Unmanned aerial vehicle operation positioning system based on artificial intelligence

Abstract

The invention relates to the technical field of unmanned aerial vehicle positioning, in particular to an unmanned aerial vehicle operation positioning system based on artificial intelligence, which comprises a flight positioning management and control platform, a flight information unit, a flight matching unit, a positioning matching unit, a yaw adjusting unit and a flight management unit, the linear distance between the target unmanned aerial vehicle and the current ground base station is collected and compared with the working range of the current ground base station, so that the current positioning mode of the target unmanned aerial vehicle is judged, the positioning mode is further analyzed, namely positioning scheme rationality processing and analysis are conducted on the positioning state information, and the positioning accuracy is improved. According to the method, whether a current target unmanned aerial vehicle flight positioning scheme is appropriate and reasonable or not is judged, improvement of target unmanned aerial vehicle flight positioning accuracy and reliability is facilitated, yaw interference matching feedback analysis is carried out on flight environment data in a progressive mode, then the yaw range is reasonably adjusted according to the yaw interference condition, and the target unmanned aerial vehicle flight positioning accuracy and reliability are improved. And data support is provided for follow-up target unmanned aerial vehicle flight positioning correction.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle positioning, and in particular to an unmanned aerial vehicle operation positioning system based on artificial intelligence. Background Art

[0002] With the continuous advancement of drone technology and the increasing expansion of its application areas, drones are playing an increasingly significant role in film and television production, agricultural monitoring, environmental protection, infrastructure inspection, etc. In these applications, the introduction of precise positioning devices has become one of the key factors in improving the operating efficiency and data quality of drones. However, in the prior art, the drone cannot reasonably match the positioning method according to the flight distance of the drone during the flight period, thereby reducing the positioning accuracy of the drone. In addition, the drone is easily deviated from the set route due to the influence of the drone's flight environment, and it is impossible to make reasonable flight corrections based on the real-time positioning of the drone, which is not conducive to the accurate positioning of the drone and reduces the positioning management efficiency of the drone. In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a UAV operation positioning system based on artificial intelligence to solve the above-mentioned technical defects. The present invention collects the straight-line distance between the target UAV and the current ground base station and compares it with the working range of the current ground base station to determine the current positioning mode of the target UAV, and further analyzes the positioning mode, that is, performs positioning scheme rationality processing and analysis on the positioning status information to determine whether the current target UAV flight positioning scheme is appropriate and reasonable, so as to reasonably replace the positioning scheme, which helps to improve the accuracy and reliability of the target UAV flight positioning, and performs yaw interference matching feedback analysis on the flight environment data in a progressive manner, and then reasonably adjusts the yaw range according to the yaw interference situation, so as to provide data support for subsequent target UAV flight positioning correction, thereby helping to improve the efficiency of target UAV flight positioning management.

[0004] The object of the present invention can be achieved by the following technical solutions: an artificial intelligence-based UAV operation positioning system, comprising a flight positioning control platform, a flight information unit, a flight matching unit, a positioning matching unit, a yaw adjustment unit, and a flight management unit; The flight information unit is used to collect the straight-line distance between the target UAV and the current ground base station and send it to the flight positioning control platform; The flight matching unit is used to retrieve the straight-line distance between the target UAV and the current ground base station, and perform flight positioning range division analysis to determine the positioning method of the target UAV and obtain a radio positioning signal or a GPS positioning signal; The positioning matching unit is used to respond to the radio positioning signal or the GPS positioning signal, collect the positioning status information of the target UAV, compare and analyze the obtained positioning deviation index and loss risk index, and obtain a positioning effective signal or a positioning adjustment signal; The yaw adjustment unit is used to respond to the effective positioning signal, collect the flight environment data of the target UAV, and perform yaw interference matching feedback analysis on the flight environment data to obtain a correction signal.

[0005] Preferably, the flight positioning range division analysis process of the flight matching unit is as follows: The operating time period of the drone is collected and set as the time threshold, the working range of the current ground base station is obtained, and the straight-line distance between the target drone and the current ground base station is obtained. The straight-line distance between the target drone and the current ground base station is compared and analyzed with the working range of the current ground base station: If the straight-line distance between the target UAV and the current ground base station falls within the working range of the current ground base station, a radio positioning signal is generated; If the straight-line distance between the target UAV and the current ground base station is not within the working range of the current ground base station, a GPS positioning signal is generated.

[0006] Preferably, the rationality processing and analysis process of the positioning scheme of the positioning matching unit is as follows: The positioning status information of the target UAV within the time threshold is obtained. The positioning status information includes the positioning deviation index and the loss risk index. The positioning deviation index and the loss risk index are compared and analyzed with the preset positioning deviation index and the loss risk index thresholds stored in the internal storage: If the positioning deviation index is less than the preset positioning deviation index threshold, and the loss risk index is less than the preset loss risk index threshold, a positioning valid signal is generated; If the positioning deviation index is greater than or equal to the preset positioning deviation index threshold, or the loss risk index is greater than or equal to the preset loss risk index threshold, a positioning adjustment signal is generated.

[0007] Preferably, the positioning deviation index represents the frequency of inconsistency between the displayed coordinates and the time coordinates of the target UAV; the loss risk index represents the product of the coordinate display loss frequency of the target UAV and the loss duration after data normalization processing.

[0008] Preferably, the yaw interference matching feedback analysis process of the yaw adjustment unit is as follows: S1. Flight environment data collection; S2, data processing matching operation; S3, target UAV yaw range adjustment operation; S4. Target UAV yaw discrimination analysis.

[0009] Preferably, S1: flight environment data collection: obtaining the flight environment data of the target UAV within a time threshold, the flight environment data including the yaw interference value and the electromagnetic interference index.

[0010] Preferably, S2, data processing matching operation: the data yaw interference value and electromagnetic interference index are labeled as PG and DG respectively, and the yaw interference value PG and the electromagnetic interference index DG are substituted into the formula The flight interference assessment coefficient is obtained, wherein a1 and a2 are preset correction proportional factor coefficients of the yaw interference value and the electromagnetic interference index respectively, a3 is the preset error correction factor coefficient, a1=1.876, a2=1.263, and a3=2,116, G is the flight interference assessment coefficient, and the flight interference assessment coefficient G is compared and analyzed with the preset flight interference assessment coefficient interval stored internally, so as to obtain the flight interference assessment coefficient G in the corresponding preset flight interference assessment coefficient interval and set it as the yaw interference factor pz.

[0011] Preferably, S3, target UAV yaw range adjustment operation: then matching the allowable yaw range value of the target UAV according to the yaw interference factor pz; S4. Target UAV yaw discrimination analysis: The flight coordinates of the target UAV are obtained in real time, and the specified flight coordinates of the target UAV are obtained at the same time, and then the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is obtained, and the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is set as the yaw flight distance, and the yaw flight distance is compared and analyzed with the allowable yaw range value of the target UAV: If the deviation flight distance is within the permissible deviation range of the target UAV, no signal is generated; If the yaw flight distance does not fall within the permissible yaw range value of the target UAV, a correction signal is generated.

[0012] The beneficial effects of the present invention are as follows: 1. The present invention collects the straight-line distance between the target UAV and the current ground base station and compares it with the working range of the current ground base station to determine the current positioning mode of the target UAV, i.e., radio positioning or GPS positioning, and further analyzes the positioning mode, i.e., performs positioning scheme rationality processing and analysis on the positioning state information to determine whether the current flight positioning scheme of the target UAV is appropriate and reasonable, so as to reasonably replace the positioning scheme, i.e., satellite positioning or inertial navigation system. On the one hand, it helps to judge whether the current flight positioning scheme of the target UAV is appropriate, and on the other hand, it helps to timely adjust the flight positioning scheme of the target UAV, thereby helping to improve the accuracy and reliability of the flight positioning of the target UAV; 2. The present invention performs yaw interference matching feedback analysis on the flight environment data in a progressive manner, and then reasonably adjusts the yaw range according to the yaw interference situation, thereby facilitating the subsequent target UAV flight positioning correction to provide data support, thereby helping to improve the target UAV flight positioning management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is a flowchart of the system of the present invention; Figure 2 It is a local analysis reference diagram of the second embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Example 1: Please refer to Figure 1 to Figure 2 As shown, the present invention is an artificial intelligence-based unmanned aerial vehicle operation positioning system, including a flight positioning control platform, a flight information unit, a flight matching unit, a positioning matching unit, a yaw adjustment unit and a flight management unit, the flight positioning control platform is in a two-way communication connection with the flight information unit, the flight positioning control platform is in a one-way communication connection with the flight matching unit, the flight matching unit is in a one-way communication connection with the positioning matching unit and the flight management unit, the positioning matching unit is in a one-way communication connection with the yaw adjustment unit and the flight management unit, and the yaw adjustment unit is in a one-way communication connection with the flight management unit; In the embodiment of the present invention, when the flight positioning control platform detects the operation of any UAV, it generates a supervision instruction and sends the supervision instruction to the flight information unit; In the embodiment of the present invention, the flight information unit is used to respond to the supervision instruction, collect the straight-line distance between the target UAV and the current ground base station, and send it to the flight positioning control platform; In the embodiment of the present invention, the flight matching unit is used to retrieve the straight-line distance between the target UAV and the current ground base station, and perform flight positioning range division analysis to determine the positioning mode of the target UAV. The specific flight positioning range division analysis process is as follows: The operating time period of the drone is collected and set as the time threshold, the working range of the current ground base station is obtained, and the straight-line distance between the target drone and the current ground base station is obtained. The straight-line distance between the target drone and the current ground base station is compared and analyzed with the working range of the current ground base station: If the straight-line distance between the target UAV and the current ground base station falls within the working range of the current ground base station, a radio positioning signal is generated; If the straight-line distance between the target UAV and the current ground base station does not fall within the working range of the current ground base station, a GPS positioning signal is generated, and the radio positioning signal or the GPS positioning signal is sent to the flight management unit. After receiving the radio positioning signal or the GPS positioning signal, the flight management unit immediately displays the preset warning text corresponding to the radio positioning signal or the GPS positioning signal, so as to perform reasonable positioning matching according to the flight distance of the target UAV; When a radio positioning signal or a GPS positioning signal is generated, the positioning matching unit is used to respond to the radio positioning signal or the GPS positioning signal, collect the positioning status information of the target UAV, and perform a positioning scheme rationality processing and analysis on the positioning status information to determine whether the current target UAV flight positioning scheme is appropriate and reasonable, so as to adjust the current target UAV flight positioning scheme. The specific positioning scheme rationality processing and analysis process is as follows: The positioning status information of the target UAV within the time threshold is obtained. The positioning status information includes the positioning deviation index and the loss risk index. The positioning deviation index and the loss risk index are compared and analyzed with the preset positioning deviation index and the loss risk index thresholds stored in the internal storage: If the positioning deviation index is less than the preset positioning deviation index threshold, and the loss risk index is less than the preset loss risk index threshold, a positioning valid signal is generated; If the positioning deviation index is greater than or equal to the preset positioning deviation index threshold, or the loss risk index is greater than or equal to the preset loss risk index threshold, a positioning adjustment signal is generated, and the positioning effective signal and the positioning adjustment signal are sent to the flight management unit. After receiving the positioning effective signal and the positioning adjustment signal, the flight management unit immediately makes the preset warning operation corresponding to the positioning effective signal and the positioning adjustment signal, and then rationally adjusts the flight positioning method of the target UAV according to the feedback information, that is, the satellite positioning or inertial navigation system, to ensure the accurate positioning of the target UAV, that is, on the one hand, it helps to judge whether the current flight positioning plan of the target UAV is appropriate, and on the other hand, it helps to rationally adjust the flight positioning plan of the target UAV, thereby helping to improve the accuracy and reliability of the flight positioning of the target UAV; In the embodiment of the present invention, the positioning deviation index indicates the frequency of inconsistency between the display coordinates and the time coordinates of the target UAV. It should be noted that the larger the value of the positioning deviation index, the greater the positioning error risk of the target UAV. In the embodiment of the present invention, the loss risk index represents the product of the coordinate display loss frequency of the target UAV and the loss duration after data normalization. It should be noted that the larger the value of the loss risk index, the greater the risk of positioning and tracking the target UAV.

[0016] Embodiment 2: When a valid positioning signal is generated, the yaw adjustment unit is used to respond to the valid positioning signal, collect the flight environment data of the target UAV, and perform yaw interference matching feedback analysis on the flight environment data, and then adjust the yaw range according to the yaw situation. The specific yaw interference matching feedback analysis process is as follows: S1. Flight environment data collection: obtain the flight environment data of the target UAV within the time threshold, the flight environment data includes the yaw interference value and the electromagnetic interference index; S2. Data processing and matching operation: The yaw interference value and electromagnetic interference index are labeled as PG and DG respectively, and the yaw interference value PG and the electromagnetic interference index DG are substituted into the formula The flight interference assessment coefficient is obtained, wherein a1 and a2 are preset correction proportional factor coefficients of the yaw interference value and the electromagnetic interference index, respectively. The preset correction proportional factor coefficient is used to correct the deviation of various parameters in the process of formula calculation, so as to make the calculation result more accurate. A3 is a preset error correction factor coefficient, a1=1.876, a2=1.263, and a3=2,116. G is the flight interference assessment coefficient. The flight interference assessment coefficient G is compared and analyzed with the preset flight interference assessment coefficient interval stored in the internal data entry, and then the flight interference assessment coefficient G is obtained in the corresponding preset flight interference assessment coefficient interval and is set as the yaw interference factor pz; In the embodiment of the present invention, each preset flight interference assessment coefficient interval is set with a corresponding yaw interference factor; S3, target UAV yaw range adjustment operation: then matching the target UAV's allowable yaw range value according to the yaw interference factor pz; S4. Target UAV yaw discrimination analysis: The flight coordinates of the target UAV are obtained in real time, and the specified flight coordinates of the target UAV are obtained at the same time, and then the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is obtained, and the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is set as the yaw flight distance, and the yaw flight distance is compared and analyzed with the allowable yaw range value of the target UAV: If the deviation flight distance is within the permissible deviation range of the target UAV, no signal is generated; If the deviation flight distance does not belong to the permissible deviation range value of the target UAV, a correction signal is generated and sent to the flight management unit. After receiving the correction signal, the flight management unit immediately performs a preset warning operation corresponding to the correction signal, so as to perform flight correction on the target UAV to improve the flight accuracy of the target UAV; The core steps of yaw disturbance matching feedback analysis are as follows: S1. Flight environment data collection; S2, data processing matching operation; S3, target UAV yaw range adjustment operation; S4, target UAV yaw discrimination analysis; In the embodiment of the present invention, the yaw interference value indicates the duration corresponding to the air velocity mean value exceeding the preset air velocity mean value threshold value. It should be noted that the larger the yaw interference value, the greater the risk of the target UAV flight yaw, and the larger the range of allowed yaw is set; In the embodiment of the present invention, the electromagnetic interference index represents the product value obtained by multiplying the number of electromagnetic interference sources and the average value of environmental electromagnetic interference after data normalization processing, and the electromagnetic interference sources include communication transmission equipment, communication switching equipment, etc. In summary, the present invention collects the straight-line distance between the target UAV and the current ground base station and compares it with the working range of the current ground base station to determine the current positioning mode of the target UAV, that is, radio positioning or GPS positioning, and further analyzes the positioning mode, that is, performs positioning scheme rationality processing and analysis on the positioning state information to determine whether the current target UAV flight positioning scheme is appropriate and reasonable, so as to reasonably replace the positioning scheme, that is, satellite positioning or inertial navigation system. On the one hand, it helps to judge whether the current target UAV flight positioning scheme is appropriate, and on the other hand, it helps to timely adjust the target UAV flight positioning scheme, thereby helping to improve the accuracy and reliability of the target UAV flight positioning, and through a progressive manner, the yaw interference matching feedback analysis of the flight environment data, and then reasonably adjust the yaw range according to the yaw interference situation, thereby facilitating the subsequent target UAV flight positioning correction to provide data support, thereby helping to improve the efficiency of target UAV flight positioning management; The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0017] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. An artificial intelligence-based drone operation positioning system, characterized in that: It includes flight positioning control platform, flight information unit, flight matching unit, positioning matching unit, yaw adjustment unit and flight management unit; The flight information unit is used to collect the straight-line distance between the target UAV and the current ground base station and send it to the flight positioning control platform; The flight matching unit is used to retrieve the straight-line distance between the target UAV and the current ground base station, and perform flight positioning range division analysis to determine the positioning method of the target UAV and obtain a radio positioning signal or a GPS positioning signal; The positioning matching unit is used to respond to the radio positioning signal or the GPS positioning signal, collect the positioning status information of the target UAV, compare and analyze the obtained positioning deviation index and loss risk index, and obtain a positioning effective signal or a positioning adjustment signal; The yaw adjustment unit is used to respond to the effective positioning signal, collect the flight environment data of the target UAV, and perform yaw interference matching feedback analysis on the flight environment data to obtain a correction signal.

2. The artificial intelligence-based drone operation positioning system according to claim 1, characterized in that: The flight positioning range division analysis process of the flight matching unit is as follows: The operating time period of the drone is collected and set as the time threshold, the working range of the current ground base station is obtained, and the straight-line distance between the target drone and the current ground base station is obtained. The straight-line distance between the target drone and the current ground base station is compared and analyzed with the working range of the current ground base station: If the straight-line distance between the target UAV and the current ground base station falls within the working range of the current ground base station, a radio positioning signal is generated; If the straight-line distance between the target UAV and the current ground base station is not within the working range of the current ground base station, a GPS positioning signal is generated.

3. The artificial intelligence-based drone operation positioning system according to claim 1 is characterized in that: The rationality analysis process of the positioning scheme of the positioning matching unit is as follows: The positioning status information of the target UAV within the time threshold is obtained. The positioning status information includes the positioning deviation index and the loss risk index. The positioning deviation index and the loss risk index are compared and analyzed with the preset positioning deviation index and the loss risk index thresholds stored in the internal storage: If the positioning deviation index is less than the preset positioning deviation index threshold, and the loss risk index is less than the preset loss risk index threshold, a positioning valid signal is generated; If the positioning deviation index is greater than or equal to the preset positioning deviation index threshold, or the loss risk index is greater than or equal to the preset loss risk index threshold, a positioning adjustment signal is generated.

4. The artificial intelligence-based unmanned aerial vehicle operation positioning system according to claim 3 is characterized in that: The positioning deviation index indicates the frequency of inconsistency between the displayed coordinates and the time coordinates of the target UAV; the loss risk index indicates the product of the coordinate display loss frequency of the target UAV and the loss duration after data normalization processing.

5. The artificial intelligence-based drone operation positioning system according to claim 1, characterized in that: The yaw disturbance matching feedback analysis process of the yaw adjustment unit is as follows: S1. Flight environment data collection; S2, data processing matching operation; S3, target UAV yaw range adjustment operation; S4. Target UAV yaw discrimination analysis.

6. The artificial intelligence-based unmanned aerial vehicle operation positioning system according to claim 5, characterized in that: S1: Flight environment data collection: Obtain the flight environment data of the target UAV within the time threshold. The flight environment data includes the yaw interference value and the electromagnetic interference index.

7. The artificial intelligence-based unmanned aerial vehicle operation positioning system according to claim 6, characterized in that: S2. Data processing and matching operation: The yaw interference value and electromagnetic interference index are labeled as PG and DG respectively, and the yaw interference value PG and the electromagnetic interference index DG are substituted into the formula The flight interference assessment coefficient is obtained, wherein a1 and a2 are preset correction proportional factor coefficients of the yaw interference value and the electromagnetic interference index respectively, a3 is the preset error correction factor coefficient, a1=1.876, a2=1.263, and a3=2,116, G is the flight interference assessment coefficient, and the flight interference assessment coefficient G is compared and analyzed with the preset flight interference assessment coefficient interval stored internally, so as to obtain the flight interference assessment coefficient G in the corresponding preset flight interference assessment coefficient interval and set it as the yaw interference factor pz.

8. The artificial intelligence-based unmanned aerial vehicle operation positioning system according to claim 6, characterized in that: S3, target UAV yaw range adjustment operation: then matching the target UAV's allowable yaw range value according to the yaw interference factor pz; S4. Target UAV yaw discrimination analysis: The flight coordinates of the target UAV are obtained in real time, and the specified flight coordinates of the target UAV are obtained at the same time, and then the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is obtained, and the straight-line distance between the flight coordinates of the target UAV and the specified flight coordinates is set as the yaw flight distance, and the yaw flight distance is compared and analyzed with the allowable yaw range value of the target UAV: If the deviation flight distance is within the permissible deviation range of the target UAV, no signal is generated; If the yaw flight distance does not fall within the permissible yaw range value of the target UAV, a correction signal is generated.

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