A multi-antenna measurement system for precise positioning of UAV formations

Abstract

The present invention relates to the field of drone positioning, and in particular to a multi-antenna measurement system for accurate positioning of drone formations, including a multi-antenna signal receiving module, a signal processing module, a positioning module, a drone adjustment module, and a user interaction module, wherein the multi-antenna signal receiving module is used to receive wireless signals from each drone in the drone formation; the signal processing module is used to process the wireless signal, the positioning module is used to generate a positioning result of the drone according to the processed data, the drone adjustment module is used to generate an adjustment instruction and adjust the drone formation, and the user interaction module is used to output the positioning result of the positioning module and the adjustment result of the drone adjustment module to a user terminal. The present invention characterizes the yaw degree of the drone by setting a yaw index, which is conducive to understanding whether there are drones that fall behind in the drone formation, thereby adjusting the drone formation.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) positioning, and in particular to a multi-antenna measurement system for precise positioning of a UAV formation. Background Art

[0002] Multiple Input Multiple Output (MIMO) technology was originally used in communication systems. By using multiple antennas at the transmitting and receiving ends, the communication quality and rate were significantly improved. In recent years, MIMO technology has also been gradually introduced into positioning systems to improve positioning accuracy, especially in complex usage environments.

[0003] As disclosed in CN110832339B, a system for locating an object within a certain spatial range may include an electrical device having multiple antennas and a switch coupled to the antenna. The system may also include a controller communicatively coupled to the switch. The controller may measure a first parameter of a signal received at a first antenna at a first time. The controller may also operate the switch from a first position to a second position, wherein the first position enables the first antenna, and wherein the second position enables the second antenna. The controller may also measure a second parameter of a signal received at a second antenna at a second time. The controller may also use the first parameter and the second parameter to determine the multi-dimensional position of the object within the spatial range.

[0004] Another typical prior art disclosed in WO2014101665A1 is a method and system for positioning using a passive multi-beam antenna, which belongs to the field of intelligent transportation. The existing method can measure the position of a vehicle in a lane by using multiple positioning modules or an active phased array module. The method includes the following steps: (1) using a passive method to generate multiple beams in a positioning module to collect signals emitted by the same OBU (on-board unit); (2) using the detector and phase detector in the positioning module to obtain the amplitude and phase signals of each beam, and using A / D sampling to digitize and obtain digital signals; (3) processing the digital signal to obtain the final location information of the OBU.

[0005] Let's take a look at a UWB multi-antenna positioning method disclosed in the prior art CN113376571A, which belongs to the field of positioning technology and specifically includes: a UWB base station with multiple antennas is fixedly set up indoors; the timestamps of sending and receiving data packets between the identification card to be tested and the UWB base station are respectively obtained, and the relative distance between the identification card to be tested and the base station is calculated according to the timestamps; the phase when different antennas receive the UWB signal is obtained, and the azimuth value of the identification card to be tested is obtained according to the phase difference and the relative distance.

[0006] At present, the existing technology using multi-antenna technology to locate UAV formations often only provides positioning, and has low adaptability when facing emergencies. In order to solve the common problems in this field, the present invention is made. Summary of the invention

[0007] The purpose of the present invention is to propose a multi-antenna measurement system for precise positioning of UAV formations in response to the current deficiencies.

[0008] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0009] A multi-antenna measurement system for accurate positioning of a drone formation comprises a multi-antenna signal receiving module, a signal processing module, a positioning module, a drone adjustment module and a user interaction module, wherein the multi-antenna signal receiving module is used to receive wireless signals from each drone in the drone formation; the signal processing module is used to process the wireless signals received by the multi-antenna signal receiving module; the positioning module is used to generate a positioning result of the drone according to the processed data; the drone adjustment module is used to generate an adjustment instruction according to the positioning result of the positioning module and adjust the drone formation according to the adjustment instruction; the user interaction module is used to output the positioning result of the positioning module and the adjustment result of the drone adjustment module to a user terminal; the adjustment of the drone formation according to the adjustment instruction comprises: calculating a yaw index of each drone according to the positioning result of each drone, generating a task completion index of the drone formation according to the yaw index of each drone, and generating an adjustment instruction for each drone according to the yaw index and the task completion index.

[0010] Furthermore, the multi-antenna signal receiving module includes an antenna array, a signal amplifier and an analog-to-digital converter, the antenna array is a square array composed of 9 evenly distributed antennas of the same height, the antenna array is used to receive wireless signals from drones, the signal amplifier is used to amplify the signals received by the antenna array, and the analog-to-digital converter is used to convert the amplified analog signals into digital signals.

[0011] Furthermore, the signal processing module includes a filter and a delay extraction unit, the filter is used to filter the signal received by the multi-antenna signal receiving module to reduce noise, the delay extraction unit includes a time difference detection circuit and a phase difference detection circuit, the time difference detection circuit is used to calculate the time difference of signals received by different antennas based on the filtered signal, and the phase difference detection circuit is used to calculate the phase difference of signals received by different antennas based on the filtered signal, and the calculation result of the delay extraction unit will be sent to the positioning module.

[0012] Furthermore, the positioning module includes a TDOA algorithm processing unit, a PDOA algorithm processing unit and a data fusion unit. The TDOA algorithm processing unit is used to calculate the position of each UAV according to the time difference of signals received by different antennas, and the PDOA algorithm processing unit is used to calculate the position of each UAV according to the phase difference of signals received by different antennas. The data fusion unit is used to fuse the positioning results of the TDOA algorithm processing unit and the PDOA algorithm processing unit through a data fusion algorithm to obtain the final positioning result of each UAV.

[0013] Furthermore, the UAV adjustment module includes a formation status analysis unit, an adjustment instruction generation unit and a UAV communication unit. The formation status analysis unit is used to determine whether the working status of the current formation of UAVs is normal; the adjustment instruction generation unit is used to generate corresponding adjustment instructions according to the analysis results of the formation status analysis unit; and the UAV communication unit is used to send the adjustment instructions generated by the adjustment instruction generation unit to the corresponding UAV.

[0014] Furthermore, the user interaction module includes a communication interface, a data storage unit and a display unit. The communication interface is used to communicate with other devices, the data storage unit is used to store the final positioning of the drone obtained by the positioning module and the adjustments made to the drone formation by the drone adjustment module, and the display unit is used to display the contents stored in the data storage unit to the user.

[0015] Furthermore, the workflow of the system includes the following steps:

[0016] S1, a multi-antenna signal receiving module receives signals from each drone in the drone formation;

[0017] S2, the signal processing module processes the received signal and sends the processed signal to the positioning module;

[0018] S3, the positioning module generates a positioning result according to the processed signal;

[0019] S4, the drone adjustment module adjusts the drones in the drone formation according to the positioning results;

[0020] S5, the user interaction module displays the positioning result generated by the positioning module and the adjustment content of the drone by the drone adjustment module.

[0021] Furthermore, the drone adjustment module adjusts the drones in the drone formation including the following steps:

[0022] S41, obtaining the positioning results of each UAV generated by the positioning module;

[0023] S42, the formation state analysis unit calculates the yaw index of each UAV according to the positioning results of each UAV;

[0024] S43, the formation state analysis unit generates a task completion index of the UAV formation according to the yaw index of each UAV;

[0025] S44, the adjustment instruction generation unit generates an adjustment instruction for each UAV according to the yaw index and the task completion index;

[0026] S45, the UAV communication unit sends the adjustment instruction to the UAV, and the UAV adjusts itself according to the adjustment instruction.

[0027] Furthermore, the adjustment instruction generation unit generates an adjustment instruction for each drone including the following steps:

[0028] S441, judging whether the mission completion index of the UAV formation is qualified, if not, generating a status instruction to continue to execute the current mission, otherwise, executing the next step;

[0029] S442, generating a return time of the UAV formation according to the task completion index;

[0030] S443, obtaining theoretical coordinates of each drone after the return time according to the mission of the drone;

[0031] S444, obtaining the adjusted target speed of each UAV according to the theoretical coordinates and the yaw index;

[0032] S445: Generate corresponding adjustment instructions based on the obtained adjusted target speed and theoretical coordinates.

[0033] The beneficial effects achieved by the present invention are: 1. By setting the yaw index to characterize the yaw degree of the drone, it is helpful to understand whether there are any drones that are left behind in the drone formation. By generating the task completion index through the yaw index, it is helpful to understand the current task completion status of the drone formation, thereby adjusting the drone formation.

[0034] 2. By adjusting the command generation unit to adjust each drone in the drone formation, it is beneficial to adjust the drone formation according to the degree of yaw of the drone and the degree of mission completion of the drone, thereby ensuring that the drone formation can work normally and speeding up the work efficiency of the drone formation. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0036] Figure 1 It is a schematic diagram of the structure of the present invention.

[0037] Figure 2 It is the work flow chart of the present invention.

[0038] Figure 3 The flowchart of the drone adjustment module of the present invention adjusting the drone.

[0039] Figure 4 The present invention is a flowchart of an adjustment instruction generation unit generating an adjustment instruction. DETAILED DESCRIPTION

[0040] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual sizes. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0041] Embodiment 1: According to Figure 1 , Figure 2 , Figure 3 and Figure 4 The present embodiment provides a multi-antenna measurement system for precise positioning of a drone formation, comprising a multi-antenna signal receiving module, a signal processing module, a positioning module, a drone adjustment module and a user interaction module, wherein the multi-antenna signal receiving module is used to receive wireless signals from each drone in the drone formation; the signal processing module is used to process the wireless signals received by the multi-antenna signal receiving module; the positioning module is used to generate a positioning result of the drone according to the processed data; the drone adjustment module is used to generate an adjustment instruction according to the positioning result of the positioning module and adjust the drone formation according to the adjustment instruction; the user interaction module is used to output the positioning result of the positioning module and the adjustment result of the drone adjustment module to a user terminal; the adjusting of the drone formation according to the adjustment instruction comprises: calculating a yaw index of each drone according to the positioning result of each drone, generating a task completion index of the drone formation according to the yaw index of each drone, and generating an adjustment instruction for each drone according to the yaw index and the task completion index.

[0042] Furthermore, the multi-antenna signal receiving module includes an antenna array, a signal amplifier and an analog-to-digital converter, the antenna array is a square array composed of 9 evenly distributed antennas of the same height, the antenna array is used to receive wireless signals from drones, the signal amplifier is used to amplify the signals received by the antenna array, and the analog-to-digital converter is used to convert the amplified analog signals into digital signals.

[0043] Furthermore, the signal processing module includes a filter and a delay extraction unit, the filter is used to filter the signal received by the multi-antenna signal receiving module to reduce noise, the delay extraction unit includes a time difference detection circuit and a phase difference detection circuit, the time difference detection circuit is used to calculate the time difference of signals received by different antennas based on the filtered signal, and the phase difference detection circuit is used to calculate the phase difference of signals received by different antennas based on the filtered signal, and the calculation result of the delay extraction unit will be sent to the positioning module.

[0044] Specifically, the time difference detection circuit and the phase difference detection circuit belong to the prior art and will not be elaborated here; the preprocessing includes but is not limited to compensation, denoising, standardization, etc.

[0045] Furthermore, the positioning module includes a TDOA algorithm processing unit, a PDOA algorithm processing unit and a data fusion unit. The TDOA algorithm processing unit is used to calculate the position of each UAV according to the time difference of signals received by different antennas, and the PDOA algorithm processing unit is used to calculate the position of each UAV according to the phase difference of signals received by different antennas. The data fusion unit is used to fuse the positioning results of the TDOA algorithm processing unit and the PDOA algorithm processing unit through a data fusion algorithm to obtain the final positioning result of each UAV.

[0046] Specifically, the data fusion algorithm may be a Kalman filter algorithm or a particle filter algorithm. The Kalman filter algorithm and the particle filter algorithm belong to the prior art and will not be described in detail herein.

[0047] Furthermore, the UAV adjustment module includes a formation status analysis unit, an adjustment instruction generation unit and a UAV communication unit. The formation status analysis unit is used to determine whether the working status of the current formation of UAVs is normal; the adjustment instruction generation unit is used to generate corresponding adjustment instructions according to the analysis results of the formation status analysis unit; and the UAV communication unit is used to send the adjustment instructions generated by the adjustment instruction generation unit to the corresponding UAV.

[0048] Furthermore, the user interaction module includes a communication interface, a data storage unit and a display unit. The communication interface is used to communicate with other devices, the data storage unit is used to store the final positioning of the drone obtained by the positioning module and the adjustments made to the drone formation by the drone adjustment module, and the display unit is used to display the contents stored in the data storage unit to the user.

[0049] Furthermore, the workflow of the system includes the following steps:

[0050] S1, a multi-antenna signal receiving module receives signals from each drone in the drone formation;

[0051] S2, the signal processing module processes the received signal and sends the processed signal to the positioning module;

[0052] S3, the positioning module generates a positioning result according to the processed signal;

[0053] Specifically, the positioning result is the coordinates of the target in three-dimensional space;

[0054] S4, the drone adjustment module adjusts the drones in the drone formation according to the positioning results;

[0055] S5, the user interaction module displays the positioning result generated by the positioning module and the adjustment content of the drone by the drone adjustment module.

[0056] Furthermore, the drone adjustment module adjusts the drones in the drone formation including the following steps:

[0057] S41, obtaining the positioning results of each UAV generated by the positioning module;

[0058] S42, the formation state analysis unit calculates the yaw index of each UAV according to the positioning results of each UAV;

[0059] Specifically, the drone formation has formed a preset layout of the formation according to the set mission when taking off. Under the preset layout, the relative positions and relative distances between the drones are set. The yaw index is used to characterize the degree of deviation between the position of each drone in its current layout and its position in the preset layout. The larger the yaw index, the higher the yaw degree. Let the total number of drones in the drone formation be A;

[0060] The yaw index can be calculated according to the following formula:

[0061] ;

[0062] in, is the yaw index of the ath UAV, A is the total number of UAVs in the UAV formation, is the coordinate of the ath drone in the x-axis direction, is the coordinate of the ath drone in the y-axis direction, is the coordinate of the ath drone in the z-axis direction, is the coordinate of the i-th UAV except the a-th UAV in the x-axis direction, is the coordinate of the ith UAV except the ath UAV in the y-axis direction, is the coordinate of the i-th UAV except the a-th UAV in the z-axis direction; is the distance between the a-th UAV and the i-th UAV other than the a-th UAV in the preset layout;

[0063] S43, the formation state analysis unit generates a task completion index of the UAV formation according to the yaw index of each UAV;

[0064] The task completion index can be calculated according to the following formula:

[0065] ;

[0066] in, The task completion index is used to characterize the degree of task completion of the UAV formation. The larger the value of this index, the worse the degree of task completion of the UAV formation. is the distance deviation weight of the a-th UAV, is the theoretical coordinate of the ath UAV in the x-axis direction, is the theoretical coordinate of the ath UAV in the y-axis direction, is the theoretical coordinate of the ath UAV in the z-axis direction;

[0067] Specifically, the theoretical coordinates of the drone at a certain moment can be obtained according to the mission assigned to the drone and the position of the drone at that moment; the distance deviation weight can be set between 0 and 1 according to the yaw index of the drone, and the larger the yaw index, the smaller the corresponding distance deviation weight;

[0068] S44, the adjustment instruction generation unit generates an adjustment instruction for each UAV according to the yaw index and the task completion index;

[0069] S45, the UAV communication unit sends the adjustment instruction to the UAV, and the UAV adjusts itself according to the adjustment instruction.

[0070] Specifically, the drone itself has a built-in instruction analysis unit, which will identify the adjustment instructions and convert the adjustment instructions into adjustment parameters of various parts of the drone (such as motor speed) through a set conversion rule (set by technical personnel in this field), thereby adjusting the drone.

[0071] The adjustment instruction generation unit generates an adjustment instruction for each drone, including the following steps:

[0072] S441, judging whether the mission completion index of the UAV formation is qualified, if not, generating a status instruction to continue to execute the current mission, otherwise, executing the next step;

[0073] S442, generating a return time of the UAV formation according to the task completion index;

[0074] ;

[0075] in, is the time required for the drone formation to return to the team, which is the limit value of the time required for the drone formation to recover from the current state to the preset layout without affecting the work task. Set the speed of the drone. is the task completion indicator threshold; the set speed of the drone is the current forward or backward speed of the drone.

[0076] S443, obtaining theoretical coordinates of each drone after the return time according to the mission of the drone;

[0077] S444, obtaining the adjusted target speed of each UAV according to the theoretical coordinates and the yaw index;

[0078] The adjusted target speed can be obtained according to the following formula:

[0079] ;

[0080] in, is the adjusted target speed of the a-th UAV, is the theoretical coordinate of the ath UAV in the x-axis direction after the return time, is the theoretical coordinate of the ath UAV in the y-axis direction after the return time, is the theoretical coordinate of the ath UAV in the z-axis direction after the return time, is the yaw index threshold;

[0081] S445: Generate corresponding adjustment instructions based on the obtained adjusted target speed and theoretical coordinates.

[0082] Specifically, a task completion index threshold and a yaw index threshold are set. When the task completion index is greater than the task completion index threshold, the task completion index is unqualified. When the yaw index is greater than the yaw index threshold, the yaw index is unqualified. The task completion index threshold and the yaw index threshold are set by technical personnel in this field according to the deviation between the actual training situation and the target training situation when the UAV formation is training.

[0083] The beneficial effects of this scheme are as follows: 1. By setting the yaw index to characterize the yaw degree of the drone, it is helpful to understand whether there are any drones that are left behind in the drone formation. By generating the task completion index through the yaw index, it is helpful to understand the current task completion status of the drone formation, so as to adjust the drone formation.

[0084] 2. By adjusting the command generation unit to adjust each drone in the drone formation, it is beneficial to adjust the drone formation according to the degree of yaw of the drone and the degree of mission completion of the drone, thereby ensuring that the drone formation can work normally and speeding up the work efficiency of the drone formation.

[0085] Embodiment 2: This embodiment should be understood to include all the features of any of the above embodiments, and further improve on the basis thereof, and further in that the distance deviation weight can be set according to the following method:

[0086] Calculate the center coordinates of the drone formation;

[0087] Center coordinates ( ) can be calculated according to the following formula:

[0088] ;

[0089] ;

[0090] ;

[0091] The distance deviation weight of the ath drone is obtained according to the following formula:

[0092] ;

[0093] in, is the coordinate value of each drone's x-axis coordinate that is farthest from the center coordinate. is the coordinate value of each drone's y-axis coordinate that is farthest from the center coordinate. It is the coordinate value of each drone's z-axis coordinate that is farthest from the center coordinate.

[0094] The beneficial effects of this embodiment are as follows: the distance deviation weight is set by the deviation coordinates and the distance between the UAV and the center coordinates, so that UAVs with larger deviations or UAVs farther away from the formation contribute smaller weights in the calculation, which is conducive to improving the calculation results of the task completion index to be more in line with the task completion degree of the UAV formation.

[0095] The above disclosed contents are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made by using the contents of the present invention specification and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated with the development of technology. The above units are only examples. Those skilled in the art can use corresponding units according to different designs according to actual needs when implementing this solution.

Claims

1. A multi-antenna measurement system for precise positioning of UAV formations, characterized in that: It includes a multi-antenna signal receiving module, a signal processing module, a positioning module, a drone adjustment module and a user interaction module. The multi-antenna signal receiving module is used to receive wireless signals from each drone in the drone formation; the signal processing module is used to process the wireless signals received by the multi-antenna signal receiving module; the positioning module is used to generate a positioning result of the drone according to the processed data; the drone adjustment module is used to generate an adjustment instruction according to the positioning result of the positioning module and adjust the drone formation according to the adjustment instruction; the user interaction module is used to output the positioning result of the positioning module and the adjustment result of the drone adjustment module to the user terminal; The adjusting of the UAV formation according to the adjustment instruction includes: calculating the yaw index of each UAV according to the positioning result of each UAV, generating the task completion index of the UAV formation according to the yaw index of each UAV, and generating the adjustment instruction for each UAV according to the yaw index and the task completion index; The drone adjustment module adjusts the drones in the drone formation, including the following steps: S41, obtaining the positioning results of each UAV generated by the positioning module; S42, the formation state analysis unit calculates the yaw index of each UAV according to the positioning results of each UAV; The yaw index can be calculated according to the following formula: ； in, is the yaw index of the ath UAV, A is the total number of UAVs in the UAV formation, is the coordinate of the ath drone in the x-axis direction, is the coordinate of the ath drone in the y-axis direction, is the coordinate of the ath drone in the z-axis direction, is the coordinate of the i-th UAV except the a-th UAV in the x-axis direction, is the coordinate of the ith UAV except the ath UAV in the y-axis direction, is the coordinate of the i-th UAV except the a-th UAV in the z-axis direction; is the distance between the a-th UAV and the i-th UAV other than the a-th UAV in the preset layout; S43, the formation state analysis unit generates a task completion index of the UAV formation according to the yaw index of each UAV; The task completion index can be calculated according to the following formula: ； in, The task completion index is used to characterize the degree of task completion of the UAV formation. The larger the value of this index, the worse the degree of task completion of the UAV formation. is the distance deviation weight of the a-th UAV, is the theoretical coordinate of the ath UAV in the x-axis direction, is the theoretical coordinate of the ath UAV in the y-axis direction, is the theoretical coordinate of the ath UAV in the z-axis direction; S44, the adjustment instruction generation unit generates an adjustment instruction for each UAV according to the yaw index and the task completion index; S45, the UAV communication unit sends the adjustment instruction to the UAV, and the UAV adjusts itself according to the adjustment instruction; The adjustment instruction generation unit generates an adjustment instruction for each drone, including the following steps: S441, judging whether the mission completion index of the UAV formation is qualified, if not, generating a status instruction to continue to execute the current mission, otherwise, executing the next step; S442, generating a return time of the UAV formation according to the task completion index; ； in, is the time required for the drone formation to return to the team, which is the limit value of the time required for the drone formation to recover from the current state to the preset layout without affecting the work task. Set the speed of the drone. is the task completion indicator threshold; the set speed of the drone is the current forward or backward speed of the drone; S443, obtaining theoretical coordinates of each drone after the return time according to the mission of the drone; S444, obtaining the adjusted target speed of each UAV according to the theoretical coordinates and the yaw index; ； in, is the adjusted target speed of the a-th UAV, is the theoretical coordinate of the ath UAV in the x-axis direction after the return time, is the theoretical coordinate of the ath UAV in the y-axis direction after the return time, is the theoretical coordinate of the ath UAV in the z-axis direction after the return time, is the yaw index threshold; S445: Generate corresponding adjustment instructions based on the obtained adjusted target speed and theoretical coordinates.

2. A multi-antenna measurement system for precise positioning of UAV formations according to claim 1, characterized in that: The multi-antenna signal receiving module includes an antenna array, a signal amplifier and an analog-to-digital converter. The antenna array is a square array composed of 9 evenly distributed antennas of the same height. The antenna array is used to receive wireless signals from drones. The signal amplifier is used to amplify the signals received by the antenna array. The analog-to-digital converter is used to convert the amplified analog signals into digital signals.

3. The multi-antenna measurement system for accurate positioning of UAV formation according to claim 2, characterized in that: The signal processing module includes a filter and a delay extraction unit. The filter is used to filter the signal received by the multi-antenna signal receiving module to reduce noise. The delay extraction unit includes a time difference detection circuit and a phase difference detection circuit. The time difference detection circuit is used to calculate the time difference of signals received by different antennas based on the filtered signal. The phase difference detection circuit is used to calculate the phase difference of signals received by different antennas based on the filtered signal. The calculation result of the delay extraction unit will be sent to the positioning module.

4. The multi-antenna measurement system for accurate positioning of UAV formation according to claim 3, characterized in that: The positioning module includes a TDOA algorithm processing unit, a PDOA algorithm processing unit and a data fusion unit. The TDOA algorithm processing unit is used to calculate the position of each drone according to the time difference of signals received by different antennas. The PDOA algorithm processing unit is used to calculate the position of each drone according to the phase difference of signals received by different antennas. The data fusion unit is used to fuse the positioning results of the TDOA algorithm processing unit and the PDOA algorithm processing unit through a data fusion algorithm to obtain the final positioning result of each drone.

5. The multi-antenna measurement system for accurate positioning of UAV formation according to claim 4, characterized in that: The UAV adjustment module includes a formation status analysis unit, an adjustment instruction generation unit and a UAV communication unit. The formation status analysis unit is used to determine whether the working status of the current formation of UAVs is normal; the adjustment instruction generation unit is used to generate corresponding adjustment instructions according to the analysis results of the formation status analysis unit; and the UAV communication unit is used to send the adjustment instructions generated by the adjustment instruction generation unit to the corresponding UAV.

6. The multi-antenna measurement system for accurate positioning of UAV formation according to claim 5, characterized in that: The user interaction module includes a communication interface, a data storage unit and a display unit. The communication interface is used to communicate with other devices. The data storage unit is used to store the final positioning of the drone obtained by the positioning module and the adjustments made to the drone formation by the drone adjustment module. The display unit is used to display the contents stored in the data storage unit to the user.

7. The multi-antenna measurement system for accurate positioning of UAV formation according to claim 6, characterized in that: The workflow of the system includes the following steps: S1, a multi-antenna signal receiving module receives signals from each drone in the drone formation; S2, the signal processing module processes the received signal and sends the processed signal to the positioning module; S3, the positioning module generates a positioning result according to the processed signal; S4, the drone adjustment module adjusts the drones in the drone formation according to the positioning results; S5, the user interaction module displays the positioning result generated by the positioning module and the adjustment content of the drone by the drone adjustment module.

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