Method, device and electronic equipment for determining route protection zone for low-altitude aircraft

Abstract

The present application provides a method, device and electronic equipment for determining the route protection zone of a low-altitude aircraft, and relates to the technical field of low-altitude traffic management. The method comprises: determining a first value based on the track error between the acquired nominal track data and the actual flight track data of the low-altitude aircraft; performing numerical integration on the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of a collision of the low-altitude aircraft; and determining the height and width of the route protection zone of the low-altitude aircraft based on the gap between the risk probability and the configured safety level constant. The method calculates the collision probability by constructing a covariance matrix in the body coordinate system and combining it with the non-central chi-square distribution model, and uses an extended golden section search algorithm to quickly solve the route protection zone. The present application can effectively balance the efficiency of airspace resource utilization and operational safety, and lay the foundation for the intelligent upgrade of urban low-altitude traffic systems and the expansion of collaborative collision avoidance technology for multiple low-altitude aircraft.

Description

Technical Field

[0001] The present application relates to the technical field of low-altitude traffic management, and in particular to a method, device and electronic equipment for determining a route protection zone for low-altitude aircraft. Background Art

[0002] With the rapid development of urban low-altitude transportation, especially the increasing use of drones, flying cars and electric vertical take-off and landing aircraft, the traffic volume of aircraft in low-altitude airspace has shown a significant growth trend.

[0003] Traditional low-altitude route protection zone design relies on static separation standards (such as fixed horizontal and vertical separations), which in turn rely on collision boxes established in the aircraft's coordinate system. Airflow in urban low-altitude environments is complex. To overcome this, aircraft operating in low-altitude environments require feedback control from the flight control system to correct their flight paths. This results in frequent changes in the flight attitude of low-altitude aircraft, which can lead to insufficient safety redundancy, waste of airspace resources, and difficulty adapting to complex flight conditions. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method, device and electronic equipment for determining the route protection zone of low-altitude aircraft, so as to solve the above-mentioned problems existing in the prior art, support real-time airspace management, and improve the safety of low-altitude aircraft flying in the route protection zone.

[0005] In a first aspect, a method for protecting a route of a low-altitude aircraft is provided, which may include:

[0006] determining a first value based on a track error between the acquired nominal track data and actual flight track data of the low-altitude aircraft;

[0007] Numerically integrating the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integral in the numerical integration process is the first value, and the configured second value is the lower limit of the integral;

[0008] The height and width of the route protection zone for low-altitude aircraft are determined based on the gap between the risk probability and the configured safety level constant.

[0009] In one possible implementation, before obtaining the track error between the nominal track data and the actual flight track data of the low-altitude aircraft, the method includes:

[0010] Determine the center of mass of the low-altitude aircraft as a mass point;

[0011] A collision box enclosing the low-altitude aircraft is constructed based on the mass points.

[0012] In one possible implementation, determining the first value includes:

[0013] The radius of the collision box and the track error are calculated using a configured preset integration algorithm to obtain the first value.

[0014] In a possible implementation, the preset integration algorithm is:

[0015]

[0016] in, represents the first value, r represents the radius, Represents the covariance matrix corresponding to the track error.

[0017] In a possible implementation, determining the height and width of the route protection zone for low-altitude aircraft based on the gap between the risk probability and a configured safety level constant includes:

[0018] Determining a target non-central parameter in the collision probability algorithm based on a golden section search algorithm to minimize the gap between the risk probability and a configured safety level constant;

[0019] The configured width algorithm and length algorithm are used to calculate the target non-center parameter and the track error respectively to obtain the height and width of the route protection zone of the low-altitude aircraft.

[0020] In one possible implementation, the width algorithm is:

[0021]

[0022] in, Indicates width, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

[0023] In one possible implementation, the length algorithm is:

[0024]

[0025] in, Indicates height, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

[0026] In a second aspect, a device for a route protection zone for low-altitude aircraft is provided, which may include:

[0027] a determining unit, configured to determine a first value based on a track error between the acquired nominal track data and actual flight track data of the low-altitude aircraft;

[0028] an integration unit, configured to perform numerical integration on the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integration in the numerical integration process is the first value, and the configured second value is the lower limit of the integration;

[0029] The determining unit further determines the height and width of the route protection zone for the low-altitude aircraft based on the gap between the risk probability and a configured safety level constant.

[0030] In a third aspect, an electronic device is provided, the electronic device including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0031] Memory for storing computer programs;

[0032] The processor is configured to implement any of the method steps described in the first aspect when executing a program stored in the memory.

[0033] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, any of the method steps described in the first aspect is implemented.

[0034] The present application provides a method for determining a route protection zone for a low-altitude aircraft, the method comprising: determining a first value based on a track error between the nominal track data and the actual flight track data of the low-altitude aircraft; numerically integrating a collision probability algorithm of a non-central chi-square distribution to determine the risk probability of a collision of the low-altitude aircraft; wherein the upper limit of the integral in the numerical integration process is the first value, and the configured second value is the lower limit of the integral; and determining the height and width of the route protection zone for the low-altitude aircraft based on the gap between the risk probability and the configured safety level constant. The method calculates the collision probability by constructing a covariance matrix in an aircraft coordinate system and combining it with a non-central chi-square distribution model, and uses an extended golden section search algorithm to quickly solve the optimal width and height of the route protection zone. The present application can adapt to complex motion scenarios of low-altitude aircraft such as drones, flying cars, and electric vertical take-off and landing aircraft, provide theoretical support for the design of airspace route protection zones, effectively balance the efficiency of airspace resource utilization and operational safety, and lay the foundation for the intelligent upgrade of urban low-altitude transportation systems and the expansion of collaborative collision avoidance technology for multiple low-altitude aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A system architecture diagram of a method for determining a route protection zone for low-altitude aircraft provided in an embodiment of the present application;

[0037] Figure 2 A flowchart of a method for determining a route protection zone for low-altitude aircraft provided in an embodiment of the present application;

[0038] Figure 3 A schematic diagram of a crash box provided in an embodiment of the present application;

[0039] Figure 4 A schematic structural diagram of a device for determining a route protection zone for low-altitude aircraft provided in an embodiment of the present application;

[0040] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0042] The method for determining the route protection zone of low-altitude aircraft provided in the embodiment of the present application can be applied to Figure 1 In the system architecture shown in Figure 1 As shown, the system may include: a low-altitude aircraft and a processor that obtains low-altitude aircraft movement information in real time.

[0043] The processor is used for acquiring low-altitude aircraft movement information in real time and executing a method for determining a route protection zone for low-altitude aircraft.

[0044] With the rapid development of urban low-altitude transportation, especially the increasing use of drones, flying cars and electric vertical take-off and landing aircraft, the traffic volume of aircraft in low-altitude airspace has shown a significant growth trend.

[0045] Traditional low-altitude route protection zone design relies on static separation standards (such as fixed horizontal and vertical separations), which in turn rely on collision boxes established in the aircraft's coordinate system. Airflow in urban low-altitude environments is complex. To overcome this, aircraft operating in low-altitude environments require feedback control from the flight control system to correct their flight paths. This results in frequent changes in the flight attitude of low-altitude aircraft, which can lead to insufficient safety redundancy, waste of airspace resources, and difficulty adapting to complex flight conditions.

[0046] Therefore, the present application provides a method for determining a route protection zone for low-altitude aircraft to solve the above-mentioned problems existing in the prior art. It can support real-time airspace management while improving the safety of low-altitude aircraft flying in the route protection zone.

[0047] The preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application can be combined with each other if there is no conflict.

[0048] Figure 2 The following is a flow chart of a method for determining a route protection zone for low-altitude aircraft provided in an embodiment of the present application. Figure 2 As shown, the method may include:

[0049] Step S210: Obtain the track error between the nominal track data and the actual flight track data of the low-altitude aircraft.

[0050] Before executing step S210, the method may further include:

[0051] Combine Figure 3 As shown in the figure, the low-altitude aircraft can be abstracted as a mass point, and the coordinates of the mass point are the position of the center of mass (or geometric center) of the low-altitude aircraft; the low-altitude aircraft is regarded as a spherical collision zone, that is, the collision box of the low-altitude aircraft is determined; the collision box is the minimum spherical area with the center of mass of the aircraft as the sphere center and enclosing the corresponding low-altitude aircraft.

[0052] Specifically, the low-altitude aircraft ground surveillance system can obtain information such as the timestamp, longitude and latitude of the flight trajectory, altitude above the ground, and nominal speed of the low-altitude aircraft during different stages (such as takeoff, hovering, climb, cruise, descent, and landing). This allows the acquisition of both nominal and actual flight trajectory data for the low-altitude aircraft during the cruise phase. The nominal trajectory data includes the nominal speed and the positions of nominal trajectory points at different timestamps, namely, longitude and latitude, and altitude above the ground. The actual flight trajectory data includes the actual speed and the positions of actual flight trajectory points at different timestamps, namely, longitude and latitude, and altitude above the ground.

[0053] The process of establishing the covariance matrix of the low-altitude aircraft track error may include:

[0054] First, establish a right-handed coordinate system, with the center of mass of the low-altitude aircraft as the origin, the speed direction of the low-altitude aircraft as the x-axis, the opposite direction of gravity as the z-axis, and the y-axis perpendicular to the x-axis and z-axis.

[0055] In actual operation of low-altitude aircraft, due to the uncertainty of actual trajectory, the covariance matrix is ​​used Describes the error distribution of the center of mass of a low-altitude aircraft relative to the nominal track data. Covariance matrix As shown in the following formula:

[0056]

[0057] in, , , is the covariance matrix The main diagonal elements of represent the track error variance in each coordinate direction; , , is the covariance matrix The non-diagonal elements of represent the error covariance between directions. The eigenvalue of , and not all are 0.

[0058] That is to say, the track error may include the error value between the position of the actual flight track point in the x-axis direction and the position of the nominal track point, the error value between the position of the actual flight track point in the y-axis direction and the position of the nominal track point, and the error value between the position of the actual flight track point in the z-axis direction and the position of the nominal track point.

[0059] Furthermore, assuming that the low-altitude aircraft is in the cruise phase, the track error of the low-altitude aircraft is determined along the body coordinate system. First, based on the operating data, the flight trajectory data of the cruise phase (the altitude of the nominal track data remains unchanged) is filtered out; secondly, when the nominal track data is known, the actual flight trajectory points of the cruise phase are found to correspond to the nominal track points according to the actual flight trajectory data. The direction coordinates are used to extract n actual flight trajectory points: 、 、…、 , and the corresponding n nominal track points: 、 、…、 , so the error between the position of the actual flight trajectory point and the nominal trajectory point in the x-axis direction is: Similarly, the error value between the position of the actual flight trajectory point in the y-axis direction and the position of the nominal trajectory point and the error value between the position of the actual flight trajectory point in the z-axis direction and the position of the nominal trajectory point can be obtained using the same algorithm, which will not be described in detail in this application.

[0060] The error covariance may include a first variance of the error value between the position of the actual flight trajectory point and the position of the nominal track point in the x-axis direction, a second variance of the error value between the position of the actual flight trajectory point and the position of the nominal track point in the y-axis direction, and a third variance of the error value between the position of the actual flight trajectory point and the position of the nominal track point in the z-axis direction; and a first covariance of the error value between the position of the actual flight trajectory point and the position of the nominal track point in the x-axis direction and the error value between the position of the actual flight trajectory point and the nominal track point in the y-axis direction, a second covariance of the error value between the position of the actual flight trajectory point and the nominal track point in the x-axis direction and the error value between the position of the actual flight trajectory point and the nominal track point in the z-axis direction, and a third covariance of the error value between the position of the actual flight trajectory point and the nominal track point in the y-axis direction and the error value between the position of the actual flight trajectory point and the nominal track point in the z-axis direction.

[0061] Continuing with the above example, the first variance of the error between the actual flight trajectory point of a low-altitude aircraft in the x-axis direction and the nominal flight trajectory point can be expressed as:

[0062]

[0063] Similarly, the second variance corresponding to low-altitude aircraft Difference with third party It can also be obtained by a similar algorithm, which will not be described here.

[0064] The first covariance of the error between the position of the actual flight track point of the low-altitude aircraft in the x-axis and y-axis directions and the position of the nominal track point can be expressed as:

[0065]

[0066] Similarly, the second covariance corresponding to low-altitude aircraft is and the third covariance It can also be obtained by a similar algorithm, which will not be described here.

[0067] The number of eigenvalues ​​of the relative covariance matrix obtained in different directions is 3, such as Three different eigenvalues, all greater than 0; among them, represent the first and second eigenvalues ​​in the horizontal direction, respectively. Indicates the eigenvalue in the vertical direction.

[0068] Step S220: Determine a first value based on the track error.

[0069] Specifically, a preset integral algorithm is used to calculate the radius of the collision box and the track error to obtain a first value.

[0070] The default integration algorithm is:

[0071]

[0072] in, Represents the first value, r represents the radius of the collision box, Represents the covariance matrix corresponding to the track error.

[0073] Step S230: Determine the route protection zone for low-altitude aircraft based on the difference between the integral value of the collision probability algorithm and the configured safety level constant.

[0074] Specifically, A. Numerically integrate the non-central chi-square distribution collision probability algorithm to determine the risk probability of a low-altitude aircraft collision, generally referring to the collision risk probability between multiple low-altitude aircraft. The first value is used as the upper limit of the integration, and the configured second value is used as the lower limit of the integration (in this application, the second value is 0).

[0075] The probability density function of the variable x with three degrees of freedom non-central chi-square distribution, that is, the collision probability algorithm is ;in, is the non-central parameter.

[0076] B. Determine the target non-centrality parameter in the collision probability algorithm to minimize the gap between the risk probability and the configured safety level constant;

[0077] The above steps A and B can be expressed as:

[0078]

[0079]

[0080]

[0081] Wherein, C represents the first value, Represents a safety level constant.

[0082] In one example, a golden section search algorithm based on band extension can be used to solve the target non-central parameter.

[0083] The specific process of the golden section search algorithm can be:

[0084] 1. Configure core parameters:

[0085] Golden Ratio : , used to determine the interval split point for each iteration;

[0086] Interval expansion factor = 2 (for initial interval expansion);

[0087] Maximum number of iterations = 100;

[0088] 2. Initialize the search interval [a, b] so that the function has a minimum point in the search interval and the accuracy is set to ε.

[0089] The right endpoint of the search interval is b , from the initial point a Start expanding;

[0090] b=a+expansion factor;

[0091] By comparing the function values ​​at the endpoints g ( a )and g ( b ), expand the search range to the right:

[0092] like g ( a )> g ( b ), indicating that the minimum value may be on the right side, a Move to b , and continue to expand (move right).

[0093] like g ( a )≤ g ( b ), indicating that the current search interval may contain the minimum value, and exit the expansion phase.

[0094] 3. Golden section search with extension:

[0095] Compute two golden section points within the expanded search interval:

[0096] w1=a+(ba)×R; in the search interval [ a , b ], calculate the left test point w1 according to the golden ratio;

[0097] w2=b-(ba)×R; calculate the right test point w2, which is symmetrically distributed with w1;

[0098] This part makes the distances between w1 and w2 and a and b respectively satisfy the golden ratio.

[0099] Calculate the corresponding function values: f1=g(w1), f2=g(w2), and select the point corresponding to the smaller value as the endpoint of the new search interval.

[0100] Iteratively shrink the search interval: When the search interval length is greater than the preset accuracy, it continues to shrink, that is, while (ba) > maximum search interval length;

[0101] Conditional branching:

[0102] like f 1> f 2: Indicates that the minimum value is in the right subinterval [w1, b ], update the right endpoint b =w1, and recalculate the right test point w2.

[0103] Otherwise: the minimum value is in the left subinterval [ a ,w2], update the left endpoint a =w2, and recalculate the left test point w1. Each iteration only needs to calculate a new test point function value, and retain the result on the other side to save computational effort.

[0104] Update w1 / w2 and the corresponding function value according to the golden ratio;

[0105] Take the midpoint of the final interval as the approximate minimum point and return the optimal solution: w*=(a+b) / 2.

[0106] In existing techniques, the traditional golden section method applied to fixed intervals cannot be used due to uncertainty about the optimal parameter values. However, the extended golden section search in this approach can adapt to different function characteristics by dynamically creating interval parameters. This method can re-determine the optimal interval at each iteration based on the function's rate of change or other characteristics, thereby better utilizing the golden section method and more quickly approaching the optimal solution.

[0107] In one embodiment, a golden section search can be combined with gradient descent and other methods to optimize each dimension. Hybrid Approach: Gradient descent may be more suitable for some dimensions (especially if gradient information is readily available and the function is smooth), while a golden section search may be more appropriate for other dimensions (e.g., for non-smooth or discontinuous functions). In this case, the most appropriate method can be selected based on the specific situation. Embedded Application: In gradient descent, the gradient becomes very small when approaching the optimal point, resulting in slower convergence. In this case, a golden section search can be used in each dimension to accelerate convergence in the final stage.

[0108] In short, this combination approach aims to leverage the strengths of each method and select the most appropriate optimization strategy for different types of function characteristics, thereby achieving more efficient and accurate problem solving. However, in practice, it is necessary to adjust the strategy based on the specific nature of the problem to ensure optimal results.

[0109] In another embodiment, a hybrid strategy is formed by combining other optimization algorithms (such as genetic algorithms and simulated annealing). In this strategy, golden section search is used for local optimization, while other algorithms are responsible for global exploration. Specifically, initial parameters are set, including population size, number of iterations, temperature (for simulated annealing), and search interval. A preliminary search is performed using the genetic algorithm or simulated annealing to explore the entire solution space and identify regions with potential optimal solutions. A determination is made as to when to transition from the global exploration phase to the local optimization phase. This can be determined by evaluating the quality of the current solution, the degree of difference between solutions, or by reaching a certain number of iterations. When the transition conditions are met, the golden section search is used to perform detailed local optimization of the selected region in order to find a more accurate optimal solution. The transition conditions can include entering the local optimization phase when the number of iterations reaches a certain value or when the quality of the solution stabilizes.

[0110] This extension can better balance global and local searches and increase the probability of finding the global optimal solution.

[0111] C. Determine the height and width of the route protection zone for low-altitude aircraft based on the target non-center parameters.

[0112] Specifically, the configured width algorithm is used to calculate the target non-center parameters and track errors to obtain the height of the route protection zone for low-altitude aircraft;

[0113] The width algorithm can be expressed as:

[0114]

[0115] in, Indicates width, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

[0116] The configured length algorithm is used to calculate the target non-center parameters and track error to obtain the width of the route protection zone for low-altitude aircraft;

[0117] The length algorithm can be:

[0118]

[0119] in, Indicates height, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

[0120] The present application provides a method for determining the route protection zone of a low-altitude aircraft, the method comprising: determining a first numerical value based on the track error between the acquired nominal track data and the actual flight track data of the low-altitude aircraft; performing numerical integration on the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of a collision of the low-altitude aircraft; wherein the upper limit of the integral in the numerical integration process is the first numerical value, and the configured second numerical value is the lower limit of the integral; determining the height and width of the route protection zone of the low-altitude aircraft based on the gap between the risk probability and the configured safety level constant. This method breaks through the limitations of the traditional static separation standard in attitude uncertainty modeling, and significantly improves the accuracy of collision probability calculation by dynamically analyzing the covariance characteristics of the heading, lateral and vertical errors of the low-altitude aircraft during tilted flight; at the same time, based on the three-degree-of-freedom distribution model of the non-diagonal covariance matrix, the golden section algorithm with extended search is used to achieve rapid calculation of the optimal solution of width and height under the safety threshold constraint, taking into account both computational efficiency and result reliability. This application can adapt to the complex movement scenarios of low-altitude aircraft such as drones, flying cars, and electric vertical take-off and landing aircraft, provide theoretical support for the design of airspace route protection zones, effectively balance the efficiency of airspace resource utilization and operational safety, and lay the foundation for the intelligent upgrade of urban low-altitude transportation systems and the expansion of collaborative collision avoidance technology for multiple low-altitude aircraft.

[0121] Corresponding to the above method, the embodiment of the present application also provides a device for protecting the route of low-altitude aircraft, such as Figure 4 As shown, the device includes:

[0122] The determining unit 410 determines a first value based on a track error between the acquired nominal track data and the actual flight track data of the low-altitude aircraft;

[0123] An integration unit 420 is configured to perform numerical integration on the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integration in the numerical integration process is the first value, and the configured second value is the lower limit of the integration;

[0124] The determining unit further determines the height and width of the route protection zone for the low-altitude aircraft based on the gap between the risk probability and a configured safety level constant.

[0125] The functions of the various functional units of the device for a route protection zone for a low-altitude aircraft provided in the above-mentioned embodiment of the present application can be achieved through the above-mentioned method steps. Therefore, the specific working process and beneficial effects of the various units in the device for a route protection zone for a low-altitude aircraft provided in the embodiment of the present application will not be repeated here.

[0126] The present application also provides an electronic device, such as Figure 5 As shown, it includes a processor 510 , a communication interface 520 , a memory 530 and a communication bus 540 , wherein the processor 510 , the communication interface 520 , and the memory 530 communicate with each other via the communication bus 540 .

[0127] Memory 530, for storing computer programs;

[0128] The processor 510 is configured to execute the program stored in the memory 530 by performing the following steps:

[0129] determining a first value based on a track error between the acquired nominal track data and actual flight track data of the low-altitude aircraft;

[0130] Numerically integrating the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integral in the numerical integration process is the first value, and the configured second value is the lower limit of the integral;

[0131] The height and width of the route protection zone for low-altitude aircraft are determined based on the gap between the risk probability and the configured safety level constant.

[0132] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the figure shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0133] The communication interface is used for communication between the above electronic device and other devices.

[0134] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0135] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

[0136] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments to solve the problems can be found in Figure 2 The various steps in the embodiment shown are implemented, therefore, the specific working process and beneficial effects of the electronic device provided by the embodiment of the present application are not repeated here.

[0137] In another embodiment provided in the present application, a computer-readable storage medium is also provided, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes a method for determining a route protection zone for a low-altitude aircraft as described in any of the above embodiments.

[0138] In another embodiment provided by the present application, a computer program product containing instructions is also provided. When the computer program product is run on a computer, the computer executes the method for determining a route protection zone for a low-altitude aircraft described in any of the above embodiments.

[0139] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the embodiments of the present application may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware. Furthermore, the embodiments of the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0140] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0141] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0143] Unless otherwise defined, the technical or scientific terms used in this application should have the usual meanings understood by persons of ordinary skill in the field to which the invention belongs. The words "first", "second" and similar terms used in this application do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "include" or "comprise" mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect", "couple" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0144] Although preferred embodiments have been described in the present application, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic inventive concepts. Therefore, the present application is intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0145] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the embodiments of the present application and their equivalents, the embodiments of the present application are also intended to include these modifications and variations.

Claims

1. A method for determining a route protection zone for low-altitude aircraft, characterized in that: The method comprises: determining a first value based on a track error between the acquired nominal track data and actual flight track data of the low-altitude aircraft; Numerically integrating the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integral in the numerical integration process is the first value, and the configured second value is the lower limit of the integral; Determine the height and width of the route protection zone for the low-altitude aircraft based on the gap between the risk probability and the configured safety level constant; Before obtaining the track error between the nominal track data and the actual flight track data of the low-altitude aircraft, the method includes: Determine the center of mass of the low-altitude aircraft as a mass point; Based on the mass points, a collision box is constructed to enclose the low-altitude aircraft; Determining a first value includes: Calculating the radius of the collision box and the track error using a configured preset integration algorithm to obtain the first value; The preset integration algorithm is: in, represents the first value, r represents the radius, Represents the covariance matrix corresponding to the track error; Based on the gap between the risk probability and the configured safety level constant, determine the height and width of the route protection zone for low-altitude aircraft, including: Determining a target non-central parameter in the collision probability algorithm based on a golden section search algorithm to minimize the gap between the risk probability and a configured safety level constant; The configured width algorithm and length algorithm are used to calculate the target non-center parameter and the track error respectively to obtain the height and width of the route protection zone of the low-altitude aircraft.

2. The determination method according to claim 1, wherein: The width algorithm is: in, Indicates width, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

3. The determination method according to claim 1, wherein: The length algorithm is: in, Indicates height, , represents the covariance matrix corresponding to the track error, represents the target noncentrality parameter.

4. A device for determining a route protection zone for low-altitude aircraft, using the determination method according to any one of claims 1 to 3, characterized in that: The determining device comprises: a determining unit, configured to determine a first value based on a track error between the acquired nominal track data and actual flight track data of the low-altitude aircraft; an integration unit, configured to perform numerical integration on the collision probability algorithm of the non-central chi-square distribution to determine the risk probability of the low-altitude aircraft collision; wherein the upper limit of the integration in the numerical integration process is the first value, and the configured second value is the lower limit of the integration; The determining unit further determines the height and width of the route protection zone for the low-altitude aircraft based on the gap between the risk probability and a configured safety level constant.

5. An electronic device, characterized in that: The electronic device includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory for storing computer programs; The processor is configured to implement the steps of the determination method according to any one of claims 1 to 3 when executing the program stored in the memory.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the determination method according to any one of claims 1 to 3 are implemented.

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