Fixed-wing unmanned aerial vehicle landing time prediction calculation method, system, equipment and medium

Abstract

The embodiment of the invention provides a fixed-wing unmanned aerial vehicle landing time prediction calculation method, system and device and a medium. The method comprises the following steps: acquiring a recovery waypoint coordinate and model data of an unmanned aerial vehicle; dividing landing route segments of the unmanned aerial vehicle according to the recovery route point coordinates, wherein the landing route segments comprise an entering segment, an approaching segment and a driving-out segment; according to the model data, time consumption of each landing route segment is reversely calculated; and accumulating the consumed time of each landing leg to obtain the total landing time of the unmanned aerial vehicle. According to the embodiment of the invention, the recovery time of the unmanned aerial vehicle is calculated in real time according to the recovery waypoint and the unmanned aerial vehicle performance simulation data set, the arrival time of each waypoint is given, and the height of each waypoint is used for reversely calculating the height reduction time, so that a user can master the recovery time of the unmanned aerial vehicle in real time; prediction assistance is provided for the landing time of the fixed-wing unmanned aerial vehicle in the airport, and particularly time reference is provided for large-scale landing of the unmanned aerial vehicle in the airport, so that timeliness and economy of the landing and recovery process of the unmanned aerial vehicle are facilitated.

Description

Technical Field

[0001] The embodiments of the present disclosure belong to the technical field of fixed-wing UAV landing time prediction, and specifically relate to a fixed-wing UAV landing time prediction calculation method, system, device and medium. Background Art

[0002] Drone recovery technology is a key link in drone mission execution, especially in logistics, emergency rescue, military reconnaissance and other scenarios. Accurate prediction of drone landing time is of great significance to mission scheduling efficiency, airspace resource allocation and safety assurance. Traditional methods usually make linear estimates based on the real-time position of drones and preset waypoints. However, due to factors such as dynamic changes in flight performance, multi-stage coordinated adjustments and complex environmental interference, prediction methods that rely solely on empirical models or static path planning often have problems such as insufficient accuracy and poor adaptability.

[0003] At present, the prediction of drone landing time mainly relies on two types of technologies: one is real-time position tracking based on GPS positioning and inertial navigation, combined with fixed waypoints to accumulate segmented time; the other is to train statistical models through historical flight data to predict the overall landing time.

[0004] However, the existing technology still has many defects, such as insufficient dynamic performance modeling, which does not fully consider the flight performance differences of different UAV models (such as turning radius, glide rate, taxiing speed, etc.), resulting in limited model generalization ability; lack of multi-stage collaborative calculation, and failure to adopt a reverse calculation mechanism to dynamically adjust the time consumption of each stage, making it difficult to cope with complex scenarios such as altitude layer switching, circling and lowering altitude, especially when there is a deviation between the actual altitude of the UAV and the theoretically calculated value, the problem of error accumulation at each level is significant; the data granularity is coarse. The traditional fitting data set uses a fixed altitude interval (such as above 500m), which cannot accurately match the refined altitude reduction requirements of the low-altitude approach phase, affecting the local accuracy of time prediction. Summary of the invention

[0005] The embodiments of the present disclosure aim to solve at least one of the technical problems existing in the prior art, and provide a method, system, device and medium for predicting and calculating the landing time of a fixed-wing unmanned aerial vehicle.

[0006] One aspect of the present disclosure provides a method for predicting and calculating the landing time of a fixed-wing UAV, the method comprising: Obtain the coordinates and model data of the recovery waypoints of the UAV; wherein the recovery waypoints include the current position of the UAV, the circling start and end points, the FAF circle entry point, the approach point and the touchdown point; and the model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set; Dividing the landing segment of the UAV according to the coordinates of the recovery waypoints, including an approach segment, an approach segment, and an exit segment; Reversely calculate the time taken for each landing segment according to the model data; The time consumed in each landing segment is accumulated to obtain the total landing time of the drone.

[0007] Furthermore, the approach section includes a pre-approach section, a circling and lowering section, a straight flight section, and a turning and lowering section in sequence; The reverse calculation of the time consumption of each landing segment according to the model data includes: According to the flight performance fitting data set, the altitude and time consumption of the turning and lowering section are calculated; According to the current position of the UAV and the lowering height of the turning lowering section, the lowering height and time consumption of the direct flight section are calculated; According to the current position of the UAV and the altitude reduction of the direct flight segment and the turning and lowering segment, the time consumption of the pre-approach segment and the circling and lowering segment is calculated; The time consumption of the pre-approach segment, the circling and altitude reduction segment, the direct flight segment and the turning and altitude reduction segment is accumulated to obtain the time consumption of the approach segment.

[0008] Furthermore, the calculating the lowering height and time consumption of the turning lowering section according to the flight performance fitting data set includes: Calculating the arc length of the FAF circle according to the recovery waypoint coordinates and the FAF circle center coordinates; Calculating the time consumption of the turning and lowering altitude segment according to the FAF circle arc length and the flight performance fitting data set; The height reduction of the turning and lowering section is obtained according to the time consumption of the turning and lowering section.

[0009] Furthermore, the calculating of the lowering height and time consumption of the direct flight segment according to the current position height of the drone and the lowering height of the turning lowering segment includes: Calculate the flight distance of the direct flight segment according to the current position of the drone and the altitude of the turning and lowering segment; Calculating the duration of the direct flight segment according to the flight distance of the direct flight segment and the flight performance fitting data set; According to the time consumed by the direct flight segment, the descent altitude of the direct flight segment is obtained.

[0010] Further, the time consumption of the pre-approach segment and the circling and lowering segment is calculated according to the current position altitude of the drone and the lowering altitude of the direct flight segment and the turning and lowering segment, including: Calculate the flight distance of the pre-approach segment according to the current position of the UAV and the altitude of the direct flight segment and the altitude reduction segment; Calculating the duration of the pre-approach segment according to the flight distance of the approach segment and the flight performance fitting data set; According to the time consumption of the pre-approach segment, an expected descent altitude of the pre-approach segment is obtained; Calculate the number of circles required for the drone to circle and descend with a minimum turning radius according to the current position of the drone, the expected descent height of the pre-approach segment, and the flight performance fitting data set; The number of revolutions is rounded off to obtain the required number of revolutions of the UAV in the hovering and descending stage; According to the difference between the number of circles and the number of full circles, time-consuming compensation of the circling and lowering section is performed; The height reduction of the circling and lowering section is obtained according to the time-consuming compensation of the circling and lowering section.

[0011] Furthermore, the reverse calculation of the time taken for each landing segment according to the model data includes: Obtain the distance to be flown from the approach point to the touchdown point, and the average time taken for the UAV to roll from landing to leaving the landing runway; According to the distance to be flown and the average speed of the approaching section of the UAV, the time taken by the UAV to fly from the approach point to the touchdown point is obtained; The time consumed from the approach point to the touchdown point and the average time consumed from the landing roll to the exit of the landing runway are accumulated to obtain the time consumed in the approach segment.

[0012] Furthermore, the reverse calculation of the time taken for each landing segment according to the model data includes: The average time taken for the UAV to stop on the taxiway from entering the connecting road is obtained, and the time taken for the exit section is obtained.

[0013] Another aspect of the present disclosure provides a fixed-wing UAV landing time prediction calculation system, the system comprising: An acquisition module is used to acquire the coordinates and model data of the recovery waypoints of the UAV; wherein the recovery waypoints include the current position of the UAV, the circling start and end points, the FAF circle entry point, the approach point and the touchdown point; and the model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set; A division module, used to divide the landing segment of the UAV according to the recovery waypoint coordinates, including an approach segment, an approach segment and an exit segment; A calculation module, used for reversely calculating the time consumption of each landing segment according to the model data; The accumulation module is used to accumulate the time consumed by each landing segment to obtain the total landing time of the drone.

[0014] Another aspect of the present disclosure provides an electronic device, characterized by comprising: at least one processor; and, The memory communicatively connected to the at least one processor is used to store one or more programs, and when the one or more programs are executed by the at least one processor, the at least one processor can implement the fixed-wing UAV landing time prediction calculation method described above.

[0015] Another aspect of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for predicting and calculating the landing time of a fixed-wing UAV.

[0016] A method, system, device and medium for predicting and calculating the landing time of a fixed-wing UAV according to an embodiment of the present disclosure can calculate the UAV recovery time in real time based on the recovery waypoints and the UAV performance simulation data set, can provide the estimated arrival time of each waypoint, and use the altitude of each waypoint to reversely calculate the time consumption for descending, so that the user can grasp the UAV recovery time in real time, provide prediction assistance for the landing time of fixed-wing UAVs at airports, and especially provide a time reference for large-scale landing of UAVs at airports, thereby contributing to the timeliness and economy of the UAV landing and recovery process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for predicting and calculating the landing time of a fixed-wing UAV according to an embodiment of the present disclosure is shown; Figure 2 This is a schematic diagram of the landing process of a fixed-wing UAV according to another embodiment of the present disclosure; Figure 3 This is a structural schematic diagram of a fixed-wing UAV landing time prediction and calculation system according to another embodiment of the present disclosure; Figure 4 The figure is a schematic diagram of the structure of an electronic device according to another embodiment of the present disclosure. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0019] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0020] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0021] It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another component. Therefore, the first component discussed below can be referred to as the second component without departing from the teachings of the concepts of the present disclosure. As used in this disclosure, the term "and / or" includes any one of the associated listed items and all combinations of one or more.

[0022] Those skilled in the art will appreciate that the drawings are merely schematic diagrams of example embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing the present disclosure, and therefore cannot be used to limit the protection scope of the present disclosure.

[0023] like Figure 1 As shown, an embodiment of the present disclosure provides a method for predicting and calculating the landing time of a fixed-wing UAV, the method comprising: Step S1, obtaining the recovery waypoint coordinates and model data of the UAV.

[0024] Specifically, the embodiment of the present disclosure adopts a precise approach method based on an equiangular route (FAF circle landing). FAF stands for Final Approach Fix, which is translated as the final approach fix point. According to known information such as airport information and FAF point location, it takes time to plan the process of the fixed-wing UAV from the current position through the FAF circle and FAF point to enter the approach phase, the approach phase, and the landing roll / exit phase.

[0025] References Figure 2The schematic diagram of the landing process of a fixed-wing UAV shown in the figure, the recovery waypoints specifically include the current position P1 of the UAV, the circling start and end points P2, the FAF circle entry point P3, the approach point P4 and the touchdown point P5. The recovery waypoint coordinates include at least the longitude, latitude and altitude of the current position P1 of the UAV. The model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set of the corresponding model of the UAV, wherein the flight performance fitting data set may include the minimum turning radius of the UAV, the average ground speed and average glide rate of direct flight at each altitude layer, and the average ground speed and average glide rate of circling at each altitude layer.

[0026] Step S2: dividing the landing segment of the UAV according to the coordinates of the recovery waypoints, including an approach segment, an approach segment, and an exit segment.

[0027] Specifically, Figure 2 As shown, the landing time estimation flight segment of the embodiment of the present disclosure is divided into three stages: the approach segment (P1 to P4), the approach segment (P4 to P5) and the exit segment (after P5). The approach segment can be further divided into the pre-approach segment from the current position of the drone P1 to the circling start and end point P2, the circling and lowering segment of the drone circling and lowering at the circling start and end point P2 (with a turning circle O1 of the minimum turning radius), the direct flight segment from the circling start and end point P2 to the FAF circle entry point P3 (the tangent of the turning circle O1 and the FAF circle O2), and the turning and lowering segment from the FAF circle entry point P3 to the approach point P4.

[0028] Step S3: reversely calculate the time consumption of each landing segment according to the model data.

[0029] Specifically, 1. Start with the turning and lowering phase, and reversely calculate the time consumption of the approach phase: ① Using the known coordinates of the FAF circle entry point P3, the approach point P4 and the center coordinates of the FAF circle O2, calculate their relative positions to the positive x The arc length is calculated by calculating the difference between the two angles. l 3. The specific formula is the difference between the two angles multiplied by the radius of the FAF circle; ② According to the model data of the drone, read the average ground speed and average gliding rate of the hovering drone at the approach point P4 altitude H4 altitude layer (select and use according to the flight performance fitting data set of each model of drone); ③ Reversely calculate the time required from the current altitude layer to the previous altitude layer. For example, if the altitude layer interval is 100m, the required time is 100m divided by the average gliding rate of hovering (m / s), recorded as t 41 , in seconds; then calculate t 41 The flight distance within the time is recorded as d1, and d1 and l 3; ④ If d1 ≥l 3, then stop the calculation, the required time t 41 Updated to t4= l 3 / The average ground speed of the drone at this altitude; if d1< l 3. Repeat the calculation in step ③ above until the cumulative flight distance d1 is greater than or equal to the arc length. l 3; ⑤ Calculate the altitude of the turning and lowering phase based on the flight time t4, and inversely deduce the altitude H3 of the FAF circle entry point P3.

[0030] 2. Then calculate the duration of the direct flight: 1. Compare the height H3 of the FAF circle entry point P3 with the current height H1 of the drone. If H1≤H3, then set H3=H1, H2=H1. At this time, the approach height requirement can be met by only lowering the altitude during the turn. The subsequent flight segments are no longer calculated. The flight distance of the direct flight segment is l 2 is 0.

[0031] 2. Compare the height H3 of the FAF circle entry point P3 with the current height H1 of the drone. If H1>H3, then: ① Keep the height H3 value of the FAF circle entry point P3 unchanged; ② Read the average ground speed and average glide rate of the direct flight of this type of drone at the H3 altitude layer (can be selected based on the flight performance fitting data set of each type of drone); ③ Calculate the flight distance of the direct flight segment l 2. Reverse the time required to fly from altitude H3 to the previous altitude layer. For example, if the altitude layer interval is 1000m, the time required is 1000m / the average descent rate of the drone in direct flight at that altitude layer (m / s), recorded as t 31 , unit is s; calculation time t 31 The flight distance d2 of the drone inside the aircraft, and judge whether d2 is l 2; ④ If d2≥ l 2, then stop the calculation, time t 31 Updated to t3= l 2 / The average ground speed of the drone in direct flight at this altitude; if d2< l 2, then continue to repeat the calculation in step ③ above until the cumulative flight distance d2 is greater than or equal to l 2; ⑤ Calculate the descent altitude of the direct flight segment based on the flight time t3 of the direct flight segment, and inversely deduce the altitude H2 of the circling start and end points P2.

[0032] 3. Then calculate the time taken for the pre-approach phase and the circling and descending phase: 1. Compare the height H2 of the circling start and end point P2 with the current height H1 of the drone. If H1≤H2, set H2=H1. At this time, the approach height requirement can be met by only lowering the height in the straight flight segment plus the height in the turning segment. The flight distance in the circling segment is 0, and the pre-approach segment is no longer calculated.

[0033] 2. Compare the height H2 of the circling start and end point P2 with the current height H1 of the drone. If H1>H2, then: ① Keep the height H2 of the circling start and end point P2 unchanged; ② Take the average circling ground speed and average circling glide rate of the drone in the H2 altitude layer; ③ Calculate the flight distance of the pre-approach segment l 1. Reverse the time required to reach the previous altitude layer from altitude H2, taking the altitude layer interval as 1000m, the required time t 11 =1000 / the average gliding rate of the drone at this altitude, in seconds; calculation time t 11 The flight distance d1 within the range is determined by comparing d1 with l 1; ④ If d1≥ l 1, then stop the calculation, time t 11 Updated to t1= l 1 / average ground speed of the UAV at the altitude level; if d1< l 1, then continue to repeat the calculation in step ③ until the cumulative flight distance is greater than or equal to l 1; ⑤ Calculate the descent height of the pre-approach phase based on the flight time t1, and infer the expected height H of the current position P1 of the drone 11 .

[0034] 3. Compare the expected height H of the drone’s current position P1 11 and the current height of the drone H1, if H1≤H 11 , then let H 11 =H1, that is, the altitude remains unchanged. At this time, the approach altitude requirement can be met only by reducing the altitude during the pre-approach segment, the straight flight segment, and the turning and lowering segment. The flight distance of the circling and lowering segment is 0 and is no longer calculated.

[0035] 4. Compare the expected height H of the drone’s current position P1 11 and the current height of the drone H1, if H1>H 11 , then: ①The expected height H 11 The value of H remains unchanged; ② Take 11 The average ground speed and average glide rate of the drone within the altitude layer; ③ Reverse calculation from the expected altitude H 11 The time required to reach the next altitude is t 21 The calculation method is the same as step ③ in step 2. above, and will not be repeated here; according to time t 21 Calculated from the expected height H 11 The flight distance to the next altitude layer is denoted as d 21 , and calculate the number of circles required for the drone to hover and descend with the minimum turning radius r, recorded as a1, and the calculation formula is the flight distance d 21 / Minimum turning circumference; ④Continue to push back until the altitude reaches the current altitude H1 of the drone, and obtain the accumulated time t2_tem and accumulated flight distance l 11 , the cumulative number of circling circles a0; at this time, the cumulative number of circling circles a0 is not an integer, and a0 is rounded off and recorded as a; ⑤ If 0<(a0-a)≤0.5, time compensation needs to be added to the cumulative time t2_tem. The compensation time is the time required to fly (a0-a) circles at the minimum turning radius r at the H2 altitude layer, recorded as t 20 , at this time t2=t2_tem+t 20 ; If 0<(a-a0)<0.5, then time compensation needs to be subtracted from the accumulated time t2_tem. The compensation time is the time required for the drone to fly (a-a0) circles at the minimum turning radius r at the H2 altitude layer, recorded as t 20 , at this time t2=t2_tem-t 20 ⑥ Perform altitude compensation in the H2 altitude layer, and the compensation altitude value is t 20 The product of the average glideslope rate of the UAV in the H2 altitude layer is used to update the altitude H2 of the circling start and end point P2.

[0036] At this point, the time consumed by the pre-approach segment, circling and lowering segment, direct flight segment, and turning and lowering segment calculated in the above process is accumulated to obtain the time consumed by the entire approach segment T1=t4+t3+t2+t1, and the final approach time is calculated at the same time.

[0037] 4. Calculate the time taken to enter the near section: ① Calculate the distance the drone needs to fly from approach point P4 and touchdown point P5 l 5, thereby inferring the time t5 taken by the drone from the approach point to the touchdown point = l 5 / the average speed of the approach phase of the UAV; ② read the landing roll performance fitting data set in the UAV model data to obtain the average time t6 from the landing roll to driving out of the landing runway; ③ calculate the time T2= t5+ t6 of the approach phase, so as to obtain the final touchdown time and final approach time of the UAV.

[0038] 5. Calculate the time taken to exit the section: ① Read the model data of the UAV and obtain the average time t7 from entering the connecting road to stopping on the taxiway; ② Get the time T3 = t7 for the exit section, and thus obtain the time of completion of exit.

[0039] Step S4: accumulating the time consumed by each landing segment to obtain the total landing time of the drone.

[0040] Specifically, the approach phase time T1, the approach phase time T2, and the exit phase time T3 calculated in the previous step S3 are accumulated to obtain the total landing time of the UAV T= T1+ T2+ T3.

[0041] A method for predicting and calculating the landing time of a fixed-wing UAV in an embodiment of the present disclosure can calculate the UAV recovery time in real time based on the recovery waypoints and the UAV performance simulation data set, and can provide the estimated arrival time of each waypoint, and use the altitude of each waypoint to reversely calculate the time consumption for descending, so that the user can grasp the UAV recovery time in real time, and provide prediction assistance for the landing time of fixed-wing UAVs at airports, especially providing a time reference for large-scale landing of UAVs at airports, thereby contributing to the timeliness and economy of the UAV landing and recovery process.

[0042] like Figure 3 As shown, another embodiment of the present disclosure provides a fixed-wing UAV landing time prediction calculation system, the system comprising: The acquisition module 310 is used to acquire the coordinates and model data of the recovery waypoints of the UAV; wherein the recovery waypoints include the current position of the UAV, the circling start and end points, the FAF circle entry point, the approach point and the touchdown point; and the model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set; A division module 320 is used to divide the landing segment of the UAV according to the recovery waypoint coordinates, including an approach segment, an approach segment and an exit segment; A calculation module 330, configured to reversely calculate the time taken for each landing segment according to the model data; The accumulation module 340 is used to accumulate the time consumed by each landing segment to obtain the total landing time of the drone.

[0043] Specifically, a fixed-wing UAV landing time prediction calculation system of an embodiment of the present disclosure is used to implement the fixed-wing UAV landing time prediction calculation method described in the above embodiments. The specific implementation process has been described in detail in the above embodiments and will not be repeated here.

[0044] A fixed-wing UAV landing time prediction and calculation system according to an embodiment of the present disclosure can calculate the UAV recovery time in real time based on the recovery waypoints and the UAV performance simulation data set, can provide the estimated arrival time of each waypoint, and use the altitude of each waypoint to reversely calculate the time consumption for descending, so that the user can grasp the UAV recovery time in real time, and provide prediction assistance for the landing time of fixed-wing UAVs at airports, especially providing a time reference for large-scale landing of UAVs at airports, thereby contributing to the timeliness and economy of the UAV landing and recovery process.

[0045] like Figure 4As shown, another embodiment of the present disclosure provides an electronic device, including: At least one processor 401; and a memory 402 communicatively connected to the at least one processor 401, for storing one or more programs, which, when executed by the at least one processor 401, enables the at least one processor 401 to implement the fixed-wing UAV landing time prediction calculation method described above.

[0046] The memory 402 and the processor 401 are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors 401 and the memory 402 together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor 401 is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor 401.

[0047] The processor 401 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 402 can be used to store data used by the processor 401 when performing operations.

[0048] Yet another embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for predicting and calculating the landing time of a fixed-wing UAV.

[0049] The computer-readable storage medium may be included in the system or electronic device of the present disclosure, or may exist independently.

[0050] Computer-readable storage media may be any tangible media that contains or stores a program, which may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, optical fiber, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0051] The computer-readable storage medium may also include a data signal propagated in baseband or as part of a carrier wave, in which the computer-readable program code is carried. Specific examples include but are not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0052] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present disclosure, but the present disclosure is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and substance of the present disclosure, and these modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A method for predicting the landing time of a fixed-wing unmanned aerial vehicle, characterized in that: The method comprises: Obtain the coordinates and model data of the recovery waypoints of the UAV; wherein the recovery waypoints include the current position of the UAV, the circling start and end points, the FAF circle entry point, the approach point and the touchdown point; and the model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set; Dividing the landing segment of the UAV according to the coordinates of the recovery waypoints, including an approach segment, an approach segment, and an exit segment; Reversely calculate the time taken for each landing segment according to the model data; The time consumed in each landing segment is accumulated to obtain the total landing time of the drone.

2. The method according to claim 1, characterized in that The approach section includes the pre-approach section, the circling and altitude reduction section, the straight flight section and the turning and altitude reduction section in sequence; The reverse calculation of the time consumption of each landing segment according to the model data includes: According to the flight performance fitting data set, the altitude and time consumption of the turning and lowering section are calculated; According to the current position of the UAV and the lowering height of the turning lowering section, the lowering height and time consumption of the direct flight section are calculated; According to the current position of the UAV and the altitude reduction of the direct flight segment and the turning and lowering segment, the time consumption of the pre-approach segment and the circling and lowering segment is calculated; The time consumption of the pre-approach segment, the circling and altitude reduction segment, the direct flight segment and the turning and altitude reduction segment is accumulated to obtain the time consumption of the approach segment.

3. The method according to claim 2, characterized in that The step of calculating the lowering height and time consumption of the turning and lowering section according to the flight performance fitting data set includes: Calculating the arc length of the FAF circle according to the recovery waypoint coordinates and the FAF circle center coordinates; Calculating the time consumption of the turning and lowering altitude segment according to the FAF circle arc length and the flight performance fitting data set; The height reduction of the turning and lowering section is obtained according to the time consumption of the turning and lowering section.

4. The method according to claim 2, characterized in that: The step of calculating the lowering height and time consumption of the direct flight segment according to the current position height of the drone and the lowering height of the turning lowering segment includes: Calculate the flight distance of the direct flight segment according to the current position of the drone and the altitude of the turning and lowering segment; Calculating the duration of the direct flight segment according to the flight distance of the direct flight segment and the flight performance fitting data set; According to the time consumed by the direct flight segment, the descent altitude of the direct flight segment is obtained.

5. The method according to claim 2, characterized in that: The calculating the time consumption of the pre-approach segment and the circling and lowering segment according to the current position altitude of the drone and the lowering altitude of the direct flight segment and the turning and lowering segment includes: Calculate the flight distance of the pre-approach segment according to the current position of the UAV and the altitude of the direct flight segment and the altitude reduction segment; Calculating the duration of the pre-approach segment according to the flight distance of the approach segment and the flight performance fitting data set; According to the time consumption of the pre-approach segment, an expected descent altitude of the pre-approach segment is obtained; Calculate the number of circles required for the drone to circle and descend with a minimum turning radius according to the current position of the drone, the expected descent height of the pre-approach segment, and the flight performance fitting data set; The number of revolutions is rounded off to obtain the required number of revolutions of the UAV in the hovering and descending stage; According to the difference between the number of circles and the number of full circles, time-consuming compensation of the circling and lowering section is performed; The height reduction of the circling and lowering section is obtained according to the time-consuming compensation of the circling and lowering section.

6. The method according to any one of claims 1 to 5, characterized in that: The reverse calculation of the time consumption of each landing segment according to the model data includes: Obtain the distance to be flown from the approach point to the touchdown point, and the average time taken for the UAV to roll from landing to leaving the landing runway; According to the distance to be flown and the average speed of the approaching section of the UAV, the time taken by the UAV to fly from the approach point to the touchdown point is obtained; The time consumed from the approach point to the touchdown point and the average time consumed from the landing roll to the exit of the landing runway are accumulated to obtain the time consumed in the approach segment.

7. The method according to any one of claims 1 to 5, characterized in that: The reverse calculation of the time consumption of each landing segment according to the model data includes: The average time taken for the UAV to stop on the taxiway from entering the connecting road is obtained, and the time taken for the exit section is obtained.

8. A fixed-wing UAV landing time prediction and calculation system, characterized in that: The system comprises: An acquisition module is used to acquire the coordinates and model data of the recovery waypoints of the UAV; wherein the recovery waypoints include the current position of the UAV, the circling start and end points, the FAF circle entry point, the approach point and the touchdown point; and the model data includes the flight performance fitting data set, the landing roll performance fitting data set and the exit performance fitting data set; A division module, used to divide the landing segment of the UAV according to the recovery waypoint coordinates, including an approach segment, an approach segment and an exit segment; A calculation module, used for reversely calculating the time consumption of each landing segment according to the model data; The accumulation module is used to accumulate the time consumed by each landing segment to obtain the total landing time of the drone.

9. An electronic device, characterized in that: include: at least one processor; as well as, A memory communicatively connected to the at least one processor, for storing one or more programs, which, when executed by the at least one processor, enables the at least one processor to implement the fixed-wing UAV landing time prediction calculation method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the fixed-wing UAV landing time prediction calculation method according to any one of claims 1 to 7 is implemented.

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