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

Abstract

The invention discloses an antenna signal transmission detection system and method based on multichannel anti-interference, and relates to the technical field of antenna signal transmission. Multi-source heterogeneous data sent by an unmanned aerial vehicle to a ground receiving end is collected, the collection time is marked, and initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to all three-dimensional coordinate points of the unmanned aerial vehicle are obtained; performing physical environment detection on the multi-source heterogeneous data received by the ground receiving end, and judging whether to update the coding coefficient of the unmanned aerial vehicle in real time according to a physical environment detection result; and when the initial coding coefficients corresponding to different carriers are updated to new coding coefficients, obtaining the resource transmission efficiency of each carrier frequency, obtaining a high-efficiency carrier frequency according to the resource transmission efficiency of each carrier frequency and feeding back the high-efficiency carrier frequency to the unmanned aerial vehicle, and when a physical environment detection result meets a requirement, performing channel detection. And the unmanned aerial vehicle is fed back according to the channel detection result, so that the communication efficiency and reliability between the unmanned aerial vehicle and the ground receiving end are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of antenna signal transmission, and in particular 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, including at least two transmitting antennas, and the at least two transmitting antennas correspond to different working frequency bands respectively; a controller, connected to the transmitting antenna group, is used to divide the Chirp transmission period into multiple period segments, and allocate the multiple period segments to at least two transmitting antennas respectively, and control the at least two transmitting antennas to transmit radar signals in time-sharing within the Chirp transmission period according to the period segment allocation results.

[0003] The prior art CN101174871A "A method and device for processing multi-antenna beam space signals" includes performing shaped reception on multiple antenna reception signals, converting the multiple antenna reception signals 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 based on the channel estimation results.

[0004] In order to better understand the advantages and beneficial effects of the above technical solutions, we can compare them with the existing technical background and point out their shortcomings. This can help us more clearly understand how the new technical solutions solve the problems existing in the existing technologies.

[0005] Existing wireless communication systems have many deficiencies in coding and modulation schemes, carrier frequency selection, real-time feedback mechanisms, data collection and processing, resource allocation, channel detection, and comprehensive optimization. These deficiencies limit the reliability, efficiency, and flexibility of communication systems, and make them unable to adapt well to complex and changing physical environments. For example, traditional wireless communication systems usually use fixed coding and modulation schemes without considering changes in the actual communication environment. In a changing physical environment, fixed coding and modulation schemes may lead to increased bit error rates and decreased communication reliability. During the flight of drones, due to changes in environmental conditions, fixed coding and modulation schemes cannot adapt to new channel conditions, resulting in low data transmission efficiency. Existing communication systems often lack real-time feedback mechanisms and cannot dynamically adjust transmission parameters according to the current channel status. Without real-time feedback mechanisms, communication systems cannot promptly detect and correct problems in the channel, resulting in unstable data transmission quality. When drones are performing tasks, if channel conditions suddenly deteriorate, there is no real-time feedback mechanism and transmission parameters cannot be adjusted in time, which may lead to data loss or delay. At the same time, existing wireless communication systems often use static resource configuration schemes without considering dynamic resource allocation.

[0006] Therefore, how to significantly improve the communication performance between the UAV and the ground receiver by dynamically adjusting the LDPC coding coefficients, multi-carrier frequency selection, real-time feedback mechanism, dynamic resource allocation, etc. is an issue that we urgently need to solve. Summary of the invention

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

[0008] Step s1: Collect multi-source heterogeneous data sent by the UAV to the ground receiving end, mark the collection time, and set the collection cycle, wherein 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 sequence 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 sequence, construct an LDPC coding coefficient comparison table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV according to the predicted physical environment data, transmission distance and LDPC coding coefficient comparison 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, the resource transmission efficiency of each carrier frequency is obtained, and the high-efficiency carrier frequency is obtained based on the resource transmission efficiency of each carrier frequency and fed back to the UAV. When the physical environment detection results meet the requirements, channel detection is performed, and feedback is given to the UAV based on the channel detection results.

[0012] Further, according to the flight mission of the UAV, a time series sequence of three-dimensional coordinate points of the UAV in the flight area is obtained, predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series sequence of three-dimensional coordinate points are obtained, and an LDPC coding coefficient comparison table is constructed. According to the predicted physical environment data, the transmission distance and the LDPC coding coefficient comparison table, the process of obtaining the initial LDPC coding coefficient corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV includes:

[0013] Construct a three-dimensional coordinate system of the flight area, obtain the flight route trajectory and trajectory timestamp of the drone in the flight mission, obtain the three-dimensional coordinate point time series sequence 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 three-dimensional coordinate point time series sequence according to the physical environment prediction model, obtain the three-dimensional coordinate point of the ground receiving end in the three-dimensional coordinate system, obtain the Euclidean distance between each three-dimensional coordinate point in the three-dimensional coordinate point time series sequence 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, 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 are obtained, and 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 are marked as a predicted physical environment sequence of the certain three-dimensional coordinate point, and so on, to obtain the predicted physical environment sequence of each three-dimensional coordinate point of the flight trajectory;

[0015] Obtain the LDPC coding coefficient comparison table, and obtain the initial LDPC coding coefficient corresponding to the 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.

[0016] Furthermore, the process of constructing the LDPC coding coefficient comparison table includes:

[0017] 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, and a UAV is used to send simulated training sequences corresponding to different LDPC coding parameters to a ground receiving end through different carrier frequencies under different transmission distances and physical environment data sequence conditions through a simulated channel. A bit error rate detection is performed on the simulated training sequences corresponding to different LDPC coding parameters with different carrier frequencies received by the ground receiving end, and the bit error rates corresponding to the simulated training sequences corresponding to different LDPC coding parameters with 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 a preset bit error rate threshold range are screened out, and the simulated training sequences are marked as qualified simulated training sequences;

[0018] An LDPC coding coefficient comparison table is constructed according to the LDPC coding parameters, transmission distances, physical environment data sequences and carrier frequencies corresponding to several qualified simulated training sequences. The LDPC coding coefficient comparison table includes LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distances.

[0019] Furthermore, 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, the preset training sequence, baseband signal, physical environment data and three-dimensional coordinate points in the multi-source heterogeneous data are extracted to obtain the physical environment data sequence of the three-dimensional coordinate points, and the physical environment data sequence is compared with the predicted physical environment data sequence of the three-dimensional coordinate points for similarity 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, the new LDPC coding coefficients corresponding to different carrier frequencies are obtained according to the physical environment data sequence corresponding to the three-dimensional coordinate points, the transmission distance and the LDPC coding coefficient comparison table, and the coding coefficient detection is performed on the new LDPC coding coefficients corresponding to different carriers, and the UAV 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 UAV continues to use the initial LDPC coding coefficients corresponding to different carrier frequencies, and performs channel detection, and the UAV is fed back according to the channel detection result.

[0021] Furthermore, 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:

[0022] When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, the multi-source heterogeneous data received by the ground receiving end are analyzed according to the new LDPC coding coefficients corresponding to different carrier frequencies, and the coded data corresponding to the multi-source heterogeneous data after being encoded by the new LDPC coding coefficients corresponding to different carrier frequencies is obtained, and the occupied bandwidth corresponding to the coded data is obtained, and the occupied bandwidth corresponding to the different carrier frequencies is determined according to the occupied bandwidth corresponding to the coded data, and the allocated bandwidth corresponding to each carrier frequency in each channel is obtained. According to the allocated bandwidth corresponding to each carrier frequency in each channel, the sum of the allocated bandwidths of each carrier frequency is obtained, and according to the sum of the allocated bandwidths of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency, the resource transmission efficiency of each carrier frequency is obtained.

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

[0024] Sort each carrier frequency in order according to its resource transmission efficiency, 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 so, mark the first carrier frequency as a high-efficiency carrier frequency and feed it back to the drone.

[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 sum of the allocated bandwidths of the first carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the sum of the allocated bandwidths corresponding to the second carrier frequencies in the carrier frequency queue, and determine whether the sum of the allocated bandwidths corresponding to the second carrier frequencies 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 feed them back to the drone. If it is not greater than or equal to, obtain the total bandwidth difference between the bandwidth to be modulated and the allocated bandwidth corresponding to the second carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the sum of the allocated bandwidths corresponding to the second-second carrier frequencies in the carrier frequency queue, and determine whether the sum of the allocated bandwidths corresponding to the second-second carrier frequencies is greater than or equal to the bandwidth to be modulated, and so on, until the high-efficiency carrier frequency is obtained and fed back to the drone.

[0026] Furthermore, when the physical environment detection result meets the requirements, channel detection is performed, and the process of providing feedback to the drone based on the channel detection result includes:

[0027] The preset training sequence received by each channel of the ground terminal receiving end is compared with the preset training sequence sent by the UAV to obtain the bit error rate of each channel, and the bit error rate of each channel is compared with the preset bit error rate threshold. If the bit error rate of the channel is less than the preset bit error rate threshold, the channel is marked as an unqualified channel and fed back to the UAV.

[0028] An antenna signal transmission detection system based on multi-channel anti-interference includes a monitoring center, wherein 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 drone to the ground receiving end, mark the acquisition time, and set the acquisition cycle, wherein 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 a time series of three-dimensional coordinate points of the drone in the flight area according to the flight mission of the drone, obtain predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of the three-dimensional coordinate points, construct an LDPC coding coefficient comparison table, and obtain initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the drone according to the predicted physical environment data, the transmission distance and the LDPC coding coefficient comparison table;

[0031] The physical environment detection module is used to perform physical environment detection on 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 results;

[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 feed it back to the drone, and when the physical environment detection result meets the requirements, perform channel detection and provide feedback to the drone based on the channel detection result.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. Dynamic adaptability:

[0035] By real-time detection of changes in the physical environment and transmission conditions, the LDPC coding coefficients can be dynamically adjusted, so that the communication system can better adapt to different environmental conditions. By timely adjusting the coding coefficients according to the physical environment detection results, the bit error rate can be reduced and the reliability of data transmission can be improved.

[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, we can have a more comprehensive understanding of the status of the communication link. At the same time, we can obtain the time series of the three-dimensional coordinate points of the drone in the flight area. Combined with the predicted physical environment data and transmission distance, we can more accurately predict changes in communication conditions.

[0038] 3. Resource optimization:

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

[0040] 4. Intelligent feedback mechanism:

[0041] By performing channel detection and providing feedback to the drone based on the channel detection results, the drone can adjust the transmission parameters according to the latest channel status to further improve 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, the anti-interference ability can be improved, and the modulation method and coding rate can be adjusted according to the real-time bit error rate, which can improve data transmission efficiency while ensuring communication quality.

[0044] 6. Improve overall performance:

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

[0046] 7. Flexibility:

[0047] This technical solution is not only applicable to antenna signal communication transmission between drones and ground receivers, but can also be extended to other antenna signal communication fields, such as Internet of Vehicles, Internet of Things, etc.

[0048] Compared with the prior art, the technical solution of the present invention significantly improves the communication efficiency and reliability between the UAV and the ground receiving end by dynamically adjusting the 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 remains in the best state through a real-time feedback mechanism, thereby providing a new solution for antenna signal transmission communication between the UAV and the ground receiving end. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0050] Figure 2 This is a schematic diagram of an antenna signal transmission detection system based on multi-channel anti-interference according to an embodiment of the present application. DETAILED DESCRIPTION

[0051] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0052] like Figure 1 As 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 UAV to the ground receiving end, mark the collection time, and set the collection cycle, wherein 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 three-dimensional coordinate point time series sequence 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 sequence, construct an LDPC coding coefficient comparison table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV according to the predicted physical environment data, transmission distance and LDPC coding coefficient comparison 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 results;

[0056] Step s4: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, the resource transmission efficiency of each carrier frequency is obtained, and the high-efficiency carrier frequency is obtained based on the resource transmission efficiency of each carrier frequency and fed back to the UAV. When the physical environment detection results meet the requirements, channel detection is performed, and feedback is given to the UAV based on the channel detection results.

[0057] It should be further explained that, in the specific implementation process, the three-dimensional coordinate point time series sequence of the UAV in the flight area is obtained according to the flight mission of the UAV, the predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the three-dimensional coordinate point time series sequence are obtained, and an LDPC coding coefficient comparison table is constructed. According to the predicted physical environment data, the transmission distance and the LDPC coding coefficient comparison table, the process of obtaining the initial LDPC coding coefficient corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV includes:

[0058] Construct a three-dimensional coordinate system of the flight area, obtain the flight route trajectory and trajectory timestamp of the drone in the flight mission, obtain the three-dimensional coordinate point time series sequence 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 three-dimensional coordinate point time series sequence according to the physical environment prediction model, obtain the three-dimensional coordinate point of the ground receiving end in the three-dimensional coordinate system, obtain the Euclidean distance between each three-dimensional coordinate point in the three-dimensional coordinate point time series sequence 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;

[0059] When the drone reaches a certain three-dimensional coordinate point of the flight trajectory, 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 are obtained, and 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 are marked as a predicted physical environment sequence of the certain three-dimensional coordinate point, and so on, to obtain the predicted physical environment sequence of each three-dimensional coordinate point of 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 explained that, in the specific implementation process, the process of building a physical environment prediction model based on deep learning includes:

[0062] Obtain physical environment data collected by several drones at each three-dimensional coordinate point in the three-dimensional coordinate system of the flight area during several historical collection cycles, use the physical environment data as a training set and a test set, input the training set into the physical environment prediction model for training until the loss function training is stable, 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 explained 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, and a UAV is used to send simulated training sequences corresponding to different LDPC coding parameters to a ground receiving end through different carrier frequencies under different transmission distances and physical environment data sequence conditions through a simulated channel. A bit error rate detection is performed on the simulated training sequences corresponding to different LDPC coding parameters with different carrier frequencies received by the ground receiving end, and the bit error rates corresponding to the simulated training sequences corresponding to different LDPC coding parameters with 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 a preset bit error rate threshold range are screened out, and the simulated training sequences are marked as qualified simulated training sequences;

[0065] An LDPC coding coefficient comparison table is constructed according to the LDPC coding parameters, transmission distances, physical environment data sequences and carrier frequencies corresponding to several qualified simulated training sequences. The LDPC coding coefficient comparison table includes LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distances. The LDPC coding parameters include code rate, code length, number of decoding iterations and parity check matrix.

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

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

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

[0069]

[0070] Among them, s represents the physical environment similarity, D ij It represents the value corresponding to the jth type indicator in the physical environment data of the ith three-dimensional coordinate point passed by the drone in the physical environment data sequence. The type indicators in the physical environment data include temperature, humidity, wind speed and direction, rainfall, and atmospheric particulate matter concentration. ij It represents the predicted value corresponding to the jth type indicator in the physical environment data of the i-th three-dimensional coordinate point in the 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 indicators in the physical environment data, and θ represents the conversion coefficient.

[0071] It should be further explained that, in a 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, the multi-source heterogeneous data received by the ground receiving end are analyzed according to the new LDPC coding coefficients corresponding to different carrier frequencies, and the coded data corresponding to the multi-source heterogeneous data after being encoded by the new LDPC coding coefficients corresponding to different carrier frequencies is obtained, and the occupied bandwidth corresponding to the coded data is obtained, and the occupied bandwidth corresponding to the different carrier frequencies is determined according to the occupied bandwidth corresponding to the coded data, and the allocated bandwidth corresponding to each carrier frequency in each channel is obtained. According to the allocated bandwidth corresponding to each carrier frequency in each channel, the sum of the allocated bandwidths of each carrier frequency is obtained, and according to the sum of the allocated bandwidths of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency, the resource transmission efficiency of each carrier frequency is obtained.

[0073] It should be further explained that, in the specific implementation process, according to the total allocated bandwidth of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency, the calculation formula for obtaining the resource transmission efficiency of 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 It represents the occupied bandwidth corresponding to the carrier frequency z, and δ represents the conversion coefficient.

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

[0077] Sort each carrier frequency in sequence according to the resource transmission efficiency of each carrier frequency, 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 of 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 feed it back to the drone. After receiving the high-efficiency carrier frequency, the drone encodes the multi-source heterogeneous data according to the LDPC coding coefficient corresponding to the high-efficiency carrier frequency to generate coded data, and modulates the coded data to the carrier frequency corresponding to the high-efficiency carrier frequency;

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

[0079] It should be further explained that, in the specific implementation process, when the physical environment detection results meet the requirements, channel detection is performed, and the process of providing feedback to the drone based on the channel detection results includes:

[0080] The preset training sequence received by each channel of the ground terminal receiving end is compared with the preset training sequence sent by the UAV to obtain the bit error rate of each channel, and the bit error rate of each channel is compared with the preset bit error rate threshold. If the bit error rate of the channel is less than the preset bit error rate threshold, the channel is marked as an unqualified channel and fed back to the UAV.

[0081] When the drone receives an unqualified channel, it will re-assign the channel.

[0082] like Figure 2 As shown, 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;

[0083] The data acquisition module is used to collect multi-source heterogeneous data sent by the drone to the ground receiving end, mark the acquisition time, and set the acquisition cycle, wherein 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 a time series of three-dimensional coordinate points of the drone in the flight area according to the flight mission of the drone, obtain predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of the three-dimensional coordinate points, construct an LDPC coding coefficient comparison table, and obtain initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the drone according to the predicted physical environment data, the transmission distance and the LDPC coding coefficient comparison table;

[0085] The physical environment detection module is used to perform physical environment detection on 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 results;

[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 feed it back to the drone, and when the physical environment detection result meets the requirements, perform channel detection and provide feedback to the drone based on 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 skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for detecting antenna signal transmission based on multi-channel anti-interference, characterized in that: The following steps are involved: Step s1: Collect multi-source heterogeneous data sent by the UAV to the ground receiving end, mark the collection time, and set the collection cycle, wherein 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 three-dimensional coordinate point time series sequence 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 sequence, construct an LDPC coding coefficient comparison table, and obtain the initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV according to the predicted physical environment data, transmission distance and LDPC coding coefficient comparison 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 UAV in real time according to the physical environment detection results; Step s4: When the initial LDPC coding coefficients corresponding to different carriers are updated to new LDPC coding coefficients, the resource transmission efficiency of each carrier frequency is obtained, and the high-efficiency carrier frequency is obtained based on the resource transmission efficiency of each carrier frequency and fed back to the UAV. When the physical environment detection results meet the requirements, channel detection is performed, and feedback is given to the UAV based on the channel detection results.

2. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 1 is characterized in that: According to the flight mission of the UAV, a time series of three-dimensional coordinate points of the UAV in the flight area is obtained, predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of three-dimensional coordinate points are obtained, and an LDPC coding coefficient comparison table is constructed. According to the predicted physical environment data, transmission distance and LDPC coding coefficient comparison table, the process of obtaining initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the UAV includes: Construct a three-dimensional coordinate system of the flight area, obtain the flight route trajectory and trajectory timestamp of the drone in the flight mission, obtain the three-dimensional coordinate point time series sequence 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 three-dimensional coordinate point time series sequence according to the physical environment prediction model, obtain the three-dimensional coordinate point of the ground receiving end in the three-dimensional coordinate system, obtain the Euclidean distance between each three-dimensional coordinate point in the three-dimensional coordinate point time series sequence 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; When the drone reaches a certain three-dimensional coordinate point of the flight trajectory, 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 are obtained, and 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 are marked as a predicted physical environment sequence of the certain three-dimensional coordinate point, and so on, to obtain the predicted physical environment sequence of each three-dimensional coordinate point of the flight trajectory; 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.

3. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 2 is characterized in that: The process of constructing the LDPC coding coefficient comparison table includes: 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, and a UAV is used to send simulated training sequences corresponding to different LDPC coding parameters to a ground receiving end through different carrier frequencies under different transmission distances and physical environment data sequence conditions through a simulated channel. A bit error rate detection is performed on the simulated training sequences corresponding to different LDPC coding parameters with different carrier frequencies received by the ground receiving end, and the bit error rates corresponding to the simulated training sequences corresponding to different LDPC coding parameters with 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 a preset bit error rate threshold range are screened out, and the simulated training sequences are marked as qualified simulated training sequences; An LDPC coding coefficient comparison table is constructed according to the LDPC coding parameters, transmission distances, physical environment data sequences and carrier frequencies corresponding to several qualified simulated training sequences. The LDPC coding coefficient comparison table includes LDPC coding parameters corresponding to different carrier frequencies under different physical environment data sequences and transmission distances.

4. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 3 is 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 drone in real time according to the physical environment detection results includes: When the ground receiving end receives the multi-source heterogeneous data sent by the UAV, the preset training sequence, baseband signal, physical environment data and three-dimensional coordinate points in the multi-source heterogeneous data are extracted to obtain the physical environment data sequence of the three-dimensional coordinate points, and the physical environment data sequence is compared with the predicted physical environment data sequence of the three-dimensional coordinate points for similarity 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, the new LDPC coding coefficients corresponding to different carrier frequencies are obtained according to the physical environment data sequence corresponding to the three-dimensional coordinate points, the transmission distance and the LDPC coding coefficient comparison table, and the coding coefficient detection is performed on the new LDPC coding coefficients corresponding to different carriers, and the UAV 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 UAV continues to use the initial LDPC coding coefficients corresponding to different carrier frequencies, and performs channel detection, and the UAV is fed back according to the channel detection result.

5. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 4 is 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, the multi-source heterogeneous data received by the ground receiving end are analyzed according to the new LDPC coding coefficients corresponding to different carrier frequencies, and the coded data corresponding to the multi-source heterogeneous data after being encoded by the new LDPC coding coefficients corresponding to different carrier frequencies is obtained, and the occupied bandwidth corresponding to the coded data is obtained, and the occupied bandwidth corresponding to the different carrier frequencies is determined according to the occupied bandwidth corresponding to the coded data, and the allocated bandwidth corresponding to each carrier frequency in each channel is obtained. According to the allocated bandwidth corresponding to each carrier frequency in each channel, the sum of the allocated bandwidths of each carrier frequency is obtained, and according to the sum of the allocated bandwidths of each carrier frequency and the occupied bandwidth corresponding to each carrier frequency, the resource transmission efficiency of each carrier frequency is obtained.

6. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 5, characterized in that: The process of obtaining a high-efficiency carrier frequency based on the resource transmission efficiency of each carrier frequency and feeding it back to the drone includes: Sort each carrier frequency in order according to its resource transmission efficiency, 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 so, mark the first carrier frequency as a high-efficiency carrier frequency and feed it back 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 sum of the allocated bandwidths of the first carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the sum of the allocated bandwidths corresponding to the second carrier frequencies in the carrier frequency queue, and determine whether the sum of the allocated bandwidths corresponding to the second carrier frequencies 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 feed them back to the drone. If it is not greater than or equal to, obtain the total bandwidth difference between the bandwidth to be modulated and the allocated bandwidth corresponding to the second carrier frequency, mark the bandwidth difference as the bandwidth to be modulated, obtain the sum of the allocated bandwidths corresponding to the second-second carrier frequencies in the carrier frequency queue, and determine whether the sum of the allocated bandwidths corresponding to the second-second carrier frequencies is greater than or equal to the bandwidth to be modulated, and so on, until the high-efficiency carrier frequency is obtained and fed back to the drone.

7. The antenna signal transmission detection method based on multi-channel anti-interference according to claim 6 is characterized in that: When the physical environment detection results meet the requirements, channel detection is performed, and the process of providing feedback to the drone based on the channel detection results includes: The preset training sequence received by each channel of the ground terminal receiving end is compared with the preset training sequence sent by the UAV to obtain the bit error rate of each channel, and the bit error rate of each channel is compared with the preset bit error rate threshold. If the bit error rate of the channel is less than the preset bit error rate threshold, the channel is marked as an unqualified channel and fed back to the UAV.

8. An antenna signal transmission detection system based on multi-channel anti-interference, specifically applied to an antenna signal transmission detection method based on multi-channel anti-interference according to any one of claims 1 to 7, characterized in that: It includes a monitoring center, which is communicatively connected with 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 drone to the ground receiving end, mark the acquisition time, and set the acquisition cycle, wherein 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 a time series of three-dimensional coordinate points of the drone in the flight area according to the flight mission of the drone, obtain predicted physical environment data and transmission distance corresponding to each three-dimensional coordinate point in the time series of the three-dimensional coordinate points, construct an LDPC coding coefficient comparison table, and obtain initial LDPC coding coefficients corresponding to different carrier frequencies corresponding to each three-dimensional coordinate point of the drone according to the predicted physical environment data, the transmission distance and the LDPC coding coefficient comparison table; The physical environment detection module is used to perform physical environment detection on 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 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 feed it back to the drone, and when the physical environment detection result meets the requirements, perform channel detection and provide feedback to the drone based on the channel detection result.

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