A UAV flight status monitoring and early warning system

Abstract

The present invention relates to the technical field of drone status monitoring, and specifically to a drone flight status monitoring and early warning system. By monitoring the driving routes of drones, if there are abnormal driving routes, they are marked as abnormal drones, and the corresponding local routes are obtained, and when the local routes form a circular closed route, the detection path planning of the test drone is realized in combination with the detection range of the test drone; by comprehensively analyzing the anti-interference index, navigation error index, communication stability index and endurance time index of the test drone, the drone that can quickly and accurately monitor and identify the risk area is determined among a large number of test drones, thereby improving the monitoring efficiency and accuracy, so as to quickly construct the risk area and enable subsequent drones to avoid it, and ensure the safety of drones in the air.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) state monitoring, and in particular to an unmanned aerial vehicle (UAV) flight state monitoring and early warning system. Background Art

[0002] At present, drones can achieve unmanned intelligent flight by traveling along preset routes, including:

[0003] When the drones are flying along the route, if multiple drones have system failures, causing them to deviate from the preset route during flight, this is usually an area where there is environmental interference (such as electromagnetic interference) on the route. This situation will greatly affect the normal flight of the drone and cause greater safety hazards during the flight of the drone. Therefore, if this situation exists, how to detect the area with environmental interference in order to quickly and accurately determine the risk area where there is interference that affects the flight of the drone, and to avoid the risk area on the route to improve the subsequent safe flight of the drone is a problem that needs to be solved at present. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, the present invention provides a UAV flight status monitoring and early warning system, which can effectively solve the problem in the prior art that when the UAV is in a route deviation warning state, it is impossible to quickly and accurately locate the risk areas in the space that affect the flight of the UAV.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0006] The present invention provides a UAV flight status monitoring and early warning system, including an integrated management platform, and also including:

[0007] The trajectory monitoring module is used to monitor the drones that have deviated from the route and record them as abnormal drones, obtain the operating parameters of the abnormal drones, and if the operating parameters are in an abnormal state:

[0008] Obtain the local route that is offset from the abnormal UAV's route;

[0009] If there are multiple abnormal drones and the local routes correspond to multiple, and the multiple local routes form a circular closed route:

[0010] Create a circular closed route in a two-dimensional plane coordinate system and determine the coordinates of the center of the circular closed route Detection range with test drones , and construct multiple test routes in the circular closed route, thus, the detection endpoint coordinates of the distance test route are and the center coordinates No one has built a queue of tests to be assigned to the latest tests;

[0011] Also includes:

[0012] Allocation scheduling module, used to obtain the anti-interference index of the test drone in the test queue to be allocated , Navigation Error Index , Communication Stability Index And the battery life index , and get the test evaluation value of the test drone , the allocation scheduling module is based on the test evaluation value The target test drone is determined in the test queue to be assigned, and the test route is input to the target test drone for regional monitoring and early warning.

[0013] The test route is constructed as follows:

[0014] If there are multiple local routes, the multiple local routes form a circular closed route, and the circular closed route is at the same altitude coordinate:

[0015] Construct a circular closed route in a two-dimensional plane coordinate system and mark multiple endpoint coordinates at equal intervals on the circular closed route ;

[0016] Get the coordinates of the center of the circular closed route , clearly test the detection range of the drone ;

[0017] Based on the center coordinates Set a test guide line on the edge of the circular closed route to test the detection range of the drone. Input the coordinates of the center of the circle and test the drone and its detection range Perform linear movement along the test guide line;

[0018] Get the detection range The detection edge coordinates formed by the two sides in the two-dimensional plane , when the linear movement is completed, the coordinates of the detection endpoint on the circular closed route are obtained ;

[0019] Get the coordinates of the detection endpoints on both sides , get the coordinates of the two detection endpoints The range spacing between the detection endpoints is determined by the range spacing. Determine the coordinates of the next detection endpoint one by one , and use this cycle to obtain multiple detection endpoint coordinates ;

[0020] Based on the coordinates of the center of the circle in a closed circular route Respectively with the detection endpoint coordinates The connections are made to form a test guide line, and the test guide line is used to generate a test route.

[0021] When testing route construction:

[0022] Get the detection endpoint coordinates of the test route respectively and the center coordinates The nearest test drones are used to build test queues to be assigned with corresponding test drones.

[0023] The allocation and scheduling module includes:

[0024] Test status analysis unit, used to obtain the anti-interference index of the test drone in the test queue to be assigned , Navigation Error Index , Communication Stability Index And the battery life index , and normalize it to get the test evaluation value of the test drone , and its calculation formula is as follows:

[0025] Where: are the corresponding weight coefficients, and The sum is 1, is the number of evaluation items, which is preset to 4. is a constant correction factor.

[0026] Anti-interference index The calculation is performed according to the following steps:

[0027] Step 1: Obtain the flight stability index of the test drone ;

[0028] Step 2: Obtain the communication stability index of the test drone ;

[0029] Step 3: Obtain the navigation error index of the test drone ;

[0030] Step 4: Set the stability index , Navigation Error Index Communication Stability Index Normalization processing and calculation of anti-interference index .

[0031] Flight stability index The calculation formula is as follows:

[0032] Where: is the change in the yaw of the test drone in the i-th measurement, is the change in the pitch of the test drone in the i-th measurement, is the change in the roll angle of the test drone in the i-th measurement, is the change in the acceleration of the test drone in the i-th measurement, To test the maximum allowable change in the yaw of the drone, To test the maximum allowable change in the pitch of the drone, To test the maximum allowable change in the roll angle of the drone, To test the maximum allowable change in the acceleration of the drone, is the number of tests.

[0033] Communication stability index The calculation formula is as follows:

[0034] Where: is the normal holding time of the UAV communication link in the i-th measurement, is the packet loss rate of the UAV communication link tested in the i-th measurement, is the data transmission rate of the UAV communication link tested in the i-th measurement, is the number of tests.

[0035] Navigation Error Index The calculation formula is as follows:

[0036] Where: is the actual longitude of the test drone position in the i-th measurement, is the monitoring longitude obtained by testing the UAV navigation system in the i-th measurement, is the actual latitude of the test drone position in the i-th measurement, is the monitoring latitude obtained by testing the UAV navigation system in the i-th measurement, is the actual height of the test drone position in the i-th measurement, is the monitoring height obtained by testing the UAV navigation system in the i-th measurement, is the number of tests.

[0037] The allocation scheduling module also includes:

[0038] Determine the target judgment unit to obtain the test evaluation value of the test drone , according to the test evaluation value Sequence the test drones in the test queue to be assigned from high to low, obtain the preset test evaluation threshold, and convert the test evaluation values ​​less than the test evaluation threshold into Eliminate and test the evaluation value The highest one is recorded as the target test drone and the corresponding test route is input to it as the test target.

[0039] If, during the construction of the test guide line, there is a circular closed route with a remaining range spacing less than the coordinates of the two detection endpoints When the range of spacing is The detected edge coordinates on both sides And the detection endpoint coordinates Form a sector-shaped range area, with the sector-shaped range area along the center coordinates Construct an equally divided center line and use the equally divided center line to construct the central test route, where:

[0040] If there is a test queue to be assigned and it has been removed and there are no other test evaluation values , perform the following steps:

[0041] Determine whether the test queue to be allocated is the test queue to be allocated corresponding to the central test route. If so:

[0042] Then, the range areas detected by the test drones along the two test routes adjacent to the middle test route are obtained;

[0043] Determine whether there is an overlapping area when the two test drones detect along the test route. If there is an overlapping area, and the overlapping area covers the range area that needs to be detected by the middle test route, obtain the overlapping edge coordinates of the overlapping area and determine whether the overlapping edge coordinates are close to the center coordinates. Farthest, if:

[0044] Get the starting time when the detection range of the test drone on two adjacent test routes reaches the overlapping edge coordinates;

[0045] According to the preset driving speed and distance ratio calculation, obtain the test drone that can reach the coincident edge coordinates at the starting time, reconstruct the queue to be tested and execute the test evaluation value Calculation of

[0046] Thereby, the target test drone detected along the middle test route is re-determined by coinciding the edge coordinates.

[0047] Compared with the known prior art, the technical solution provided by the present invention has the following beneficial effects:

[0048] By monitoring the flight routes of the drones, if there are any abnormal flight routes, they are marked as abnormal drones, and the corresponding local routes are obtained. When the local routes form a circular closed route, the detection path planning of the test drone is realized in combination with the detection range of the test drone.

[0049] At the same time, through a comprehensive analysis of the test drone’s anti-interference index, navigation error index, communication stability index and endurance time index, the drone that can quickly and accurately monitor and identify risk areas is determined among a large number of test drones, thereby improving monitoring efficiency and accuracy, so that risk areas can be quickly constructed and subsequent drones can avoid them, ensuring the safety of drones in the air. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0053] The present invention will be further described below in conjunction with the embodiments.

[0054] Example 1 (reference Figure 1 ): A UAV flight status monitoring and early warning system, comprising at least:

[0055] The integrated management platform is used to supervise the drones in the supervision area. It should be noted that the supervision area is a preset range area, and the drones flying in this range area are subject to the status monitoring and control of the integrated management platform;

[0056] The trajectory monitoring module arranged in the integrated management platform is used to monitor the flight route of the UAV. If the UAV deviates from the flight route while flying on the preset flight route, that is, it does not navigate according to the preset flight route, an early warning response information is generated, and reaction margin information is generated thereby. The reaction margin information means that when a UAV deviates, another nearby UAV has an actual distance at which it can react to avoid the deviated UAV based on the coordinates of the deviated UAV, which is usually a preset value. Thus, the reaction margin information is output to other UAVs in flight, thereby ensuring the safe flight of the UAV.

[0057] Furthermore, after detecting a drone with a deviated route, the drone is recorded as an abnormal drone, and the operating parameters of the abnormal drone are obtained. The operating parameters include GPS signal data, flight attitude data, sensor data (gyroscope, acceleration, etc.) and communication data, and it is determined whether the operating parameters are in an abnormal state, wherein:

[0058] The abnormal state of GPS signal data refers to the sudden jump or loss of data;

[0059] The abnormal state of flight attitude data refers to the sudden climb, descent or yaw of the drone;

[0060] Abnormal state of sensor data refers to irregular fluctuations or abnormal values ​​in the readings of sensors such as gyroscopes and accelerometers;

[0061] The abnormal state of communication data refers to the detection of packet loss or increased error rate in the communication link;

[0062] If the above abnormal state exists, the flight state of the UAV is continuously monitored to obtain the local route where the UAV's flight route is deviated, and the area covered by the local route indicates that an abnormality exists.

[0063] It should be noted that if the above abnormal state exists and is not affected by other factors, it usually means that there is electromagnetic interference in the abnormal navigation area, but electromagnetic interference may exist in multiple areas. Therefore, if there are multiple abnormal drones, and each abnormal drone corresponds to a local route, the endpoints of multiple local routes (the starting point and the end point of the local route) are connected to form a circular closed route, and the circular closed route is at the same altitude coordinate:

[0064] Construct a circular closed route in a two-dimensional plane coordinate system at an equal scale, and mark the coordinates of multiple endpoints at equal intervals on the circular closed route ;

[0065] Get the coordinates of the center of the circular closed route , clearly test the detection range of the drone (maximum);

[0066] Based on the center coordinates Set a test guide line (connecting line) on the edge of the circular closed route to test the detection range of the drone. Input the coordinates of the center of the circle , and make it move linearly along the test guide line;

[0067] Thus, the detection range is obtained The detection edge coordinates formed by the two sides in the two-dimensional plane , and when the linear movement is completed (reaching the edge of the circular closed route), the coordinates of the detection endpoint on the circular closed route are obtained ;

[0068] Thus, the coordinates of the detection endpoints on both sides are obtained , get the coordinates of the two detection endpoints The range spacing between the detection endpoints is determined by the range spacing. Determine the coordinates of the next detection endpoint one by one , and by doing this cycle, you can get multiple detection endpoint coordinates ;

[0069] Based on the coordinates of the center of the circle in a closed circular route Respectively with the detection endpoint coordinates Connect the test guide line to form a coverage detection within the circular closed route, thereby generating a test route from the test guide line, and obtaining the detection endpoint coordinates from the test route respectively. and the center coordinates The nearest test drone (equipped with electromagnetic detection equipment for environmental detection), where the nearest test drone can be determined by setting a distance threshold, such as a distance threshold of 1km, etc., where the distance detection endpoint coordinates are determined and the center coordinates The nearest test drone refers to the test drone that is more convenient to reach the detection endpoint coordinates Or the center coordinates , and move along the test route to detect areas with electromagnetic interference to improve monitoring efficiency;

[0070] In the above, it should be noted that each time the coordinates of the center of the circle are used. Respectively with the detection endpoint coordinates Connect to form a test guide line. If, during the construction of the test guide line, the remaining range spacing on the circular closed route is smaller than the coordinates of the two previous detection endpoints, When the range spacing between (in this case, usually the starting detection endpoint coordinates and the end point coordinates of the probe The range spacing between two adjacent endpoint coordinates The distance between the two circles), at this time the coordinates of the center of the circle The detected edge coordinates on both sides And the detection endpoint coordinates A fan-shaped area (fan-shaped range area) smaller than the detection range of the test drone will be formed, and the fan-shaped area will be along the center coordinates Construct an equally divided center line, and construct a central test route with the equally divided center line, and move the test drone's detection range on the central test route. At this time, the test drone's detection range is in a state of partially covering the detection ranges of other test drones on both sides (and other test drones on both sides synchronously partially cover the detection range of the current test drone), that is, there are three test drones whose detection ranges partially overlap, including two test routes and the central test route;

[0071] The coordinates of the detection endpoint of the distance test route and the center coordinates The test drones corresponding to the nearest (usually set a threshold, such as 1km) respectively construct a test queue to be assigned, so as to obtain the test drones in the test queue to be assigned to the test route. By delineating the test route and assigning the corresponding test drones, the electromagnetic interference area can be quickly monitored and recorded to improve efficiency. In this regard, in order to assign sustainable and stable monitoring test drones to the test route, so as to further speed up the regional interference test efficiency and ensure the safe flight of the drone, it also includes:

[0072] Allocation scheduling module, which includes:

[0073] Test status analysis unit, used to obtain the anti-interference index of the test drone in the test queue to be assigned , Navigation Error Index , Communication Stability Index And the battery life index , and normalize it to get the test evaluation value of the test drone , and its calculation formula is as follows:

[0074] Where: are the corresponding weight coefficients, and The sum is 1, is the number of evaluation items, which is preset to 4. is a constant correction factor, where:

[0075] Anti-interference index The calculation is performed according to the following steps:

[0076] Step 1: Obtain the flight stability index of the test drone :

[0077] Where: is the change in the yaw of the test drone in the i-th measurement, is the change in the pitch of the test drone in the i-th measurement, is the change in the roll angle of the test drone in the i-th measurement, is the change in the acceleration of the test drone in the i-th measurement, To test the maximum allowable change in the yaw of the drone, To test the maximum allowable change in the pitch of the drone, To test the maximum allowable change in the roll angle of the drone, To test the maximum allowable change in the acceleration of the drone, It is the number of tests. It should be noted that in this solution, the number of tests obtained is the most recent test data (such as within a week), and is set to at least 3 times to reflect the actual test data of the test drone. According to the above, the yaw stability index, pitch stability index, roll angle stability index and acceleration stability index of the test drone are obtained respectively, so as to obtain the flight stability index of the test drone. ;

[0078] Step 2: Obtain the communication stability index of the test drone :

[0079] Where: is the normal maintenance time of the UAV communication link in the i-th measurement (obtained by subtracting the test time from the communication link interruption time each time), is the packet loss rate of the UAV communication link tested in the i-th measurement, is the data transmission rate of the UAV communication link tested in the i-th measurement, is the number of tests;

[0080] Step 3: Obtain the navigation error index of the test drone :

[0081] Where: is the actual longitude of the test drone position in the i-th measurement, is the monitoring longitude obtained by testing the UAV navigation system in the i-th measurement, is the actual latitude of the test drone position in the i-th measurement, is the monitoring latitude obtained by testing the UAV navigation system in the i-th measurement, is the actual height of the test drone position in the i-th measurement, is the monitoring height obtained by testing the UAV navigation system in the i-th measurement, is the number of tests;

[0082] Step 4: Set the stability index , Navigation Error Index Communication Stability Index Normalization processing and calculation of anti-interference index :

[0083] Where: The default value is 3 for the number of calculation items. is the weight coefficient, and The sum is 1, which is preset by the personnel. is the constant correction factor;

[0084] In the above scheme, the endurance index Calculate according to the following formula:

[0085] Where: is the power consumed by the test drone in the i-th measurement, is the initial power of the drone tested in the i-th measurement, To test the basic endurance of the drone, get, In order to test the environmental coefficient of the drone affected by the environment, the environmental coefficient is used to indicate the degree of influence of the environment on the basic endurance. Generally speaking, the environment includes temperature, humidity, and wind speed. If the endurance is reduced in an environment where the temperature is too high or too low, the humidity is too high or too low, or the wind speed is too high or too low, then they can be assigned a value of 1 respectively. The actual environmental coefficient is determined comprehensively according to the type of environment.

[0086] The target determination unit is used to obtain the test evaluation value corresponding to the test drone in the test queue to be assigned , thus, according to the test evaluation value The test drones in the test queue to be assigned are sequenced from high to low, and at the same time, a preset test evaluation threshold is obtained to convert the test evaluation values ​​less than the test evaluation threshold into Marking is performed, thereby obtaining the corresponding test drone and removing it from the test queue to be assigned, thereby marking the test evaluation value in the corresponding test queue to be assigned The highest one is recorded as the target test drone and the corresponding test route is input to it as the test target (distance detection endpoint coordinates and the center coordinates nearest) to facilitate identification and monitoring of navigation areas with abnormalities.

[0087] It should be noted that in the test queue to be assigned, if there are the same test evaluation values When the remaining battery power is greater, the one with the larger remaining battery power is recorded as the target test drone so that it can perform identification and monitoring operations.

[0088] It should be noted that in the above, if there is a test evaluation value that has been removed from the test queue to be assigned , then there are no other test evaluation values , it means that there is no test drone in the test queue to be assigned to the corresponding test route as the test target, so the following steps are performed:

[0089] Determine whether the test queue to be allocated is the test queue to be allocated corresponding to the central test route. If so:

[0090] Then, the range areas detected by the test drones along the two test routes adjacent to the middle test route are obtained;

[0091] Determine whether there is an overlapping area when the two test drones detect along the test route. If there is an overlapping area, and the overlapping area covers the range area that needs to be detected on the middle test route (the undetected area between the detection ranges corresponding to the test drones on the two adjacent test routes, due to the center coordinates of the circle As the center and the test drone moves outward along the center, when the two detection areas overlap, it is along the center coordinates of the circle. Expanding outward, so the overlap area initially covers the range area that needs to be detected by the central test route), then obtain the overlap edge coordinates of the overlap area (such as the intersection) and determine whether the overlap edge coordinates are close to the center coordinates Farthest, if:

[0092] Get the starting time when the detection range of the test drone on two adjacent test routes reaches the overlapping edge coordinates;

[0093] According to the preset driving speed and distance ratio, the test drone that can reach the coincident edge coordinates at the starting time is obtained. The arrival at the starting time can ensure that the detection efficiency of the circular closed route is not affected, and the queue to be tested is reconstructed and the test evaluation value is performed on it. Calculation of

[0094] Furthermore, the target test drone that can be detected along the middle test route by overlapping edge coordinates can be re-determined based on the above-mentioned target test drone determination method, so as to achieve comprehensive coverage interference monitoring and recording of the circular closed route, thereby improving the safety of other drones during driving.

[0095] Finally, it is worth mentioning that if the above-mentioned area detection of electromagnetic interference is completed by the target test drone, a risk area can be constructed based on the detection results to avoid subsequent drone flights, thereby improving the safety of drone flights.

[0096] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. A UAV flight status monitoring and early warning system, including an integrated management platform, characterized in that: Also includes: The trajectory monitoring module is used to monitor the drones that have deviated from the route and record them as abnormal drones, obtain the operating parameters of the abnormal drones, and if the operating parameters are in an abnormal state: Obtain the local route that is offset from the abnormal UAV's route; If there are multiple abnormal drones and the local routes correspond to multiple, and the multiple local routes form a circular closed route: Create a circular closed route in a two-dimensional plane coordinate system and determine the coordinates of the center of the circular closed route Detection range with test drones , and construct multiple test routes in the circular closed route, thus, the detection endpoint coordinates of the distance test route are and the center coordinates No one has built a queue of tests to be assigned to the latest tests; Also includes: Allocation scheduling module, used to obtain the anti-interference index of the test drone in the test queue to be allocated , Navigation Error Index , Communication Stability Index And the battery life index , and get the test evaluation value of the test drone , the allocation scheduling module is based on the test evaluation value The target test drone is determined in the test queue to be assigned, and the test route is input to the target test drone for regional monitoring and early warning.

2. The UAV flight status monitoring and early warning system according to claim 1 is characterized in that: The test route is constructed as follows: If there are multiple local routes, the multiple local routes form a circular closed route, and the circular closed route is at the same altitude coordinate: Construct a circular closed route in a two-dimensional plane coordinate system and mark multiple endpoint coordinates at equal intervals on the circular closed route ; Get the coordinates of the center of the circular closed route , clearly test the detection range of the drone ; Based on the center coordinates Set a test guide line on the edge of the circular closed route to test the detection range of the drone. Input the coordinates of the center of the circle and test the drone and its detection range Perform linear movement along the test guide line; Get the detection range The detection edge coordinates formed by the two sides in the two-dimensional plane , when the linear movement is completed, the coordinates of the detection endpoint on the circular closed route are obtained ; Get the coordinates of the detection endpoints on both sides , get the coordinates of the two detection endpoints The range spacing between the detection endpoints is determined by the range spacing. Determine the coordinates of the next detection endpoint one by one , and use this loop to get multiple detection endpoint coordinates ; Based on the coordinates of the center of the circle in a closed circular route Respectively with the detection endpoint coordinates The connections are made to form a test guide line, and the test guide line is used to generate a test route.

3. The UAV flight status monitoring and early warning system according to claim 2 is characterized in that: When the test route is constructed: Get the detection endpoint coordinates of the test route respectively and the center coordinates The nearest test drones are used to build test queues to be assigned with corresponding test drones.

4. The UAV flight status monitoring and early warning system according to claim 1 is characterized in that: The allocation scheduling module includes: Test status analysis unit, used to obtain the anti-interference index of the test drone in the test queue to be assigned , Navigation Error Index , Communication Stability Index And the battery life index , and normalize it to get the test evaluation value of the test drone , and its calculation formula is as follows: Where: are the corresponding weight coefficients, and The sum is 1, is the number of evaluation items, which is preset to 4. is a constant correction factor.

5. The UAV flight status monitoring and early warning system according to claim 4 is characterized in that: The anti-interference index The calculation is performed according to the following steps: Step 1: Obtain the flight stability index of the test drone ; Step 2: Obtain the communication stability index of the test drone ; Step 3: Obtain the navigation error index of the test drone ; Step 4: Set the stability index , Navigation Error Index Communication Stability Index Normalization processing and calculation of anti-interference index .

6. The UAV flight status monitoring and early warning system according to claim 5 is characterized in that: The flight stability index The calculation formula is as follows: Where: is the change in the yaw of the test drone in the i-th measurement, is the change in the pitch of the test drone in the i-th measurement, is the change in the roll angle of the test drone in the i-th measurement, is the change in the acceleration of the test drone in the i-th measurement, To test the maximum allowable change in the yaw of the drone, To test the maximum allowable change in the pitch of the drone, To test the maximum allowable change in the roll angle of the drone, To test the maximum allowable change in the acceleration of the drone, is the number of tests.

7. The UAV flight status monitoring and early warning system according to claim 6 is characterized in that: The communication stability index The calculation formula is as follows: Where: is the normal holding time of the UAV communication link in the i-th measurement, is the packet loss rate of the UAV communication link tested in the i-th measurement, is the data transmission rate of the UAV communication link tested in the i-th measurement, is the number of tests.

8. The UAV flight status monitoring and early warning system according to claim 1 is characterized in that: Said Navigation Error Index The calculation formula is as follows: Where: is the actual longitude of the test drone position in the i-th measurement, is the monitoring longitude obtained by testing the UAV navigation system in the i-th measurement, is the actual latitude of the test drone position in the i-th measurement, is the monitoring latitude obtained by testing the UAV navigation system in the i-th measurement, is the actual height of the test drone position in the i-th measurement, is the monitoring height obtained by testing the UAV navigation system in the i-th measurement, is the number of tests.

9. The UAV flight status monitoring and early warning system according to claim 2 is characterized in that: The allocation scheduling module also includes: Determine the target judgment unit to obtain the test evaluation value of the test drone , according to the test evaluation value Sequence the test drones in the test queue to be assigned from high to low, obtain the preset test evaluation threshold, and convert the test evaluation values ​​less than the test evaluation threshold into Eliminate and test the evaluation value The highest one is recorded as the target test drone and the test route is input to it.

10. The UAV flight status monitoring and early warning system according to claim 9, characterized in that: If, during the construction of the test guide line, there is a circular closed route with a remaining range spacing less than the coordinates of the two detection endpoints When the range of spacing is The detected edge coordinates on both sides And the detection endpoint coordinates Form a sector-shaped range area, with the sector-shaped range area along the center coordinates Construct an equally divided center line and use the equally divided center line to construct the central test route, where: If there is a test queue to be assigned and it has been removed and there are no other test evaluation values , perform the following steps: Determine whether the test queue to be allocated is the test queue to be allocated corresponding to the central test route. If so: Then, the range areas detected by the test drones along the two test routes adjacent to the middle test route are obtained; Determine whether there is an overlapping area when the two test drones detect along the test route. If there is an overlapping area, and the overlapping area covers the range area that needs to be detected by the middle test route, obtain the overlapping edge coordinates of the overlapping area and determine whether the overlapping edge coordinates are close to the center coordinates. Farthest, if: Get the starting time when the detection range of the test drone on two adjacent test routes reaches the overlapping edge coordinates; According to the preset driving speed and distance ratio calculation, obtain the test drone that can reach the coincident edge coordinates at the starting time, reconstruct the queue to be tested and execute the test evaluation value Calculation of Thereby, the target test drone detected along the middle test route is re-determined by coinciding the edge coordinates.

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