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

Abstract

The application discloses a Beidou satellite-based unmanned plane real-time tracking and positioning system and method, relates to the technical field of high-precision navigation and unmanned plane real-time tracking and positioning, and comprises a receiving module, which receives signals of Beidou satellites and global navigation satellite systems in real time through an antenna, converts and demodulates the signals to obtain pseudo ranges; a processing module, which detects and preliminarily corrects the pseudo ranges, and further corrects and optimizes the preliminarily corrected pseudo ranges according to delay effects of ionospheres and tropospheres; the application corrects the pseudo ranges according to the multipath effect, reduces the influence of reflection and refraction on GNSS signals, significantly improves the positioning precision, further reduces the pseudo range error through the correction of the ionosphere and the troposphere, thereby improving the position solution precision, and significantly improving the positioning real-time performance of the unmanned plane.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of high-precision navigation and real-time tracking and positioning of unmanned aerial vehicles, and in particular to a real-time tracking and positioning system and method for unmanned aerial vehicles based on Beidou satellites. BACKGROUND

[0002] In recent years, the global navigation satellite system (GNSS) technology has developed rapidly, and the application of the Beidou satellite navigation system (BDS) has become increasingly widespread around the world, especially in the field of high-precision real-time positioning and tracking of unmanned aerial vehicles. With the integration of Beidou and other global navigation systems (such as GPS and GLONASS), GNSS technology has been widely applied in various industries, such as logistics, agricultural surveying and mapping, and urban management. However, in complex environments, such as urban areas with high-rise buildings or mountainous regions, GNSS signals are easily affected by multipath effects, leading to signal reflection and refraction, which in turn affects the accuracy of pseudorange. In addition, changes in the ionosphere and troposphere also affect signal propagation, resulting in additional delays and errors in the position solution process, which leads to a decrease in positioning accuracy. Although 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, existing systems still have deficiencies in terms of accuracy and stability.

[0003] Although existing unmanned aerial vehicle positioning systems can obtain basic position information of the unmanned aerial vehicle through GNSS signals, in complex urban environments or other high-interference areas, they are easily affected by reflection and refraction factors, leading to multipath effects, which significantly reduces the positioning accuracy. Furthermore, under the influence of the ionosphere and troposphere, pseudorange errors are further increased, which reduces the accuracy of subsequent position solutions. SUMMARY

[0004] In view of the problems existing in the above-mentioned real-time tracking and positioning system and method for unmanned aerial vehicles based on Beidou satellites, the present application is proposed.

[0005] Therefore, the problem to be solved by the present application is that although existing unmanned aerial vehicle positioning systems can obtain basic position information of the unmanned aerial vehicle through GNSS signals, in complex urban environments or other high-interference areas, they are easily affected by reflection and refraction factors, leading to multipath effects, which significantly reduces the positioning accuracy. Furthermore, under the influence of the ionosphere and troposphere, pseudorange errors are further increased, which reduces the accuracy of subsequent position solutions.

[0006] To solve the above technical problems, the present application provides the following technical solution: a real-time tracking and positioning system for unmanned aerial vehicles based on Beidou satellites, comprising,

[0007] a receiving module for receiving signals from Beidou satellites and global navigation satellite systems in real time through an antenna, and converting and demodulating the signal frequency to obtain pseudorange;

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

[0009] The position solving module solves the position based on the optimized pseudo-range to obtain the three-dimensional coordinates of the unmanned aerial vehicle;

[0010] The 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.

[0011] As a preferred scheme of the unmanned aerial vehicle real-time tracking and positioning system based on Beidou satellite, the antenna is used to receive the signals of the Beidou satellite and the global navigation satellite system in real time, the signal frequency is converted and demodulated to obtain the pseudo-range, the double-frequency antenna is installed on the unmanned aerial vehicle, the double-frequency signals of the Beidou satellite and the global navigation satellite system are received through the double-frequency antenna, the received double-frequency signal frequency is reduced to the baseband frequency by using the frequency downconverter, and the pseudo-random noise code, the timestamp and the carrier phase information in the baseband frequency are extracted by using the demodulator, the signal propagation time t is calculated according to the difference between the receiving time and the timestamp pro :

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

[0013] In the formula, t rec represents the receiving time, and t sat represents the timestamp extracted by demodulation.

[0014] The calculated signal propagation time t pro is combined with the speed of light to calculate the pseudo-range:

[0015] P=c·t pro ,

[0016] In the formula, P represents the calculated pseudo-range, and c represents the speed of light.

[0017] As a preferred scheme of the unmanned aerial vehicle real-time tracking and positioning system based on Beidou satellite, the multipath effect detection and preliminary correction of the pseudo-range include,

[0018] The signal power A s and the noise power A a of the satellite signal received by the double-frequency antenna are calculated to obtain the signal-to-noise ratio SNR.

[0019] The normal signal-to-noise ratio threshold is set as 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 the propagation time of the reflected signal, the time delay difference Δt is calculated and the pseudo-range is corrected:

[0021] Δt = t ref -t dir ,

[0022] P cor = P - c · Δt,

[0023] In the formula, t ref represents the arrival time of the reflected signal, t dir represents the arrival time of the direct signal, P represents the original pseudo-range, P cor represents the pseudo-range after time delay correction, and c represents the speed of light.

[0024] By calculating the carrier phase difference between the reflected signal and the direct signal, the corrected pseudo-range P cor is further corrected:

[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 pseudo-range after phase correction, and β represents the carrier wavelength, represents the carrier phase difference.

[0028] The weighting factor w i of the satellite signal is calculated, and the further corrected pseudo-range is optimized:

[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 pseudo-range, P pha,i represents the pseudo-range of the i-th satellite after phase difference correction.

[0032] As a preferred scheme of the Beidou satellite-based unmanned aerial vehicle real-time tracking and positioning system, wherein: the further correction and optimization of the weighted and optimized pseudo-range according to the delay effect of ionosphere and troposphere comprises,

[0033] Real-time surface air pressure and temperature and humidity data are obtained through a weather station;

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

[0035] The ionospheric delay I is calculated by using the difference between the dual-frequency signals, and the pseudo-range is corrected:

[0036]

[0037] P ono = P ted -I,

[0038] In the formula, f1 represents the frequency of B1 band, f2 represents the frequency of B2 band, P B1 and P B2 represent the pseudo-range of B1 and B2 bands after phase correction, P ono represents the pseudo-range after ionospheric correction;

[0039] The relative geometric distance between the dual-frequency antenna position and the satellite position is calculated, and the satellite elevation angle θ is obtained in combination with the height of the dual-frequency antenna:

[0040]

[0041] In the formula, R represents the distance between the dual-frequency antenna and the satellite, h sat represents the height of the satellite, and h rec represents the height of the dual-frequency antenna;

[0042] The total tropospheric delay T tro is calculated by using the Saastamoinen model, and the pseudo-range is further corrected:

[0043]

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

[0045] In the formula, T tro represents the total tropospheric delay, B0 represents the ground air pressure, T0 represents the standard temperature, h0 represents the height of the unmanned aerial vehicle, and P opo represents the pseudo-range after further correction;

[0046] The pseudo-range is further optimized using the combination of narrow-lane and wide-lane pseudo-range:

[0047]

[0048]

[0049] In the formula, N WL and N NL respectively represent the corrected wide-lane pseudo-range and narrow-lane pseudo-range, P ono1 and P ono2 respectively represent the pseudo-range of B1 and B2 bands after ionospheric and tropospheric correction;

[0050] The ionospheric, tropospheric, narrow-lane and wide-lane corrected pseudo-range is weighted and fused to obtain the final pseudo-range S.

[0051] As a preferred scheme of the unmanned aerial vehicle real-time tracking and positioning system based on Beidou satellite, wherein the position solution based on the optimized pseudo-range to obtain the three-dimensional coordinates of the unmanned aerial vehicle comprises,

[0052] The pseudo-range equation with the satellite position is established by fusing the optimized pseudo-range S:

[0053]

[0054] In the formula, S i represents the optimized pseudo-range of the i-th 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 unmanned aerial vehicle to be solved, c represents the speed of light, and ∈ represents the receiver clock bias.

[0055] The pseudo-range equation is solved using the least square method, and the best solution is determined by minimizing the error between the pseudo-range calculation value and the actual measured value, and the objective function f(x, y, z, ∈) is defined:

[0056]

[0057] In the formula, n represents the total number of satellites, S i represents the pseudo-range of the i-th satellite.

[0058] The three-dimensional coordinates (x, y, z) of the unmanned aerial vehicle and the clock bias ∈ are obtained by minimizing the objective function f(x, y, z, ∈);

[0059] Set the convergence condition threshold as L, compare the target function f(x, y, z, ∈) with the convergence condition L, if the target function f(x, y, z, ∈) is less than or equal to the convergence condition, it indicates that the convergence condition is reached and the current optimal solution is output, if the target function f(x, y, z, ∈) is greater than the convergence condition, it indicates that the convergence condition is not reached, and the iteration update is continued;

[0060] By setting the initial take-off point of the unmanned aerial vehicle as the reference point, and using the iterative algorithm to iteratively update the three-dimensional coordinates (x, y, z) and clock deviation ∈ until the set convergence condition is reached, the optimal solution of the three-dimensional coordinates (x, y, z) and clock deviation ∈ is output according to the set convergence condition;

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

[0062] As a preferred scheme of the unmanned aerial vehicle real-time tracking and positioning system based on Beidou satellite, wherein: the data is transmitted to the control center through the wireless communication mode, that is, a high-speed, low-delay wireless connection is established with the ground control center through a 5G wireless communication network, the data is encrypted using AES and transmitted to the receiving server of the ground control center through the UDP protocol, the data is decrypted using the same AES key as the encryption, and the decrypted data is stored in the database.

[0063] As a preferred scheme of the unmanned aerial vehicle real-time tracking and positioning system based on Beidou satellite, wherein: the flight position and trajectory are displayed through a visual interface, that is, the CesiumJS engine of the control center server is started, and the three-dimensional model of the earth and the three-dimensional model of the unmanned aerial vehicle are loaded into Cesium by initializing a three-dimensional earth scene, the current position of the unmanned aerial vehicle is dynamically displayed, and the future flight trajectory of the unmanned aerial vehicle is displayed in the three-dimensional scene in the form of a dashed line by analyzing the prediction data through Cesium.

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

[0065] The signals of Beidou satellites and global navigation satellite systems are received in real time through an antenna, and the signal frequency is converted and demodulated to obtain pseudo-range;

[0066] The pseudo-range is detected for multipath effect and preliminarily corrected, and the preliminarily corrected pseudo-range is further corrected and optimized according to the delay effect of ionosphere and troposphere;

[0067] The three-dimensional coordinates of the unmanned aerial vehicle are obtained by position solution based on the optimized pseudo-range;

[0068] The data is transmitted to the control center through wireless communication mode, 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 positioning system when executing the computer program.

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

[0071] The present application has the beneficial effects that: the present application corrects the multipath effect of pseudo-range, reduces the influence of reflection and refraction on GNSS signal, significantly improves the positioning accuracy, and further reduces the error of pseudo-range through the correction of ionosphere and troposphere, thereby improving the accuracy of position solution, and significantly improving the positioning real-time performance of the unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0073] Figure 1 It is a structural schematic diagram of the Beidou satellite-based unmanned aerial vehicle real-time tracking positioning system.

[0074] Figure 2 It is a flowchart of the Beidou satellite-based unmanned aerial vehicle real-time tracking positioning method. DETAILED DESCRIPTION

[0075] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0076] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the concept of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0077] Second, the "one embodiment" or "an embodiment" appearing in the specification herein indicates that a specific feature, structure, or characteristic can be included in at least one implementation of the present application. The "in one embodiment" appearing in different places in the specification herein does not all refer to the same embodiment, nor does it mean that the embodiments are mutually exclusive or alternative to each other.

[0078] Embodiment 1, Reference Figure 1 As a first embodiment of the present application, the embodiment 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 comprises the following modules:

[0079] S1, receiving module, receiving signals of Beidou satellite and global navigation satellite system in real time through antenna, and converting and demodulating signal frequency to obtain pseudo range;

[0080] Specifically, the pseudo range is obtained by receiving signals of Beidou satellite and global navigation satellite system in real time through antenna, and converting and demodulating signal frequency. Specifically, a dual-frequency antenna is installed on the unmanned aerial vehicle, 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 signals is reduced to baseband frequency by using a frequency downconverter, and the pseudo-random noise code, timestamp and carrier phase information in the baseband frequency are extracted by using a demodulator. The signal propagation time t pro is calculated by the difference between the receiving time and the timestamp.

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

[0082] In the formula, t rec represents the receiving time, and t sat represents the timestamp extracted by demodulation.

[0083] The calculated signal propagation time t pro is combined with the speed of light to calculate the pseudo range:

[0084] P = c·t pro ,

[0085] In the formula, P represents the calculated pseudo range, and c represents the speed of light.

[0086] Through the double frequency signal receiving, the influence of ionosphere on signal propagation can be reduced, and the precision of pseudo-range data is improved. Meanwhile, the pseudo-random noise code and time stamp are extracted by the demodulator, and the signal propagation time is accurately calculated, which lays a foundation for subsequent pseudo-range calculation. Through the time stamp information extracted by the demodulator and the specific time of receiving the signal, the system can accurately calculate the signal propagation time. The pseudo-range of the satellite signal to the unmanned aerial vehicle can be calculated by combining the signal propagation time with the speed of light. Through the accurate calculation of the pseudo-range, the system can provide accurate data source for subsequent multi-path effect correction, ionosphere and troposphere delay correction. Compared with the traditional single frequency system, the double frequency signal processing of the present application makes the pseudo-range data more accurate.

[0087] S2, a processing module, performs multi-path effect detection and preliminary correction on the pseudo-range, and further corrects and optimizes the pseudo-range after preliminary correction according to the delay effect of ionosphere and troposphere;

[0088] Specifically, the multi-path effect detection and preliminary correction on the pseudo-range include,

[0089] The signal power A of the satellite signal received by the double frequency antenna s and the noise power A a The signal-to-noise ratio SNR is calculated.

[0090]

[0091] According to experience, the normal signal-to-noise ratio threshold Q is set. 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 multi-path 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 multi-path effect.

[0092] By analyzing the difference of the propagation time of the reflected signal, the time delay difference At is calculated and the pseudo-range is corrected:

[0093] At = t ref -t dir ,

[0094] P cor = P-c·At,

[0095] In the formula, t ref represents the arrival time of the reflected signal, t dir represents the arrival time of the direct signal, P represents the original pseudo-range, P cor represents the pseudo-range after time delay correction, and c represents the speed of light.

[0096] By calculating the carrier phase difference between the reflected signal and the direct signal, the corrected pseudo-range P cor is further corrected:

[0097]

[0098]

[0099] In the formula, denotes the carrier phase of the reflected signal, denotes the carrier phase of the direct signal, P pha denotes the pseudo-range after phase correction, and β denotes the carrier wavelength, denotes the carrier phase difference;

[0100] The weighted factor w of the satellite signal is calculated i , and the pseudo-range after further correction is optimized:

[0101]

[0102]

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

[0104] Through the analysis and judgment of the signal-to-noise ratio, the present application can effectively detect and distinguish the multipath effect interference, and thus perform corresponding pseudo-range correction. This can significantly reduce the pseudo-range error and improve the positioning accuracy. Through carrier phase difference correction, the influence of multipath effect and other error sources on the pseudo-range accuracy can be further reduced, for example, in high-precision positioning demand application scenarios, carrier phase difference correction is an effective error compensation means, which helps to improve the accuracy of the positioning system. By giving different weights according to the quality of each satellite signal, the satellite with higher signal-to-noise ratio has greater influence on the final positioning result, thereby further improving the positioning accuracy of the overall system. Through multiple corrections and weighted optimization of the pseudo-range data, the system can effectively cope with positioning requirements in various complex environments and ensure the positioning accuracy of the unmanned aerial vehicle.

[0105] Further, the further correction and optimization of the weighted and optimized pseudo-range according to the delay effect of the ionosphere and the troposphere include,

[0106] Real-time ground surface pressure and temperature and humidity data are obtained through a weather station;

[0107] The minimum and maximum values in the pseudo-range data, ground surface pressure data, and temperature and humidity data are found by using the minimum-maximum normalization method, and the pseudo-range data, ground surface pressure data, and temperature and humidity data are normalized;

[0108] The ionospheric delay I is calculated by the difference between the two frequencies and the pseudorange is corrected:

[0109]

[0110] P ono = P ted - I,

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

[0112] The relative geometric distance between the dual-frequency antenna position and the satellite position is calculated, and combined with the height of the dual-frequency antenna, the satellite elevation angle θ is obtained:

[0113]

[0114] where R represents the distance between the dual-frequency antenna and the satellite, h sat represents the height of the satellite, and h rec represents the height of the dual-frequency antenna;

[0115] The total tropospheric delay T tro is calculated using the Saastamoinen model and the pseudorange is further corrected:

[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 height of the UAV, P opo represents the pseudorange after further correction;

[0119] The pseudorange is further optimized using the combination of narrow-lane and wide-lane 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 represent the pseudoranges of B1 and B2 bands after ionospheric and tropospheric correction, respectively;

[0123] The ionosphere, troposphere, narrow lane and wide lane correction pseudo-range is weighted and fused to obtain the final pseudo-range S.

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

[0125] S3, a position solving module, based on the optimized pseudo-range, to obtain the three-dimensional coordinates of the unmanned aerial vehicle;

[0126] Specifically, based on the optimized pseudo-range, the three-dimensional coordinates of the unmanned aerial vehicle are obtained, including,

[0127] By fusing the optimized pseudo-range S, a pseudo-range equation set with satellite positions is established:

[0128]

[0129] In the formula, S i represents the optimized pseudo-range of the i-th 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 unmanned aerial vehicle to be solved, c represents the speed of light, and ∈ represents the receiver clock bias.

[0130] The least squares method is used to solve the pseudo-range equation, and the best solution is determined by minimizing the error between the pseudo-range calculation value and the actual measured value, defining the objective function f(x, y, z, ∈):

[0131]

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

[0133] The three-dimensional coordinates (x, y, z) of the unmanned aerial vehicle and the clock deviation ∈ are obtained by minimizing the objective function f(x, y, z, ∈);

[0134] According to the accuracy requirement and experience, the convergence condition threshold L is set, 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 indicates that the convergence condition is reached and the current optimal solution is output, if the objective function f(x, y, z, ∈) is greater than the convergence condition, it indicates that the convergence condition is not reached, and the iteration update is continued;

[0135] The initial take-off point of the unmanned aerial vehicle is set as the reference point, and the iteration algorithm is used to update the three-dimensional coordinates (x, y, z) and the clock deviation ∈ until the set convergence condition is reached, and the three-dimensional coordinates (x, y, z) and the 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 the real-time tracking and positioning of the unmanned aerial vehicle.

[0137] Through the construction of the pseudo-range equation set and the iterative solution of the least square method, the three-dimensional position of the unmanned aerial vehicle can be accurately determined, especially through the minimization of 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 out of synchronization, improves the overall reliability of the positioning system. And the use of the least square method can ensure that the system obtains the position of the unmanned aerial vehicle 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, a 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, the data is transmitted to the control center through a 5G wireless communication network to establish a high-speed, low-latency wireless connection with the ground control center, the data is encrypted using AES and transmitted to the receiving server of the ground control center through the UDP protocol, the data is decrypted using the same AES key as the encryption, and the decrypted data is stored in the database.

[0140] By using 5G wireless communication, the present application can ensure seamless data transmission for the UAV 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 UAV in real time, ensuring the timeliness and accuracy of UAV control. Thus, it provides stable communication support for the UAV to perform high-precision tasks (such as logistics, inspection, rescue, etc.). Through AES encryption, the present application realizes efficient security protection, ensuring the safety of data transmission between the UAV and the ground control center. In complex or sensitive task scenarios (such as UAV military applications or high-value logistics tasks), data confidentiality is crucial. The AES encryption mechanism can effectively prevent data leakage and tampering, enhancing the security and reliability of the system. The use of UDP protocol greatly reduces the delay of data transmission, ensuring the rapid transmission of real-time data of the UAV. Especially in the 5G network environment, the UDP protocol can further exert the low-delay characteristics, ensuring that the ground control center can quickly receive the real-time data of the UAV and respond. By decryption and storage at the ground control center, it can ensure that the data transmitted by the UAV can be safely and quickly processed and saved.

[0141] Further, the visual interface displays the flight position and trajectory, which starts the CesiumJS engine of the control center server side, and loads the three-dimensional model of the earth and the three-dimensional model of the UAV into Cesium by initializing a three-dimensional earth scene, dynamically displays the current position of the UAV, and displays the future flight trajectory of the UAV in the three-dimensional scene in the form of a dashed line by analyzing the prediction data with Cesium.

[0142] Using the CesiumJS engine can greatly improve the scalability and visualization effect of the system. In addition, CesiumJS can also load various geographic data layers, such as elevation, terrain, road information, etc., to provide more detailed environmental data support for UAV flight. The dynamic update of the real-time position of the UAV can help the operator clearly understand the flight status and position of the current UAV, especially when the UAV is in long-distance flight or complex environment, real-time monitoring becomes crucial. Dynamic display in the three-dimensional scene can enable the controller to grasp the flight information of the UAV in a more intuitive way, so as to make corresponding operation decisions. The display of the future flight trajectory provides higher predictability for UAV flight, especially in complex flight tasks, the operator 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 more flexibly and comprehensively monitor the flight status of the UAV.

[0143] Embodiment 2, refer to Figure 2 For the second embodiment of the present application, this embodiment is different from the previous embodiment, and provides a Beidou satellite-based real-time tracking and positioning method for a UAV, which comprises,

[0144] The signals of Beidou satellite and global navigation satellite system are received in real time through the antenna, and the pseudo range is obtained by converting and demodulating the signal frequency;

[0145] The pseudo range is detected and preliminarily corrected for multipath effect, and the preliminarily corrected pseudo range is further corrected and optimized according to the delay effect of ionosphere and troposphere;

[0146] The three-dimensional coordinates of the unmanned aerial vehicle are obtained by position solution based on the optimized pseudo range;

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

[0148] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts that essentially contribute to the prior art or parts of the technical solutions can be embodied in the form of software products, which are stored in a storage medium and include instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and various program code storage media.

[0149] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered a list of executable instructions for implementing logic functions, which can be specifically 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 and execute instructions from an instruction execution system, device or apparatus) or in conjunction with these instructions execution system, device or apparatus. For the purpose of this specification, "computer readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by an instruction execution system, device or apparatus or in conjunction with these instruction execution system, device or apparatus.

[0150] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer readable medium can be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, via an optical scanner, then compiled, interpreted, or otherwise processed, as necessary, and stored in a computer memory.

[0151] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the embodiments described above, various steps or methods can be implemented, for example, in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following technologies, known in the art, or combinations thereof, can be used: discrete logic circuitry having logic gates for implementing logic functions upon an application of data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0152] It should be noted that the above examples are merely intended to illustrate the technical solutions of the present application and not to limit the same. Although the present application 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 application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and all such modifications or replacements should be included in the scope of the claims of the present application.

Claims

1. A real-time tracking and positioning system for unmanned aerial vehicles (UAVs) based on the BeiDou satellite system, characterized in that: include, The receiving module receives signals from BeiDou satellites and the Global Navigation Satellite System in real time via an antenna, and converts and demodulates the signal frequencies to obtain pseudorange. The processing module performs multipath effect detection and preliminary correction on the pseudorange, and further corrects and optimizes the preliminary corrected pseudorange based on the delay effects of the ionosphere and troposphere. The position calculation module calculates the UAV's three-dimensional coordinates based on the optimized pseudorange; 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; The multipath effect detection and preliminary correction of pseudorange includes, Signal power received by dual-frequency antenna from satellite signals and noise power Calculate the signal-to-noise ratio (SNR); Set the normal signal-to-noise ratio threshold to Q. If the calculated signal-to-noise ratio (SNR) is less than or equal to the SNR threshold Q, it indicates that the signal is a reflected signal affected by the multipath effect. If the calculated SNR is greater than the SNR threshold Q, it indicates that the signal is a direct signal not affected by the multipath effect. The time delay difference is calculated by analyzing the difference in the propagation time of the reflected signal. And perform pseudorange correction: ， ， In the formula, Indicates the arrival time of the reflected signal. Indicates the arrival time of the direct signal. Represents the original pseudorange. denoted by time 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 is... Further corrections are needed: ， ， In the formula, Indicates the carrier phase of the reflected signal. Indicates the carrier phase of the direct signal. This represents the pseudorange after phase correction. Indicates the carrier wavelength. Indicates the carrier phase difference; Calculate the weighting factor of the satellite signal And further optimize the pseudorange after correction: ， ， In the formula, The signal-to-noise ratio of the i-th satellite signal is represented by n, where n represents the total number of satellite signals. This represents the weighted pseudorange. This represents the pseudorange of the i-th satellite after phase difference correction; The further correction and optimization of the weighted pseudorange based on the delay effects of the ionosphere and troposphere includes, Real-time surface air pressure, temperature, and humidity data are obtained through weather stations; The minimum and maximum values ​​of pseudorange data, surface air pressure data, and temperature and humidity data were found by using the minimum-maximum normalization method, and then the pseudorange data, surface air pressure data, and temperature and humidity data were normalized. The ionospheric delay I is calculated and pseudorange correction is performed using the difference between the two frequencies: ， , In the formula, This indicates the frequency of the B1 band. This indicates the frequency of the B2 band. and This represents the pseudorange in the B1 and B2 frequency bands after phase correction. This represents the pseudorange after ionospheric correction; Calculate the relative geometric distance between the dual-band antenna position and the satellite position, and combine this with the altitude of the dual-band antenna to obtain the satellite elevation angle. : ， In the formula, R represents the distance between the dual-band antenna and the satellite. Indicates the satellite's altitude. Indicates the height of the dual-band antenna; The total tropospheric delay was calculated using the Saastamoinen model. And further pseudorange correction is performed: ， ， In the formula, Indicates total tropospheric delay, Indicates ground air pressure. Indicates standard temperature. Indicates the altitude of the drone. This indicates the pseudorange after further correction; The pseudorange is further optimized using a combination of narrow and wide pseudoranges: ， ， In the formula, and These represent the corrected wide lane pseudorange and narrow lane pseudorange, respectively. and These represent the pseudoranges of the B1 and B2 bands after correction for the ionosphere and troposphere, respectively. The pseudoranges corrected for the ionosphere, troposphere, narrow lane, and wide lane are weighted and fused to obtain the final pseudorange S.

2. The real-time tracking and positioning system for unmanned aerial vehicles based on BeiDou satellite as described in claim 1, characterized in that: The process involves receiving signals from the BeiDou and Global Navigation Satellite Systems in real time via an antenna, converting and demodulating the signal frequencies to obtain pseudorange indicators. A dual-frequency antenna is installed on the UAV to receive dual-frequency signals from the BeiDou and Global Navigation Satellite Systems. A downconverter reduces the frequency of the received dual-frequency signals to the baseband frequency, and a demodulator extracts the pseudo-random noise code, timestamp, and carrier phase information from the baseband frequency. The signal propagation time is calculated by the difference between the received time and the timestamp. : ， In the formula, Indicated as the receiving time, This is represented as the timestamp extracted during demodulation; Calculate the signal propagation time Combined with the speed of light, the pseudorange was calculated: ， In the formula, P represents the calculated pseudorange, and c represents the speed of light.

3. The real-time tracking and positioning system for unmanned aerial vehicles based on BeiDou satellite as described in claim 2, characterized in that: The method of obtaining the UAV's three-dimensional coordinates based on the optimized pseudorange includes: By fusing and optimizing the pseudorange S, a set of pseudorange equations relating to the satellite position is established: ， In the formula, This represents the optimized pseudorange of the i-th satellite. Represents the known three-dimensional coordinates of the i-th satellite. Let c represent the three-dimensional coordinates of the UAV to be solved, and let c represent the speed of light. Indicates receiver clock deviation; The pseudorange equation is solved using the least squares method, and the optimal solution is determined by minimizing the error between the calculated pseudorange value and the actual measured value. The objective function is defined as follows. : ， In the formula, n represents the total number of satellites. This represents the pseudorange of the i-th satellite; By minimizing the objective function The three-dimensional coordinates (x, y, z) of the UAV and the clock offset were obtained. ; Set the convergence threshold to L, and set the objective function... Compare with the convergence condition L, if the objective function If the objective function is less than or equal to the convergence condition, it indicates that the convergence condition has been met, and the current optimal solution is output. If the result is greater than the convergence condition, it means that the convergence condition has not been met, and iterative updates continue. By setting the initial takeoff point of the UAV as the reference point, and using an iterative algorithm to calculate the three-dimensional coordinates (x, y, z) and clock offset, the method is optimized. The process iterates and updates until a set convergence condition is met. Based on this condition, the three-dimensional coordinates (x, y, z) and clock offset of the optimal solution are output. ; The obtained optimal solution's three-dimensional coordinates (x, y, z) and clock offset are then compared. It is used for real-time tracking and positioning of drones.

4. The real-time tracking and positioning system for unmanned aerial vehicles based on BeiDou satellite as described in claim 3, characterized in that: The process of transmitting data to the control center via wireless communication 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, transmitting it to the receiving server at the ground control center via the UDP protocol, decrypting the data using the same AES key as the encryption key, and storing the decrypted data in the database.

5. The real-time tracking and positioning system for unmanned aerial vehicles based on BeiDou satellite as described in claim 4, characterized in that: The process of displaying the flight position and trajectory through a visual interface involves starting the CesiumJS engine on the control center server, initializing a 3D Earth scene, loading the 3D model of the Earth and the 3D model of the drone into Cesium, dynamically displaying the current position of the drone, and using Cesium to parse and predict data to display the future flight trajectory of the drone in the 3D scene as a dashed line.

6. A method for real-time tracking and positioning of unmanned aerial vehicles (UAVs) based on the BeiDou satellite-based real-time tracking and positioning system according to any one of claims 1-5, characterized in that: include, The system receives signals from BeiDou satellites and global navigation satellite systems in real time via an antenna, and converts and demodulates the signal frequencies to obtain pseudorange. Multipath effect detection and preliminary correction are performed on pseudorange, and the preliminary correction is further corrected and optimized based on the delay effects of the ionosphere and troposphere. The three-dimensional coordinates of the UAV are obtained by solving the position based on the optimized pseudorange; Data is transmitted to the control center via wireless communication, and the flight position and trajectory are displayed through a visual interface.

7. A computer device, comprising: Memory and processor; The memory stores a computer program, characterized in that: when the processor executes the computer program, it implements the steps of the real-time tracking and positioning system for unmanned aerial vehicles based on Beidou satellite as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the real-time tracking and positioning system for unmanned aerial vehicles based on Beidou satellite as described in any one of claims 1 to 5.

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