Unmanned aerial vehicle real-time tracking and positioning system and method based on Beidou satellite

Abstract

The invention discloses an unmanned aerial vehicle real-time tracking and positioning system and method based on a Beidou satellite, and relates to the technical field of high-precision navigation and unmanned aerial vehicle real-time tracking and positioning, and the system comprises a receiving module which receives signals of the Beidou satellite and a global navigation satellite system in real time through an antenna, and converts and demodulates the signal frequency to obtain a pseudo range; the processing module is used for performing multi-path effect detection and preliminary correction on the pseudo-range, and further correcting and optimizing the pseudo-range after preliminary correction according to the delay effect of the ionosphere and the troposphere; according to the method, multi-path effect correction is carried out on the pseudo-range, the influence of reflection and refraction on GNSS signals is reduced, the positioning precision is remarkably improved, the error of the pseudo-range is further reduced through correction of the ionosphere and the troposphere, and therefore the precision of position calculation is improved, and the positioning real-time performance of the unmanned aerial vehicle is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of high-precision navigation and unmanned aerial vehicle real-time tracking and positioning, and in particular to a Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system and method. Background Art

[0002] In recent years, the global navigation satellite system (GNSS) technology has developed rapidly, especially the Beidou satellite navigation system (BDS), which has been increasingly widely used around the world, especially in the field of high-precision real-time positioning and tracking of drones. With the integration of Beidou and other global navigation systems (such as GPS and GLONASS), GNSS technology has been widely used in many industries, such as logistics, agricultural mapping, urban management, etc. However, in complex environments, such as urban areas with tall buildings or mountainous areas, GNSS signals are easily interfered by multipath effects, resulting in signal reflection and refraction, which in turn affects the accuracy of pseudorange. In addition, changes in the ionosphere and troposphere will also affect signal propagation, resulting in additional delays and errors in the position solution process, resulting in reduced positioning accuracy. Although the existing dual-frequency signal technology can partially reduce the impact of the ionosphere, the overall error correction effect is still limited, especially in real-time tracking, the existing system still has shortcomings in accuracy and stability.

[0003] Although the existing UAV positioning system can obtain the basic location information of the UAV through GNSS signals, it is easily affected by reflection and refraction factors in complex urban environments or other high-interference areas, resulting in multipath effects, which greatly reduces the positioning accuracy. The pseudo-range error is further increased under the influence of the ionosphere and troposphere, which reduces the accuracy of subsequent position solution. Summary of the invention

[0004] In view of the problems existing in the above-mentioned existing Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system and method, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that although the existing UAV positioning system can obtain the basic position information of the UAV through GNSS signals, it is easily affected by reflection and refraction factors in complex urban environments or other high-interference areas, resulting in multipath effects, which greatly reduces the positioning accuracy, and further increases the pseudo-range error under the influence of the ionosphere and troposphere, thereby reducing the accuracy of subsequent position solution.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a real-time tracking and positioning system for unmanned aerial vehicles based on Beidou satellites, comprising:

[0007] The receiving module receives the signals of Beidou satellite and global navigation satellite system in real time through the antenna, and converts and demodulates the signal frequency to obtain pseudo-range;

[0008] The processing module detects and preliminarily corrects the multipath effect of the pseudorange, and further corrects and optimizes the preliminarily corrected pseudorange according to the delay effect of the ionosphere and troposphere;

[0009] The position calculation module calculates the position based on the optimized pseudo-range to obtain the three-dimensional coordinates of the UAV;

[0010] The wireless communication and display module transmits data to the control center via wireless communication and displays the flight position and trajectory through a visual interface.

[0011] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system described in the present invention, the method of receiving the Beidou satellite and global navigation satellite system signals in real time through the antenna, and converting and demodulating the signal frequency to obtain the pseudo-range refers to installing a dual-frequency antenna on the unmanned aerial vehicle, receiving the dual-frequency signals of the Beidou satellite and the global navigation satellite system through the dual-frequency antenna, reducing the received dual-frequency signal frequency to the baseband frequency by a down-converter, and extracting the pseudo-random noise code, timestamp and carrier phase information in the baseband frequency by a demodulator, and calculating the signal propagation time t by the difference between the receiving time and the timestamp. pro :

[0012] t pro =t rec -t sat ,

[0013] Where, t rec Represented as the receiving time, t sat Represents the timestamp extracted for demodulation;

[0014] The calculated signal propagation time t pro Combined with the speed of light, the pseudorange is calculated:

[0015] P=c·t pro ,

[0016] Where P represents the calculated pseudorange and c represents the speed of light.

[0017] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system of the present invention, wherein: the multipath effect detection and preliminary correction of the pseudorange include:

[0018] Signal power of satellite signal received by dual-band antenna A s Sum noise power A a Calculate the signal-to-noise ratio SNR;

[0019] The normal signal-to-noise ratio threshold is set to Q. If the calculated signal-to-noise ratio SNR is less than or equal to the signal-to-noise ratio threshold Q, it indicates that the signal is a reflected signal affected by the multipath effect. If the calculated signal-to-noise ratio SNR is greater than the signal-to-noise ratio threshold Q, it indicates that the signal is a direct signal not affected by the multipath effect.

[0020] By analyzing the difference in propagation time of the reflected signal, the delay difference Δt is calculated and the pseudorange correction is performed:

[0021] Δt=t ref -t dir ,

[0022] P cor =Pc·Δt,

[0023] Where, t ref represents the arrival time of the reflected signal, t dir represents the time when the direct signal arrives, P represents the original pseudorange, and P cor represents the pseudorange after delay correction, c represents the speed of light;

[0024] By calculating the carrier phase difference between the reflected signal and the direct signal, the corrected pseudorange P cor To make further corrections:

[0025]

[0026]

[0027] In the formula, represents the carrier phase of the reflected signal, represents the carrier phase of the direct signal, P pha represents the pseudorange after phase correction, β represents the carrier wavelength, Indicates the carrier phase difference;

[0028] Calculate the weighting factor w of the satellite signal i , and optimize the further corrected pseudorange:

[0029]

[0030]

[0031] In the formula, SNR i represents the signal-to-noise ratio of the i-th satellite signal, n represents the total number of satellite signals, P ted represents the weighted pseudorange, P pha,i It represents the pseudorange of the i-th satellite after phase difference correction.

[0032] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system of the present invention, the further correction and optimization of the weighted optimized pseudorange according to the delay effect of the ionosphere and the troposphere includes:

[0033] Obtain real-time surface air pressure, temperature and humidity data through weather stations;

[0034] The minimum and maximum values ​​of pseudorange data, surface pressure data, and temperature and humidity data are found by using the minimum-maximum normalization method, and the pseudorange data, surface pressure data, and temperature and humidity data are normalized;

[0035] By using the dual-frequency signal difference, the ionospheric delay I is calculated and the pseudorange correction is performed:

[0036]

[0037] P ono =P ted -I,

[0038] Where f1 represents the frequency of the B1 band, f2 represents the frequency of the B2 band, and P B1 and P B2 P represents the pseudorange of B1 and B2 bands after phase correction, ono represents the pseudorange after ionospheric correction;

[0039] Calculate the relative geometric distance between the dual-frequency antenna position and the satellite position, and combine it with the height of the dual-frequency antenna to obtain the satellite elevation angle θ:

[0040]

[0041] Where R is the distance between the dual-frequency antenna and the satellite, h sat Indicates the altitude of the satellite, h rec Indicates the height of the dual-band antenna;

[0042] Calculation of the total tropospheric delay T using the Saastamoinen model tro And further correction of pseudorange is performed:

[0043]

[0044] P opo =P ono -T tro ,

[0045] Where, T tro represents the total tropospheric delay, B0 represents the ground pressure, T0 represents the standard temperature, h0 represents the altitude of the drone, P opo represents the pseudorange after further correction;

[0046] The pseudoranges are further optimized using a combination of narrowlane and widelane pseudoranges:

[0047]

[0048]

[0049] Where N WL and N NL represent the corrected wide lane pseudorange and narrow lane pseudorange, respectively, P ono1 and P ono2 They represent the pseudoranges of the B1 and B2 bands after ionosphere and troposphere correction, respectively;

[0050] The pseudoranges corrected by the ionosphere, troposphere, narrow lane and wide lane are weighted and fused to obtain the final pseudorange S.

[0051] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system of the present invention, wherein: the three-dimensional coordinates of the unmanned aerial vehicle obtained by position calculation based on the optimized pseudo-range include:

[0052] By integrating the optimized pseudorange S, the pseudorange equation group with the satellite position is established:

[0053]

[0054] In the formula, S i represents the optimized pseudorange of the ith satellite, (x i ,y i ,z i ) represents the known three-dimensional coordinates of the i-th satellite, (x, y, z) represents the three-dimensional coordinates of the drone to be solved, c represents the speed of light, and ∈ represents the receiver clock bias;

[0055] The pseudorange equation is solved using the least squares method, and the optimal solution is determined by minimizing the error between the pseudorange calculation value and the actual measurement value. The objective function f(x,y,z,∈) is defined as:

[0056]

[0057] In the formula, n represents the total number of satellites, S i represents the pseudorange of the i-th satellite;

[0058] By minimizing the objective function f(x,y,z,∈), we can obtain the three-dimensional coordinates (x,y,z) and clock deviation ∈ of the drone;

[0059] Set the convergence condition threshold to L, compare the objective function f(x,y,z,∈) with the convergence condition L. If the objective function f(x,y,z,∈) is less than or equal to the convergence condition, it means that the convergence condition is met and the current optimal solution is output. If the objective function f(x,y,z,∈) is greater than the convergence condition, it means that the convergence condition is not met and the iterative update continues;

[0060] The initial take-off point of the UAV is set as the reference point, and an iterative algorithm is used to iteratively update the three-dimensional coordinates (x, y, z) and clock deviation ∈ until the set convergence condition is reached. The three-dimensional coordinates (x, y, z) and clock deviation ∈ of the optimal solution are output according to the set convergence condition;

[0061] The obtained optimal solution three-dimensional coordinates (x, y, z) and clock deviation ∈ are applied to real-time tracking and positioning of UAVs.

[0062] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system described in the present invention, the data is transmitted to the control center via wireless communication, which refers to establishing a high-speed, low-latency wireless connection with the ground control center through a 5G wireless communication network, encrypting the data using AES and transmitting it to the receiving server of the ground control center via the UDP protocol, decrypting the data using the same AES key as used for encryption, and storing the decrypted data in a database.

[0063] As a preferred solution of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system described in the present invention, the display of the flight position and trajectory through a visual interface refers to starting the CesiumJS engine on the server side of the control center, and initializing the three-dimensional earth scene, loading the three-dimensional model of the earth and the three-dimensional model of the unmanned aerial vehicle into Cesium, dynamically displaying the current position of the unmanned aerial vehicle, and displaying the future flight trajectory of the unmanned aerial vehicle in the three-dimensional scene in the form of dotted lines through Cesium parsing and predicting data.

[0064] Another object of the present invention is to provide a method for real-time tracking and positioning of an unmanned aerial vehicle based on Beidou satellites, which comprises:

[0065] Receive signals from Beidou satellites and global navigation satellite systems in real time through antennas, and convert and demodulate the signal frequencies to obtain pseudoranges;

[0066] Perform multipath effect detection and preliminary correction on pseudorange, and further correct and optimize the pseudorange after preliminary correction according to the delay effect of ionosphere and troposphere;

[0067] The three-dimensional coordinates of the UAV are obtained by position calculation based on the optimized pseudo-range;

[0068] The data is transmitted to the control center via wireless communication, and the flight position and trajectory are displayed through a visual interface.

[0069] A computer device comprises: a memory and a processor; the memory stores a computer program, and the processor implements the steps of the above-mentioned Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system when executing the computer program.

[0070] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system.

[0071] The beneficial effects of the present invention are as follows: the present invention reduces the influence of reflection and refraction on GNSS signals by correcting the multipath effect of pseudorange, significantly improves the positioning accuracy, and further reduces the error of pseudorange by correcting the ionosphere and troposphere, thereby improving the accuracy of position solution, thereby significantly improving the real-time positioning of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0073] Figure 1 This is a structural diagram of the real-time tracking and positioning system for UAVs based on Beidou satellites.

[0074] Figure 2 This is a flowchart of the real-time tracking and positioning method for UAVs based on Beidou satellites. DETAILED DESCRIPTION

[0075] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0076] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0077] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0078] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system includes the following modules:

[0079] S1, receiving module, receives the signals of Beidou satellite and global navigation satellite system in real time through the antenna, and converts and demodulates the signal frequency to obtain pseudorange;

[0080] Specifically, the signals of Beidou satellite and global navigation satellite system are received in real time through the antenna, and the signal frequency is converted and demodulated to obtain the pseudo-range. A dual-frequency antenna is installed on the UAV, and the dual-frequency signals of Beidou satellite and global navigation satellite system are received through the dual-frequency antenna. The frequency of the received dual-frequency signal is reduced to the baseband frequency by a down-converter, and the pseudo-random noise code, timestamp and carrier phase information in the baseband frequency are extracted by a demodulator, and the signal propagation time t is calculated by the difference between the receiving time and the timestamp. pro :

[0081] t pro =t rec -t sat ,

[0082] Where, t rec Represented as the receiving time, t sat Represents the timestamp extracted for demodulation;

[0083] The calculated signal propagation time t pro Combined with the speed of light, the pseudorange is calculated:

[0084] P=c·t pro ,

[0085] Where P represents the calculated pseudorange and c represents the speed of light.

[0086] By receiving dual-frequency signals, the influence of the ionosphere on signal propagation can be reduced and the accuracy of pseudo-range data can be improved. At the same time, the demodulator is used to extract pseudo-random noise codes and timestamps, and the signal propagation time is accurately calculated, laying the foundation for subsequent pseudo-range calculations. And through the timestamp information extracted by the demodulator, combined with the specific time when the signal is received, the system can accurately calculate the propagation time of the signal. Combining the signal propagation time with the speed of light, the pseudo-range of the satellite signal to the drone can be calculated, and by accurately calculating the pseudo-range, the system can provide an accurate data source for subsequent multipath effect correction, ionosphere and tropospheric delay correction. Compared with the traditional single-frequency system, the dual-frequency signal processing of the present invention makes the pseudo-range data more accurate.

[0087] S2, a processing module, performs multipath effect detection and preliminary correction on the pseudorange, and further corrects and optimizes the pseudorange after preliminary correction according to the delay effect of the ionosphere and troposphere;

[0088] Specifically, the multipath effect detection and preliminary correction of pseudorange include:

[0089] Signal power of satellite signal received by dual-band antenna A s Sum noise power A a Calculate the signal-to-noise ratio SNR;

[0090]

[0091] The normal signal-to-noise ratio threshold is set as Q based on experience. If the calculated signal-to-noise ratio SNR is less than or equal to the signal-to-noise ratio threshold Q, it means that the signal is a reflected signal affected by the multipath effect. If the calculated signal-to-noise ratio SNR is greater than the signal-to-noise ratio threshold Q, it means that the signal is a direct signal not affected by the multipath effect.

[0092] By analyzing the difference in propagation time of the reflected signal, the delay difference Δt is calculated and the pseudorange correction is performed:

[0093] Δt=t ref -t dir ,

[0094] P cor =Pc·Δt,

[0095] Where, t ref represents the arrival time of the reflected signal, t dir represents the time when the direct signal arrives, P represents the original pseudorange, and P cor represents the pseudorange after delay correction, c represents the speed of light;

[0096] By calculating the carrier phase difference between the reflected signal and the direct signal, the corrected pseudorange P cor To make further corrections:

[0097]

[0098]

[0099] In the formula, represents the carrier phase of the reflected signal, represents the carrier phase of the direct signal, P pha represents the pseudorange after phase correction, β represents the carrier wavelength, Indicates the carrier phase difference;

[0100] Calculate the weighting factor w of the satellite signal i , and optimize the further corrected pseudorange:

[0101]

[0102]

[0103] In the formula, SNR i represents the signal-to-noise ratio of the i-th satellite signal, n represents the total number of satellite signals, P ted represents the weighted pseudorange, P pha,i It represents the pseudorange of the i-th satellite after phase difference correction.

[0104] Through the analysis and judgment of the signal-to-noise ratio, the present invention can effectively detect and distinguish the interference of multipath effects, so as to perform corresponding pseudorange correction. This can significantly reduce pseudorange errors and improve positioning accuracy. Through carrier phase difference correction, the influence of multipath effects and other error sources on pseudorange accuracy can be further reduced. For example, in application scenarios requiring high-precision positioning, carrier phase difference correction is an effective means of error compensation, which helps to improve the accuracy of the positioning system. By assigning different weights according to the quality of each satellite signal, the satellite with a higher signal-to-noise ratio has a greater impact on the final positioning result, thereby further improving the positioning accuracy of the overall system. Through multiple corrections and weighted optimization of pseudorange data, the system can effectively respond to positioning requirements in various complex environments and ensure the positioning accuracy of the drone.

[0105] Furthermore, the weighted optimized pseudorange is further corrected and optimized according to the delay effect of the ionosphere and the troposphere, including:

[0106] Obtain real-time surface air pressure, temperature and humidity data through weather stations;

[0107] The minimum and maximum values ​​of pseudorange data, surface pressure data, and temperature and humidity data are found by using the minimum-maximum normalization method, and the pseudorange data, surface pressure data, and temperature and humidity data are normalized;

[0108] By using the dual-frequency signal difference, the ionospheric delay I is calculated and the pseudorange correction is performed:

[0109]

[0110] P ono =P ted -I,

[0111] Where f1 represents the frequency of the B1 band, f2 represents the frequency of the B2 band, and P B1 and P B2 P represents the pseudorange of B1 and B2 bands after phase correction, ono represents the pseudorange after ionospheric correction;

[0112] Calculate the relative geometric distance between the dual-frequency antenna position and the satellite position, and combine it with the height of the dual-frequency antenna to obtain the satellite elevation angle θ:

[0113]

[0114] Where R is the distance between the dual-frequency antenna and the satellite, h sat Indicates the altitude of the satellite, h rec Indicates the height of the dual-band antenna;

[0115] Calculation of the total tropospheric delay T using the Saastamoinen model tro And further correction of pseudorange is performed:

[0116]

[0117] P opo =P ono -T tro ,

[0118] Where, T tro represents the total tropospheric delay, B0 represents the ground pressure, T0 represents the standard temperature, h0 represents the altitude of the drone, P opo represents the pseudorange after further correction;

[0119] The pseudoranges are further optimized using a combination of narrowlane and widelane pseudoranges:

[0120]

[0121]

[0122] Where N WL and N NL represent the corrected wide lane pseudorange and narrow lane pseudorange, respectively, P ono1 and P ono2 They represent the pseudoranges of the B1 and B2 bands after ionosphere and troposphere correction, respectively;

[0123] The pseudoranges corrected by the ionosphere, troposphere, narrow lane and wide lane are weighted and fused to obtain the final pseudorange S.

[0124] Through the joint correction of ionospheric and tropospheric delays, the present invention can significantly improve the accuracy of pseudo-range data, especially under high altitude and complex atmospheric conditions (such as environments with frequent weather changes), and can significantly reduce the positioning error caused by atmospheric changes. The normalization process ensures that pseudo-range data, air pressure, temperature and humidity data have the same dimension in the subsequent algorithm processing, avoiding the accuracy problem caused by data range differences. The stability and processing efficiency of the entire positioning system can be effectively improved. The positioning accuracy of satellite signals is significantly improved through multi-level pseudo-range correction technology, especially under conditions of significant multipath effects and complex meteorological conditions, which can effectively improve the real-time positioning accuracy of drones. And through layer-by-layer optimization, the accuracy of pseudo-range data is guaranteed, avoiding the influence of error accumulation on positioning accuracy. The use of narrow lane and wide lane pseudo-range combinations can provide more accurate pseudo-range data, especially in complex environments, by eliminating the influence of multipath effects and noise, enhancing the stability and accuracy of satellite signals. This enables drones to maintain high-precision positioning in high-rise building dense areas or complex terrain environments. Weighted fusion technology can greatly improve the overall accuracy of pseudo-ranges by integrating the results of each correction step, avoiding the limitations of a single correction method.

[0125] S3, position calculation module, calculates the position based on the optimized pseudo-range to obtain the three-dimensional coordinates of the UAV;

[0126] Specifically, the three-dimensional coordinates of the drone are obtained by position calculation based on the optimized pseudo-range, including:

[0127] By integrating the optimized pseudorange S, the pseudorange equation group with the satellite position is established:

[0128]

[0129] In the formula, S i represents the optimized pseudorange of the ith satellite, (x i ,y i ,z i ) represents the known three-dimensional coordinates of the i-th satellite, (x, y, z) represents the three-dimensional coordinates of the drone to be solved, c represents the speed of light, and ∈ represents the receiver clock bias;

[0130] The pseudorange equation is solved using the least squares method, and the optimal solution is determined by minimizing the error between the pseudorange calculation value and the actual measurement value. The objective function f(x,y,z,∈) is defined as:

[0131]

[0132] In the formula, n represents the total number of satellites, S i represents the pseudorange of the i-th satellite;

[0133] By minimizing the objective function f(x,y,z,∈), we can obtain the three-dimensional coordinates (x,y,z) and clock deviation ∈ of the drone;

[0134] According to the accuracy requirements and experience, the convergence condition threshold is set to L, and the objective function f(x,y,z,∈) is compared with the convergence condition L. If the objective function f(x,y,z,∈) is less than or equal to the convergence condition, it means that the convergence condition is met and the current optimal solution is output. If the objective function f(x,y,z,∈) is greater than the convergence condition, it means that the convergence condition is not met and the iterative update continues;

[0135] The initial take-off point of the UAV is set as the reference point, and an iterative algorithm is used to iteratively update the three-dimensional coordinates (x, y, z) and clock deviation ∈ until the set convergence condition is reached. The three-dimensional coordinates (x, y, z) and clock deviation ∈ of the optimal solution are output according to the set convergence condition;

[0136] The obtained optimal solution three-dimensional coordinates (x, y, z) and clock deviation ∈ are applied to real-time tracking and positioning of UAVs.

[0137] Through the construction of pseudo-range equations and iterative solution of the least squares method, the present invention can accurately determine the three-dimensional position of the UAV, especially by minimizing the error to achieve high-precision positioning. At the same time, the solution of the clock deviation also effectively solves the problem of the receiver clock and the satellite clock being out of sync, improving the overall reliability of the positioning system. And the use of the least squares method can ensure that the system obtains the position of the UAV in the fastest and most accurate way. The setting of the convergence condition ensures that the algorithm will not fall into an infinite loop or lengthy calculation, and can efficiently process a large amount of satellite data to ensure real-time performance.

[0138] S4, wireless communication and display module, transmits data to the control center through wireless communication, and displays the flight position and trajectory through a visual interface;

[0139] Specifically, transmitting data to the control center via wireless communication means establishing a high-speed, low-latency wireless connection with the ground control center through the 5G wireless communication network, encrypting the data using AES and transmitting it to the receiving server of the ground control center via the UDP protocol, decrypting the data using the same AES key as used for encryption, and storing the decrypted data in a database.

[0140] By using 5G wireless communication, the present invention can ensure that the drone transmits data seamlessly during flight. Even in high-speed movement and long-distance operation, the ground control center can still receive and process the predicted data of the drone in real time, ensuring the timeliness and accuracy of the drone control. Thereby providing stable communication support for the drone to perform high-precision tasks (such as logistics, inspection, rescue, etc.). Through AES encryption, the present invention achieves efficient security protection and ensures the security of data transmission between the drone and the ground control center. In complex or sensitive mission scenarios (such as drone military applications or high-value logistics tasks), the confidentiality of data is crucial. The AES encryption mechanism can effectively prevent data leakage and tampering, and enhance the security and reliability of the system. The use of the UDP protocol greatly reduces the delay in data transmission and ensures the rapid transmission of real-time data of the drone. Especially in the 5G network environment, the UDP protocol can further play the low-latency characteristics, ensuring that the ground control center can quickly receive the real-time data of the drone and respond. By decrypting and storing in the ground control center, it can be ensured that the data transmitted by the drone can be safely and quickly processed and saved.

[0141] Furthermore, displaying the flight position and trajectory through a visual interface means starting the CesiumJS engine on the server side of the control center, and initializing the three-dimensional earth scene, loading the three-dimensional model of the earth and the three-dimensional model of the drone into Cesium, dynamically displaying the current position of the drone, and displaying the future flight trajectory of the drone in the three-dimensional scene in the form of dotted lines through Cesium parsing and predicting data.

[0142] The use of the CesiumJS engine can greatly improve the scalability and visualization of the system. In addition, CesiumJS can also load various geographic data layers, such as elevation, terrain, roads and other information, to provide more detailed environmental data support for drone flights. The real-time dynamic update of the drone's position allows operators to clearly understand the current flight status and position of the drone, especially when the drone is in a long-distance flight or in a complex environment, real-time monitoring becomes essential. The dynamic display in the three-dimensional scene allows the controller to grasp the flight information of the drone in a more intuitive way in real time, so as to make corresponding operational decisions. The display of future flight trajectories provides higher predictability for drone flights, especially in complex flight missions, operators can make adjustments in advance according to the predicted path to avoid potential flight risks. Through the display of the three-dimensional scene, the controller can monitor the flight status of the drone more flexibly and comprehensively.

[0143] Example 2, reference Figure 2 , which is the second embodiment of the present invention, and which is different from the previous embodiment, provides a method for real-time tracking and positioning of a UAV based on Beidou satellites, comprising:

[0144] Receive signals from Beidou satellites and global navigation satellite systems in real time through antennas, and convert and demodulate the signal frequencies to obtain pseudoranges;

[0145] Perform multipath effect detection and preliminary correction on pseudorange, and further correct and optimize the pseudorange after preliminary correction according to the delay effect of ionosphere and troposphere;

[0146] The three-dimensional coordinates of the UAV are obtained by position calculation based on the optimized pseudo-range;

[0147] The data is transmitted to the control center via wireless communication, and the flight position and trajectory are displayed through a visual interface.

[0148] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0149] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0150] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0151] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0152] It should be noted that the above embodiments are only used to illustrate the technical solutions 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A real-time tracking and positioning system for unmanned aerial vehicles based on Beidou satellites, characterized in that: include, The receiving module receives the signals of Beidou satellite and global navigation satellite system in real time through the antenna, and converts and demodulates the signal frequency to obtain pseudo-range; The processing module detects and preliminarily corrects the multipath effect of the pseudorange, and further corrects and optimizes the preliminarily corrected pseudorange according to the delay effect of the ionosphere and troposphere; The position calculation module calculates the position based on the optimized pseudo-range to obtain the three-dimensional coordinates of the UAV; The wireless communication and display module transmits data to the control center via wireless communication and displays the flight position and trajectory through a visual interface.

2. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 1, characterized in that: The method of receiving the signals of Beidou satellite and global navigation satellite system in real time through the antenna, converting and demodulating the signal frequency to obtain the pseudo-range refers to installing a dual-frequency antenna on the UAV, receiving the dual-frequency signals of Beidou satellite and global navigation satellite system through the dual-frequency antenna, reducing the received dual-frequency signal frequency to the baseband frequency by a down-converter, extracting the pseudo-random noise code, timestamp and carrier phase information in the baseband frequency by a demodulator, and calculating the signal propagation time t by the difference between the receiving time and the timestamp. pro : t pro =t rec -t sat , Where, t rec Represented as the receiving time, t sat Represents the timestamp extracted for demodulation; The calculated signal propagation time t pro Combined with the speed of light, the pseudorange is calculated: P=c·t pro , Where P represents the calculated pseudorange and c represents the speed of light.

3. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 2, characterized in that: The multipath effect detection and preliminary correction of the pseudorange include: Signal power of satellite signal received by dual-band antenna A s Sum noise power A a Calculate the signal-to-noise ratio SNR; The normal signal-to-noise ratio threshold is set to Q. If the calculated signal-to-noise ratio SNR is less than or equal to the signal-to-noise ratio threshold Q, it indicates that the signal is a reflected signal affected by the multipath effect. If the calculated signal-to-noise ratio SNR is greater than the signal-to-noise ratio threshold Q, it indicates that the signal is a direct signal not affected by the multipath effect. By analyzing the difference in propagation time of the reflected signal, the delay difference Δt is calculated and the pseudorange correction is performed: Δt=t ref -t dir , P cor =Pc·Δt, Where, t ref represents the arrival time of the reflected signal, t dir represents the time when the direct signal arrives, P represents the original pseudorange, and P cor represents the pseudorange after delay correction, c represents the speed of light; By calculating the carrier phase difference between the reflected signal and the direct signal, the corrected pseudorange P cor To make further corrections: In the formula, represents the carrier phase of the reflected signal, represents the carrier phase of the direct signal, P pha represents the pseudorange after phase correction, β represents the carrier wavelength, Indicates the carrier phase difference; Calculate the weighting factor w of the satellite signal i , and optimize the further corrected pseudorange: In the formula, SNR i represents the signal-to-noise ratio of the i-th satellite signal, n represents the total number of satellite signals, P ted represents the weighted pseudorange, P pha，i It represents the pseudorange of the i-th satellite after phase difference correction.

4. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 3, characterized in that: The further correction and optimization of the weighted optimized pseudorange according to the delay effect of the ionosphere and the troposphere includes: Obtain real-time surface air pressure, temperature and humidity data through weather stations; The minimum and maximum values ​​of the pseudorange data, surface pressure data, and temperature and humidity data are found by using the minimum-maximum normalization method, and the pseudorange data, surface pressure data, and temperature and humidity data are normalized; By using the dual-frequency signal difference, the ionospheric delay I is calculated and the pseudorange correction is performed: P ono =P ted -I, Where f1 represents the frequency of the B1 band, f2 represents the frequency of the B2 band, and P B1 and P B2 P represents the pseudorange of B1 and B2 bands after phase correction, ono represents the pseudorange after ionospheric correction; Calculate the relative geometric distance between the dual-frequency antenna position and the satellite position, and combine it with the height of the dual-frequency antenna to obtain the satellite elevation angle θ: Where R is the distance between the dual-frequency antenna and the satellite, h sat Indicates the altitude of the satellite, h rec Indicates the height of the dual-band antenna; Calculation of the total tropospheric delay T using the Saastamoinen model tro And further correction of pseudorange is performed: P opo =P ono -T tro , Where, T tro represents the total tropospheric delay, B0 represents the ground pressure, T0 represents the standard temperature, h0 represents the altitude of the drone, P opo represents the pseudorange after further correction; The pseudoranges are further optimized using a combination of narrowlane and widelane pseudoranges: Where N WL and N NL represent the corrected wide lane pseudorange and narrow lane pseudorange, respectively, P ono1 and P ono2 They represent the pseudoranges of the B1 and B2 bands after ionosphere and troposphere correction, respectively; The pseudoranges corrected by the ionosphere, troposphere, narrow lane and wide lane are weighted and fused to obtain the final pseudorange S.

5. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 4, characterized in that: The three-dimensional coordinates of the UAV obtained by position calculation based on the optimized pseudo-range include: By integrating the optimized pseudorange S, the pseudorange equation group with the satellite position is established: In the formula, S i represents the optimized pseudorange of the ith satellite, (x i ,y i , z i ) represents the known three-dimensional coordinates of the i-th satellite, (x, y, z) represents the three-dimensional coordinates of the drone to be solved, c represents the speed of light, and ∈ represents the receiver clock bias; The pseudorange equation is solved using the least squares method, and the optimal solution is determined by minimizing the error between the pseudorange calculation value and the actual measurement value. The objective function f(x, y, z, ∈) is defined as: In the formula, n represents the total number of satellites, S i represents the pseudorange of the i-th satellite; By minimizing the objective function f(x, y, z,∈), we can obtain the three-dimensional coordinates (x, y, z) and clock deviation ∈ of the drone; Set the convergence condition threshold to L, compare the objective function f(x, y, z, ∈) with the convergence condition L. If the objective function f(x, y, z, ∈) is less than or equal to the convergence condition, it means that the convergence condition is met and the current optimal solution is output. If the objective function f(x, y, z, ∈) is greater than the convergence condition, it means that the convergence condition is not met and the iterative update continues; The initial take-off point of the UAV is set as the reference point, and an iterative algorithm is used to iteratively update the three-dimensional coordinates (x, y, z) and clock deviation ∈ until the set convergence condition is reached. The three-dimensional coordinates (x, y, z) and clock deviation ∈ of the optimal solution are output according to the set convergence condition; The obtained optimal solution three-dimensional coordinates (x, y, z) and clock deviation ∈ are applied to real-time tracking and positioning of UAVs.

6. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 5, characterized in that: The transmitting of data to the control center via wireless communication refers to establishing a high-speed, low-latency wireless connection with the ground control center via the 5G wireless communication network, encrypting the data using AES and transmitting it to the receiving server of the ground control center via the UDP protocol, decrypting the data using the same AES key as used for encryption, and storing the decrypted data in a database.

7. The Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system as claimed in claim 6, characterized in that: Displaying the flight position and trajectory through a visual interface refers to starting the CesiumJS engine on the server side of the control center, and initializing the three-dimensional earth scene, loading the three-dimensional model of the earth and the three-dimensional model of the drone into Cesium, dynamically displaying the current position of the drone, parsing the predicted data through Cesium, and displaying the future flight trajectory of the drone in the three-dimensional scene in the form of dotted lines.

8. A Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning method based on the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system according to any one of claims 1 to 7, characterized in that: include, Receive signals from Beidou satellites and global navigation satellite systems in real time through antennas, and convert and demodulate the signal frequencies to obtain pseudoranges; Perform multipath effect detection and preliminary correction on pseudorange, and further correct and optimize the pseudorange after preliminary correction according to the delay effect of ionosphere and troposphere; The three-dimensional coordinates of the UAV are obtained by position calculation based on the optimized pseudo-range; The data is transmitted to the control center via wireless communication, and the flight position and trajectory are displayed through a visual interface.

9. A computer device comprising: Memory and processor; The memory stores a computer program, characterized in that: when the processor executes the computer program, the steps of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system described in any one of claims 1 to 7 are implemented.

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