CN116030664A - Low-altitude flight collision early warning method, device, equipment and medium based on grid - Google Patents
Low-altitude flight collision early warning method, device, equipment and medium based on grid Download PDFInfo
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Abstract
The embodiment of the disclosure provides a low-altitude flight collision early warning method, device, equipment and medium based on grids, which are applied to the technical field of track planning. The method comprises the steps of obtaining flight information of a current flight target, wherein the flight information comprises flight time information and flight track information; selecting a corresponding flight track point according to the flight time information and the flight track information; predicting the next flight position of the current flight target according to the flight track point; determining a 3D grid corresponding to the next flight position; and responding to the existence of other flying targets in the 3D grid, and performing collision early warning. In this way, the method can realize the advanced calculation of the distance, the prediction of the flight path and the planning of the decision-making follow-up flight path, effectively avoid the occurrence of air accidents, solve the problem of overtime of the prediction result caused by the delay of transmission data and improve the prediction efficiency.
Description
Technical Field
The disclosure relates to the technical field of track planning, in particular to a low-altitude flight collision early warning method, device, equipment and medium based on grids.
Background
With more and more flight targets in a low-altitude airspace, collision detection methods for the flight targets are more and more, the collision detection of the targets is mainly based on the fact that the targets send real-time position information including longitude, latitude, altitude and other information of current flight to a ground receiving station through Beidou, ADS-B and other means in the real-time flight process, and after the ground receiving station receives the position information, calculation and analysis are carried out based on the position information, so that whether the targets collide or not is determined. There are various conventional collision detection methods, but a method of setting a protection area around a target is mainly adopted. The method for setting the protection area around the target is that the protection area is set around the target, the protection area is a cylinder, a collision detection module is set in the target, the collision detection module detects whether a target aircraft enters or will enter the local protection area, if the target aircraft enters or will enter the local protection area, the alarm module is started to send out an alarm signal, the threshold time of the target aircraft entering the local protection area is T, and the detection module is used for detecting whether the target aircraft enters or will enter the local protection area, so that a pilot can know the possibility of collision and collision of the aircraft earlier, and timely adjusts the flight scheme to avoid the collision.
However, for a target flying at high speed in the air, the time the target location is reported to the ground station is delayed, that is, the received location is the location through which the target has flown, and the result of calculation and detection based on the location that has passed is delayed and inaccurate. Further, assuming that there are n aircraft in the current airspace, if the safe distance is determined by the aircraft distance, n× (n-1)/2 times of calculation is required, and the calculation amount is huge and the efficiency is low.
Disclosure of Invention
The disclosure provides a low-altitude flight collision early warning method, device, equipment and medium based on grids.
According to a first aspect of the present disclosure, a grid-based low-altitude flight collision warning method is provided. The method comprises the following steps:
acquiring flight information of a current flight target, wherein the flight information comprises flight time information and flight track information;
selecting a corresponding flight track point according to the flight time information and the flight track information;
predicting the next flight position of the current flight target according to the flight track point;
determining a 3D grid corresponding to the next flight position;
and responding to the existence of other flying targets in the 3D grid, and performing collision early warning.
Further, the selecting a corresponding flight trajectory point according to the flight time information and the flight trajectory information includes:
acquiring current flight time information of the current flight target;
and selecting flight track points of the first n moments of the current flight moment information, wherein n is a positive integer.
Further, the predicting the next flight position of the current flight target according to the flight track point includes:
predicting the next flight distance of the current flight target according to the distance values of the flight track points at the previous n moments;
predicting the next flight angle of the current flight target according to the angle offset of the flight track points at the previous n moments;
determining a next flight trajectory point of the current flight target according to the next flight distance and the next flight angle;
and taking the next flight track point as the next flight position of the current flight target.
Further, the method further comprises:
acquiring weather information of a 3D grid;
calculating a weather comprehensive index evaluation score value based on the weather information;
responding to the weather comprehensive index evaluation score value being more than or equal to a preset threshold value, and adjusting the next flight distance and/or the next flight angle;
and re-determining the next flight position of the current flight target.
Further, the next flight location includes corresponding longitude, latitude, and altitude information, and the determining the 3D grid corresponding to the next flight location includes:
according to the longitude, latitude and altitude information and a preset 3D grid side length, respectively calculating to obtain three-dimensional coordinate values corresponding to the next flight position;
mapping the three-dimensional coordinate values into the preset 3D grids, and determining the 3D grids corresponding to the next flight position.
Further, the responding to the existence of other flying targets in the 3D grid, performing collision early warning, includes:
responding to the existence of other flying targets in the 3D grid, and adjusting the take-off time of the flying targets based on the flying time information and the flying target information with collision danger;
and/or the number of the groups of groups,
the flying height of the flying object is adjusted based on flying height information and flying object information that are in danger of collision.
Further, the method further comprises:
and re-predicting the flying collision based on the adjusted take-off moment and/or the adjusted flying height.
According to a second aspect of the present disclosure, a low-altitude flight collision warning device based on a grid is provided. The device comprises:
the flight information acquisition module is used for acquiring flight information of the current flight target, wherein the flight information comprises flight time information and flight track information;
the track point selection module is used for selecting a corresponding flight track point according to the flight time information and the flight track information;
the flight position prediction module is used for predicting the next flight position of the current flight target according to the flight track point;
the grid determining module is used for determining a 3D grid corresponding to the next flight position;
and the collision early warning module is used for responding to the existence of other flying targets in the 3D grid and carrying out collision early warning.
According to a third aspect of the present disclosure, an electronic device is provided. The electronic device includes: a memory and a processor, the memory having stored thereon a computer program, the processor implementing the method as described above when executing the program.
According to a fourth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method according to the first aspect of the present disclosure.
The embodiment of the disclosure provides a low-altitude flight collision early warning method, a device, equipment and a medium based on grids, which can realize the advanced calculation of distance and the prediction of flight track by acquiring the flight time information and the flight track information of a current flight target, selecting a corresponding flight track point according to the flight time information and the flight track information, and predicting the next flight position of the current flight target according to the flight track point; the 3D grid corresponding to the next flight position is determined, the calculation times for simultaneously predicting a plurality of flight targets can be reduced through the form of the 3D grid, and the calculation efficiency is improved; in response to the existence of other flight targets in the 3D grid, collision early warning is carried out, so that a collision result can be obtained only by judging whether two or more aircrafts exist in the same grid, a subsequent flight path can be planned and decided in time, and the occurrence of an air accident is effectively avoided.
It should be understood that what is described in this summary is not intended to limit the critical or essential features of the embodiments of the disclosure nor to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following description.
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The above and other features, advantages and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. For a better understanding of the present disclosure, and without limiting the disclosure thereto, the same or similar reference numerals denote the same or similar elements, wherein:
FIG. 1 illustrates a flow chart of a grid-based low-altitude flight collision warning method according to an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a grid-based low-altitude flight collision warning method according to yet another embodiment of the present disclosure;
FIG. 3 illustrates a schematic diagram of a grid-based low-altitude flight collision warning method according to yet another embodiment of the present disclosure;
FIG. 4 illustrates a 3D mesh structure schematic of a mesh-based low-altitude flight collision warning method according to yet another embodiment of the present disclosure;
FIG. 5 illustrates a flow chart of a grid-based low-altitude flight collision warning method in accordance with yet another embodiment of the present disclosure;
FIG. 6 illustrates a block diagram of a grid-based low-altitude flight collision warning device, in accordance with an embodiment of the present disclosure;
fig. 7 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are some embodiments of the present disclosure, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments in this disclosure without inventive faculty, are intended to be within the scope of this disclosure.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
The embodiment of the disclosure provides a grid-based low-altitude flight collision early warning method, device, equipment and medium, which can be used for predicting whether a current flight target has collision danger when flying according to a predicted flight track, and can also be used for simultaneously predicting collision conditions among a plurality of flight targets when the current airspace has the plurality of flight targets. The grid-based low-altitude flight collision early warning method is taken as an example of one of the flight targets, and is also applicable to other flight targets, and is not limited herein.
Fig. 1 illustrates a flowchart of a grid-based low-altitude flight collision warning method 100, according to an embodiment of the present disclosure. The method 100 comprises the following steps:
In some embodiments, time-of-flight information and flight trajectory information of a flying target to be predicted are obtained. The flying object may be various aircrafts capable of performing controllable flying in the atmosphere, including an airplane, a sensing aircraft, an aerial craft, a water craft and the like. The flight information of the flight target can be obtained through the travel tracks and corresponding time information of all low-altitude aircrafts running currently and uploaded to the computer by being arranged on a ground base station, and the travel tracks and corresponding time information of the aircrafts can be collected through the airborne sensors of the aircrafts in a flight state, such as radar, laser, cameras, thermal infrared imagers and the like and uploaded to the computer.
And 120, selecting a corresponding flight trajectory point according to the flight time information and the flight trajectory information.
In some embodiments, selecting the flight trajectory point may be accomplished by:
acquiring current flight time information of the current flight target;
and selecting flight track points of the first n moments of the current flight moment information, wherein n is a positive integer.
For example, 6 track points of the latest flight at the current flight time of 10:00 are selected, wherein the selection of the 6 track points may be selecting corresponding flight positions according to a preset time interval (for example, 5 minutes), that is, selecting flight positions corresponding to the flight times of 9:55, 9:50, 9:45, 9:40, 9:35, and 9:30; the corresponding flight position can be selected according to a preset flight distance interval (for example, 1000 meters); the selection can be performed by combining a preset time interval and a preset flight distance interval; the selected preset time interval and/or flight distance interval of each track point is set according to actual practice, and is not necessarily set to be a unified and unchanged value, and when the influence and fluctuation of real-time flight conditions are considered, the influence of the same climate and environment factors with larger prediction gap in the past is caused, dense acquisition points are needed, so that the prediction accuracy is improved. For example, between 6 track points selected in the same group, the track points are selected according to different time intervals, namely, between the 1 st point and the 2 nd point, the track points are selected according to 5-minute time intervals, between the 2 nd point and the 3 rd point, the track points are selected according to 6-minute time intervals … …, and similarly, between 6 track points selected in the same group, the track points can also be selected according to different flight distance intervals; in addition, the track points may be selected by combining a preset time interval and a preset flight distance interval, for example, the 1 st point and the 2 nd point are selected according to a preset time interval, and the 2 nd point and the 3 rd point are selected according to a preset flight distance interval. It should be noted that, for the examples of the data, the adjustment may be performed according to the actual situation, and is not limited by the examples. The selection rules are adjusted in real time to adapt to changeable environments and scenes, so that the prediction result is more accurate, and the result is fed back in real time to make adjustment in time.
And step 130, predicting the next flight position of the current flight target according to the flight track point.
In some embodiments, one of the flight positions is predicted, and the next flight position is predicted by the flight trajectory point, which is implemented by the following steps, as shown in fig. 2, specifically including:
And 220, predicting the next flight angle of the current flight target according to the angle offset of the flight track points at the previous n moments.
And 230, determining a next flight trajectory point of the current flight target according to the next flight distance and the next flight angle.
And step 240, taking the next flight trajectory point as the next flight position of the current flight target.
In some embodiments, fig. 3 shows a schematic diagram of selecting corresponding flight positions at preset time intervals of 5 minutes, namely selecting 7 th, 8 th and 9 th flight positions according to flight positions corresponding to flight moments of 9:55, 9:50, 9:45, 9:40, 9:35 and 9:30. Let the distance from each track point to the previous track point be s 1 -s 6 Then by solving for s 1 -s 6 The 7 th flight distance s can be obtained from the average travel distance of (2) 7 The method comprises the steps of carrying out a first treatment on the surface of the Setting the angle offset alpha of the 1 st and 6 th points 1 Then the 7 th point is offset by an angle alpha 1 6; finally, according to the predicted s 7 And alpha 1 And/6 determining the specific position of the 7 th point as the next flight position. Similarly, the 8 th and 9 th flight positions are predicted: s-solving 2 -s 7 、s 3 -s 8 Can obtain the distance s between the 8 th and 9 th points 8 Sum s 9 The method comprises the steps of carrying out a first treatment on the surface of the The offset angles of the 8 th and 9 th points are respectively 2 nd and 7 th points are alpha 2 The offset angle of the (6), (3) th and (8) th points is alpha 3 6, wherein alpha 2 Represents the angular offset, alpha, of the 2 nd and 7 th points 3 Indicating the angular offset of the 3 rd and 8 th points; and then determining the 8 th and 9 th flight positions … … according to the predicted distance and the deviation angle, predicting the flight track according to the analysis results of the distance and the angle, performing collision analysis according to the predicted flight track instead of performing collision analysis according to the position through which the target has flown, reducing the time delay for calculating the flight position reported to the ground station by the flying target, and improving the prediction efficiency. It should be noted that the requirements can be set according to the actual requirementsThe number of predicted flight positions is not limited to the 3 th, 8 th and 9 th predicted flight positions of the above example.
In some embodiments, when the aircraft flies through the 7 th flight position, the predicted flight position of the 7 th point can be compared with the actual flight position data, and when the predicted flight position is greater than or equal to a preset safety range, the flight positions of the 8 th and 9 th … … nth points can be predicted again according to the actual flight position data so as to improve the accuracy of the flight position prediction.
And 140, determining a 3D grid corresponding to the next flight position.
In some embodiments, determining the 3D grid corresponding to the next flight position by the predicted next flight position may be achieved by:
according to the longitude, latitude and altitude information and a preset 3D grid side length, respectively calculating to obtain three-dimensional coordinate values corresponding to the next flight position;
mapping the three-dimensional coordinate values into the preset 3D grids, and determining the 3D grids corresponding to the next flight position.
In some embodiments, assuming that the safety distance between the aircrafts is a, then taking the intersection point of the equator and the primary meridian as the starting point to perform 3D grid space subdivision with the side length of a, and the first layer of grid labels are K 111 、K 112 、K 113 …K 11n …K 1nn The method comprises the steps of carrying out a first treatment on the surface of the The second layer of grid label is K 211 、K 212 、K 213 …K 21n …K 2nn The n-th layer grid label is K n11 、K n12 、K n13 …K n1n …K nnn . Meanwhile, the conversion relation between longitude and latitude and distance is as follows: in the case of equal latitude, the distances differ by 10000 meters every 0.1 °, and in the case of equal longitude, the distances are 11132 meters every 0.1 °. Therefore, the points in the 3D grid have a corresponding relation with longitude and latitude. And obtaining the corresponding relation between the aircraft and the 3D grid through the longitude and latitude height data returned by the aircraft.
In some embodiments, as shown in FIG. 4, in two flightsCollision analysis of targets is illustrated. Let the longitude and latitude heights of the flying object 1 and the flying object 2 be (a) 1 ,b 1 ,c 1 )、(x 1 ,y 1 ,z 1 ) Then the transverse-longitudinal distance between the flying object 1 and the origin is d 1 =100000×a 1 ，d 2 =111320×b 1 The corresponding trellis code is t 1 =100000×a 1 /a，t 2 =111320×b 1 /a，t 3 =c 1 . The network code corresponding to the flying object 2 is t 1 =100000×x 1 /a，t 2 =111320×x 2 /a，t 3 =z 1 Four points in the motion trajectories of the two aircrafts can be obtained roughly by analyzing the speeds and the flight angles of the two flying targets, and the corresponding relation between the four motion trajectory points of the two aircrafts and the 3D grid can be obtained respectively according to the conversion formulas of the longitude and the latitude and the distance. It should be noted that, the collision pre-warning can be performed on a plurality of flight targets that need to perform the collision pre-warning at corresponding moments at the same time, and the method is not limited by the two flight targets illustrated above. The method has the advantages that the calculation amount can be greatly reduced by carrying out low-altitude flight target collision early warning through the grid coding, n flight targets are assumed to exist in a current airspace, if the safety distance is judged through the flight target distance, n-1) + (n-2) + (n-3) + (… … +3+2+1 is needed, namely n× (n-1)/2 times of calculation is carried out, when the safety distance is judged through the grid coding mode, the corresponding relation between an aircraft and a grid is obtained for collision analysis, the calculation amount is greatly reduced, and the prediction efficiency is improved.
And step 150, performing collision early warning in response to the existence of other flying targets in the 3D grid.
In some embodiments, if two or more flying objects are within the same grid at a time, then these flying objects within the same grid are at risk of collision. The corresponding relation between the predicted flight track of the flight targets and the grids obtained in the step 140 can be used for simultaneously predicting whether a plurality of flight targets have collision risks, and collision early warning is carried out according to the information of the flight targets of two or more than two flight targets in the same grid and the corresponding moment, so that the flight safety guarantee is improved, and the flight accidents are reduced. The time and the collision position of the flying target 3 with collision danger in a plurality of future time can be predicted by taking one flying target 3 as a prediction object, so that the flying strategy of the flying target 3 can be adjusted, and the flying safety can be ensured.
According to the embodiment of the disclosure, the following technical effects are achieved:
selecting a corresponding flight track point according to the flight time information and the flight track information of the current flight target, and predicting the next flight position of the current flight target, so that the distance can be calculated in advance, and the flight track can be predicted; meanwhile, the next flight position is processed in a 3D grid form, so that the calculation times when a plurality of flight targets are predicted at the same time can be reduced, and the calculation efficiency is improved; in addition, according to whether other flight targets exist in the same 3D grid, collision early warning is carried out, so that a collision result can be obtained only by judging whether two or more aircrafts exist in the same grid, a subsequent flight path can be planned and decided in time, and the occurrence of an air accident is effectively avoided.
Based on the above embodiment, in the predicting the next flight position of the current flight target according to still another embodiment provided in the present disclosure, as shown in fig. 5, the method includes the following steps:
And step 530, adjusting the next flight distance and/or the next flight angle in response to the weather combination indicator evaluation score value being greater than or equal to a preset threshold.
In some embodiments, the aircraft may be subjected to various special climatic conditions during operation, including high and low temperatures, icing, gusts, lightning, high Intensity Radiation Fields (HIRF), low visibility (fog, dust, rain, snow, etc.), volcanic ash or sand storm, etc., which may have varying degrees of impact on the flight of the aircraft. Such as gust weather, can affect the speed of flight and cause the angle of flight to deviate; the higher temperature can cause the reduction of lift force and the reduction of air density, thereby reducing the lift force on the wings of the aircraft and affecting the flying speed; the fog weather can cause the reduction of the visibility of the flight environment, and the rain and snow weather can easily cause the ice accumulation on the outer surface of the aircraft, and the like, which can influence the aircraft speed and/or the movement angle of the aircraft, and cause certain external force environment factor interference on the next flight position of the predicted aircraft. Therefore, weather comprehensive index evaluation is performed by acquiring weather information in the 3D grid, and deviation caused by weather factor conditions possibly influencing the flight track of the aircraft is considered by setting a threshold value, so that prediction accuracy is improved. Currently, some weather information providers may provide real-time weather information with accurate current location according to longitude and latitude, so the system obtains real-time weather information with accurate current location from the weather information provider using the corresponding longitude and latitude of the target 3D grid as current location information, for example, global weather information provider: tomorrow.io, understore, etc. The calculation of the weather comprehensive index evaluation score value specifically comprises the following steps: for example, if the currently acquired weather information is a gust, the weather index evaluation score corresponding to the gust is obtained as a weather comprehensive index evaluation score value, for example, 7.3, according to the wind speed and/or wind power level of the gust multiplied by the corresponding coefficient. If the preset threshold is set to be 7 and 7.3 is greater than 7, it means that the wind weather appearing in the target 3D grid affects the flight angle and/or flight speed of the aircraft, and affects the predicted next flight position, so that the next flight distance and/or flight angle need to be corrected again to accurately predict the next flight position. The coefficients may be set empirically by a user or the like, and are not limited herein. In addition to considering the influence of only one weather type, the calculation process of the weather comprehensive index evaluation score value may also set different coefficients for multiple weather types (such as gusts, thunders, fog, rain, snow, etc.) according to the user needs, and the manner of calculating the weather comprehensive index evaluation score corresponding to the weather types and then accumulating the calculated values is not limited by the above example.
Based on the foregoing embodiments, in response to the presence of other flying objects in the 3D grid, a further embodiment provided in the present disclosure performs collision early warning, including: responding to the existence of other flying targets in the 3D grid, and adjusting the take-off time of the flying targets based on the flying time information and the flying target information with collision danger; and/or adjusting the flying height of the flying object based on the flying height information and the flying object information with collision danger.
In some embodiments, a 3D grid with a risk of collision is obtained in step 150, and corresponding time information and corresponding flight object information are obtained, e.g., the 3D grid is labeled K 711 If the grid of the grid is divided into the flying object 5 and the flying object 20 at the position of 15 pm and the flying object 5 and the flying object 20 are divided into the grid at the position of 15 pm, the flying object 5 and the flying object 20 collide according to the expected flying track at the position of 15 pm, and the possibility of collision can be avoided by adjusting the flying height of the flying object and/or the original take-off time and the like.
In some embodiments, the flight strategy can be planned by summarizing the collision information predicted by the 3D grid, for example, for an airspace which is relatively easy to collide, i.e. has high collision probability, or for a flight time which is easy to collide, i.e. has high collision probability, the traffic condition of the airspace or the air route at the moment is indicated to be crowded, the flight plan of the flight target can be planned again as a whole, the air route is balanced and reasonably utilized, and the flight safety is fully ensured.
Based on the foregoing embodiment, the grid-based low-altitude flight collision warning method according to still another embodiment provided in the present disclosure further includes: and re-predicting the flying collision based on the adjusted take-off moment and/or the adjusted flying height.
In some embodiments, in order to ensure flight safety, measures for adjusting take-off time and/or adjusting flight altitude may affect the result of grid prediction of flight collision, so that the flight collision prediction needs to be performed again according to the adjusted data.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present disclosure is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present disclosure. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all alternative embodiments, and that the acts and modules referred to are not necessarily required by the present disclosure.
The foregoing is a description of embodiments of the method, and the following further describes embodiments of the present disclosure through examples of apparatus.
Fig. 6 illustrates a block diagram of a grid-based low-altitude flight collision warning device 600, in accordance with an embodiment of the present disclosure. As shown in fig. 6, the apparatus 600 includes:
a flight information obtaining module 610, configured to obtain flight information of a current flight target, where the flight information includes flight time information and flight trajectory information;
the track point selection module 620 is configured to select a corresponding flight track point according to the flight time information and the flight track information;
a flight position prediction module 630, configured to predict a next flight position of the current flight target according to the flight trajectory point;
a grid determining module 640, configured to determine a 3D grid corresponding to the next flight location;
and the collision early warning module 650 is used for carrying out collision early warning in response to the existence of other flying targets in the 3D grid.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the described modules may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 7 shows a schematic block diagram of an electronic device 700 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
The electronic device 700 includes a computing unit 701 that can perform various appropriate actions and processes according to a computer program stored in a ROM702 or a computer program loaded from a storage unit 708 into a RAM 703. In the RAM703, various programs and data required for the operation of the electronic device 700 may also be stored. The computing unit 701, the ROM702, and the RAM703 are connected to each other through a bus 704. I/O interface 705 is also connected to bus 704.
Various components in the electronic device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, etc.; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, an optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the electronic device 700 to exchange information/data with other devices through a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 701 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 700 via the ROM702 and/or the communication unit 709. When the computer program is loaded into RAM703 and executed by computing unit 701, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the method 100 by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (10)
1. The low-altitude flight collision early warning method based on the grid is characterized by comprising the following steps of:
acquiring flight information of a current flight target, wherein the flight information comprises flight time information and flight track information;
selecting a corresponding flight track point according to the flight time information and the flight track information;
predicting the next flight position of the current flight target according to the flight track point;
determining a 3D grid corresponding to the next flight position;
and responding to the existence of other flying targets in the 3D grid, and performing collision early warning.
2. The method of claim 1, wherein selecting a corresponding flight trajectory point based on the time of flight information and the flight trajectory information comprises:
acquiring current flight time information of the current flight target;
and selecting flight track points of the first n moments of the current flight moment information, wherein n is a positive integer.
3. The method of claim 2, wherein predicting a next flight location of the current flight target from the flight trajectory point comprises:
predicting the next flight distance of the current flight target according to the distance values of the flight track points at the previous n moments;
predicting the next flight angle of the current flight target according to the angle offset of the flight track points at the previous n moments;
determining a next flight trajectory point of the current flight target according to the next flight distance and the next flight angle;
and taking the next flight track point as the next flight position of the current flight target.
4. A method according to claim 3, characterized in that the method further comprises:
acquiring weather information of a 3D grid;
calculating a weather comprehensive index evaluation score value based on the weather information;
responding to the weather comprehensive index evaluation score value being more than or equal to a preset threshold value, and adjusting the next flight distance and/or the next flight angle;
and re-determining the next flight position of the current flight target.
5. The method of claim 1, wherein the next flight location comprises corresponding longitude, latitude, and altitude information, and wherein determining the 3D grid corresponding to the next flight location comprises:
according to the longitude, latitude and altitude information and a preset 3D grid side length, respectively calculating to obtain three-dimensional coordinate values corresponding to the next flight position;
mapping the three-dimensional coordinate values into the preset 3D grids, and determining the 3D grids corresponding to the next flight position.
6. The method of claim 1, wherein the collision pre-warning in response to the presence of other flying objects in the 3D grid comprises:
responding to the existence of other flying targets in the 3D grid, and adjusting the take-off time of the flying targets based on the flying time information and the flying target information with collision danger;
and/or the number of the groups of groups,
the flying height of the flying object is adjusted based on flying height information and flying object information that are in danger of collision.
7. The method of claim 6, wherein the method further comprises:
and re-predicting the flying collision based on the adjusted take-off moment and/or the adjusted flying height.
8. A low-altitude flight collision warning device based on a grid, comprising:
the flight information acquisition module is used for acquiring flight information of the current flight target, wherein the flight information comprises flight time information and flight track information;
the track point selection module is used for selecting a corresponding flight track point according to the flight time information and the flight track information;
the flight position prediction module is used for predicting the next flight position of the current flight target according to the flight track point;
the grid determining module is used for determining a 3D grid corresponding to the next flight position;
and the collision early warning module is used for responding to the existence of other flying targets in the 3D grid and carrying out collision early warning.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
10. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-7.
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