The process includes: Construct a three-dimensional coordinate system of the flight area, obtain the flight route trajectory and trajectory route timestamp of the UAV in the flight mission, obtain the time series of three-dimensional coordinate points of the UAV in the three-dimensional coordinate system according to the flight route trajectory and the predetermined route trajectory time, construct a physical environment prediction model based on deep learning, obtain the predicted physical environment data corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points according to the physical environment prediction model, obtain the three-dimensional coordinate point of the ground receiving end in the three-dimensional coordinate system, and obtain the Euclidean distance between each three-dimensional coordinate point in the time series of three-dimensional coordinate points and the three-dimensional coordinate point of the ground receiving end. Mark the Euclidean distance as the transmission distance; When the UAV reaches a certain three-dimensional coordinate point on the flight trajectory, obtain the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point passed by the UAV before. Mark the predicted physical environment data of the certain three-dimensional coordinate point and the predicted physical environment data of each three-dimensional coordinate point passed by the UAV before as the predicted physical environment sequence of the certain three-dimensional coordinate point. And so on, obtain the predicted physical environment sequences of each three-dimensional coordinate point on the flight trajectory; Obtain the LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data sequence, transmission distance, and LDPC coding coefficient look-up table corresponding to each three-dimensional coordinate point.

3. A method for detecting antenna signal transmission based on multi-channel anti-interference according to claim 2, characterized in that, The process of constructing the LDPC coding coefficient look-up table includes: Based on the idea of imitation learning, use a simulator to generate simulated training sequences corresponding to different LDPC coding parameters, set up a simulated channel, and use the UAV to send the simulated training sequences corresponding to different LDPC coding parameters through different carrier frequencies to the ground receiving end under different transmission distances and physical environment data sequences conditions through the simulated channel. Perform bit error rate detection on the simulated training sequences corresponding to different LDPC coding parameters of different carrier frequencies received by the ground receiving end, obtain the bit error rates corresponding to the simulated training sequences corresponding to different LDPC coding parameters of different carrier frequencies under different transmission distances and physical environment data sequences conditions, screen out the simulated training sequences whose corresponding bit error rates are within the preset bit error rate threshold range, and mark the simulated training sequences as qualified simulated training sequences; Construct an LDPC coding coefficient look-up table based on the LDPC coding parameters, transmission distance, physical environment data sequence, and carrier frequency corresponding to a number of qualified simulation training sequences. The LDPC coding coefficient look-up table includes the LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distance conditions.

4. A method for detecting antenna signal transmission based on multi-channel anti-interference according to claim 3, characterized in that The process of performing physical environment detection on the multi-source heterogeneous data received by the ground receiving end and determining whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the unmanned aerial vehicle (UAV) according to the physical environment detection results includes: When the ground receiving end receives the multi-source heterogeneous data sent by the UAV, extract the preset training sequence, baseband signal, physical environment data, and three-dimensional coordinate points in the multi-source heterogeneous data, obtain the physical environment data sequence of the three-dimensional coordinate points, compare the similarity between the physical environment data sequence and the predicted physical environment data sequence of the three-dimensional coordinate points to obtain the physical environment similarity of the three-dimensional coordinate points. If the physical environment similarity is less than the preset physical environment similarity threshold, obtain the new LDPC coding coefficients corresponding to different carrier frequencies according to the physical environment data sequence, transmission distance, and LDPC coding coefficient look-up table corresponding to the three-dimensional coordinate points, perform coding coefficient detection on the new LDPC coding coefficients corresponding to different carriers, and provide feedback to the UAV according to the coding coefficient detection results. If the physical environment similarity is greater than or equal to the preset physical environment similarity threshold, the UAV continues to use the initial LDPC coding coefficients corresponding to different carrier frequencies, perform channel detection, and provide feedback to the UAV according to the channel detection results.

5. A method for detecting antenna signal transmission based on multi-channel anti-interference according to claim 4, characterized in that When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, the process of obtaining the resource transmission efficiency of each carrier frequency includes: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, analyze the multi-source heterogeneous data received by the ground receiving end according to the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the coded data corresponding to the multi-source heterogeneous data after being coded by the new LDPC coding coefficients corresponding to different carrier frequencies, obtain the occupied bandwidth corresponding to the coded data, determine the occupied bandwidth corresponding to different carrier frequencies according to the occupied bandwidth corresponding to the coded data, obtain the allocated bandwidth corresponding to each carrier frequency in each channel, obtain the total allocated bandwidth of each carrier frequency according to the allocated bandwidth corresponding to each carrier frequency in each channel, and obtain the resource transmission efficiency of each carrier frequency according to the total allocated bandwidth of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency.

6. A method for detecting antenna signal transmission based on multi-channel anti-interference according to claim 5, characterized in that, When the physical environment detection result meets the requirements, the process of performing channel detection and providing feedback to the UAV according to the channel detection results includes: Compare the error bits of the preset training sequence received by each channel of the ground terminal with the preset training sequence sent by the UAV to obtain the bit error rate of each channel, compare the bit error rate of each channel with the preset bit error rate threshold. If the bit error rate of the channel is not less than the preset bit error rate threshold, mark the channel as an unqualified channel and feedback it to the UAV.

7. An antenna signal transmission detection system based on multi-channel anti-interference, which is specifically applied to an antenna signal transmission detection method based on multi-channel anti-interference described in any one of claims 1 to 6, characterized in that It includes a monitoring center, which is communicatively connected to a data acquisition module, a data preprocessing module, a physical environment detection module, and a data feedback module; The data acquisition module is used to collect multi-source heterogeneous data sent by the UAV to the ground receiving end, mark the acquisition time, and set the acquisition period. The multi-source heterogeneous data includes a preset training sequence, a baseband signal, physical environment data, and three-dimensional coordinate points; The data preprocessing module is used to obtain the three-dimensional coordinate point time series of the UAV in the flight area according to the flight mission of the UAV, obtain the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the three-dimensional coordinate point time series, construct an LDPC coding coefficient look-up table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies of the UAV at each three-dimensional coordinate point according to the predicted physical environment data, transmission distance, and the LDPC coding coefficient look-up table; The physical environment detection module is used to perform physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and judge whether to update the LDPC coding coefficients corresponding to different carrier frequencies of the UAV in real time according to the physical environment detection results; The data feedback module is used to obtain the resource transmission efficiency of each carrier frequency when the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, obtain the high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feedback it to the UAV. When the physical environment detection result meets the requirements, perform channel detection and feedback to the UAV according to the channel detection results.

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