CN117725506A - Method for calculating threat degree of reentry vehicle - Google Patents
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Abstract
The invention provides a method for calculating threat degrees of reentry aircrafts, which comprises the following steps: selecting a reentry vehicle to be monitored, and determining initial speeds and initial positions of all flight directions of the reentry vehicle; determining an optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position; determining an optimal position and an optimal value through all the optimal positions; updating the update speed and the update position of the reentry vehicle in all directions according to time; establishing a space motion model according to the optimal position, the optimal value and the initial speed; and establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model. The method can rapidly judge the falling threat degree of the reentry vehicle, simplifies the whole calculation process and greatly improves the efficiency.
Description
Technical Field
The invention relates to the technical field of aerospace vehicle orbit prediction, in particular to a method for calculating threat degree of a reentry vehicle.
Background
The running route of the aircraft in the air is called an orbit, and when the spacesman controls the own aircraft, the threat degree of other reentry aircraft needs to be calculated in order to avoid the collision between the other reentry aircraft and the own aircraft. For other reentry aircraft threat degree calculation, a perturbation model is generally adopted, the prediction precision of a low-order analysis solution is low, and the process of a high-order analysis solution is very complicated; the method is not beneficial for spacesuit staff to quickly and accurately master the flight orbit of other reentry vehicles.
Disclosure of Invention
In order to solve the existing technical problems, an embodiment of the invention provides a method for calculating threat degrees of reentry vehicles, which comprises the following steps:
selecting a reentry vehicle to be monitored, and determining initial speeds and initial positions of all flight directions of the reentry vehicle;
determining an optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position;
determining an optimal position and an optimal value through all the optimal positions;
updating according to time and obtaining the updating speed and the updating position of the reentry vehicle in all directions;
establishing a space motion model according to the optimal position, the optimal value, the initial speed, the initial position, the updating speed and the updating position;
and establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model.
In the solution provided in the first aspect of the present application, the initial speed and the initial position of the reentry vehicle are obtained by determining the reentry vehicle to be monitored, the optimal track of the reentry vehicle in each flight direction and the optimal position corresponding to each optimal track are determined by the historical database, the optimal value is determined by using the optimal position, the update speed and the update position of the reentry vehicle are obtained again by using the update time, and the spatial motion model is constructed according to the optimal value, the initial speed and the optimal position; constructing a threat value evaluation model based on the reentry vehicle, and determining the threat value of the reentry vehicle according to the threat value evaluation model and the space motion model to determine the threat degree of the reentry vehicle; compared with the semi-analytic method in the related art, the threat degree of the reentry vehicle to the ground can be judged by only constructing a space motion model and a threat value evaluation model through the reentry vehicle. The threat of falling of the reentry vehicle can be rapidly judged, the whole calculation process is simplified, and the efficiency is greatly improved.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly describe the embodiments of the present invention or the technical solutions in the background art, the following description will describe the drawings that are required to be used in the embodiments of the present invention or the background art.
FIG. 1 illustrates a flow chart of a method for reentry vehicle threat level calculation provided by an embodiment of the invention;
FIG. 2 illustrates a schematic diagram of the connection of modules of a reentry aircraft threat level calculation system provided by an embodiment of the invention;
fig. 3 is a schematic structural diagram of an electronic device for performing a method for calculating threat degrees of reentry vehicles according to an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. The present invention will be further described in detail below with reference to the drawings and detailed description for the purpose of enabling those skilled in the art to better understand the aspects of the present invention.
The orbit is a route for various aircrafts to run, and is an indispensable element in the research of aerospace technology. The space staff must have the ability to predict and sense the running orbit of other aircrafts while operating the own aircrafts to follow the self-running orbit, so as to ensure the operation safety on the own flight path and avoid collision accidents in time. Therefore, a reasonable calculation method for threat level of the reentry vehicle is an essential element of the research of aerospace application.
However, the threat degree calculation of the reentry aircraft generally adopts a perturbation model, the prediction precision of a low-order analysis solution is low, and the process of a high-order analysis solution is very complicated; the method is not beneficial for spacesuit staff to quickly and accurately master the flight orbit of other reentry vehicles.
Based on this, the present embodiment gives the following embodiments 1 to 3 to solve the above problems.
Example 1
The execution subject of the reentry vehicle threat degree calculation method provided in the embodiment is a server.
Referring to a flowchart of a method for calculating threat degrees of reentry vehicles shown in fig. 1, the embodiment provides a method for calculating threat degrees of reentry vehicles, which includes the following specific steps:
step 100: and selecting the reentry vehicle to be monitored, and determining the initial speeds and initial positions of all flight directions of the reentry vehicle.
In step 100, the reentry vehicle refers to an object in the space, and because a special factor causes the vehicle to enter the atmosphere, the special factor may be rocket debris that is destroyed and generated subjectively, may be a dead satellite caused by an unreliability factor, may be a missile in a test, or the like, and therefore, the reentry vehicle cannot be simply understood as a satellite. The initial speed refers to the running speed of the reentry vehicle at the beginning of monitoring, and can be monitored and calculated by satellites which normally run in orbit. The initial position refers to coordinates corresponding to the reentry vehicle, which may be provided by the longitude and latitude lines of the earth. The determination of the initial speed and initial position of the reentry vehicle in all possible directions can be achieved by the orbit height, load registration and run-time of the reentry vehicle.
Wherein determining the speed and position of the object using the track height, load registration and run period is common knowledge in the art and will not be repeated.
Step 101: and determining the optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position, and determining the optimal position and an optimal value through all the optimal positions.
In the above step 101, the reentry vehicle may have multiple flight directions during entering the atmosphere, but depending on the parameters of the reentry vehicle and the atmospheric environment, the reentry vehicle may have an optimal trajectory in each of the multiple directions during entering the atmosphere, where the optimal trajectory may be understood as a flight path that the reentry vehicle may pass through, and there is an optimal position where the reentry vehicle will arrive in each optimal trajectory. However, the reentry vehicle can only fly in one direction, and there is only one optimal position. The optimal value refers to a coordinate point of the optimal position of the reentry aircraft, and the coordinate point is a three-dimensional coordinate, including an x-axis, a y-axis and a z-axis. The x-axis and y-axis of the reentry vehicle are provided by the in-orbit normal use satellites, and the z-axis (altitude from the ground) of the reentry vehicle is provided by the ground station in cooperation with the in-orbit normal satellites.
The best position belongs to the predicted value, and the reentry vehicle does not reach the best position at this time, and the best position is provided by the history database in step 101. The historical database refers to the track and position of the aircraft with the same model or series as the reentry aircraft in the historical time when the aircraft enters the atmosphere, and the aircraft enters the atmosphere and is recorded as the historical database by the aircraft manufacturer or a professional telemetry mechanism in real time.
And the historical database is used for storing the corresponding relation between the model numbers of various reentry aircrafts and the optimal positions.
The optimal position is the corresponding optimal position of the reentry vehicle from the historical database using the model of the reentry vehicle.
Step 102: updating and obtaining the updating speed and the updating position of the reentry vehicle in all directions according to time.
In the step 102, the updated speed after the updated time may be understood as the flying speed at the second time, and the initial speed in the step 100 may be understood as the flying speed at the first time.
In particular, the update time refers to any time after the initial time, and may be one second more than the initial time, or one minute more than the initial time, and the time at which the update speed is determined by itself according to specific requirements, so the second time is not specifically limited. Similarly, the updated position after the update time may be understood as a position coordinate point through which the second time reenters the aircraft.
Note that in step 101, the optimal position of the reentry vehicle is predicted, so the historical database is called, but the updated position coordinate point in step 102 is the true coordinates of the reentry vehicle itself.
Step 103: and establishing a space motion model according to the optimal position, the optimal value, the initial speed, the initial position, the updating speed and the updating position.
In step 103, a spatial motion model may be constructed by the optimal position, the optimal value, the initial velocity, the initial position, the update velocity, and the update position, where the spatial motion model may obtain the motion velocity of the reentry vehicle at time t+1 and the position of the reentry vehicle at time t, where the spatial motion model satisfies the following formula:
V id (t+1)＝w s *V id (t)+c 1 *r 1 *[(p id (t)-x id (t))]+c 2 *r 2 *[(g gd (t)-x id (t))]；
x id (t+1)＝x id (t)+V id (t+1)，1≤d≤14；
wherein d represents the spatial dimension in which the reentry vehicle is located, w s Representing the inertial factor, i representing the direction of movement of the reentry vehicle, c 1 Represents a first acceleration constant, c 2 Represents a second acceleration constant, t represents an initial time, x id (t) represents an initial position, V id (t+1) represents the movement speed of the reentry vehicle in the movement direction i at time t+1, r 1 And r 2 Represents a uniform random number between 0 and 1, p id (t) represents the optimal value of the optimal position of the reentry vehicle in the direction of motion i at time t, V id (t) represents the initial speed of the reentry vehicle at time t, x id (t) represents the position of the reentry vehicle at time t, x id (t+1) represents the position of the reentry vehicle at time t+1, g gd (t) represents the optimal position of the reentry vehicle in all directions of motion at time t.
In the present embodiment, V is found by a spatial motion model id (t+1) and x id After (t+1), the falling speed and position of the reentry vehicle can be obtained, and the threat degree of the reentry vehicle can be obtained through the threat value.
In one embodiment, the inertial factors of the spatial motion model satisfy:
wherein w is max Representing the maximum value of the inertial factor of the reentry vehicle in the direction of motion, w g Represents the fundamental inertia of the reentry vehicle in the direction of motion, ni represents the current iteration number, ni max Representing the maximum number of iterations.
A first acceleration constant and the second acceleration constant in the spatial motion model satisfy:
wherein c 1min The minimum value of the acceleration weight factor representing the extreme value of the balance motion direction, c 1max Maximum value of acceleration weight factor representing extreme value of balance motion direction, c 2min Minimum value of acceleration weight factor representing global extremum of balance motion direction c 2max Maximum value of acceleration weight factor representing global extremum of balance motion direction, ni max Represents the maximum number of iterations, and Ni represents the current number of iterations.
Step 104: and establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model.
In the above step 104, a threat value evaluation model is constructed, such that the prior probability of the parameter θ in the threat value evaluation model obeys Dirichlet (Dirichlet) distribution, and the posterior probability is:
wherein P (D-G) is the posterior probability of the threat value assessment model, I represents the I-th variable, n represents the total number of variables, qI represents the total number of nodes of the Bayesian network, J represents the nodes in the Bayesian networkAnd (5) a dot. In particular, the above alpha IJ ＝∑ k α IJk Where k represents the parent node of node J and rk represents the number of parent nodes of node J. Above-mentionedWherein alpha is IJk Individual elements, N, representing conditions in a dataset IJk Representing the number of instances in the dataset that satisfy the condition.
The Bayesian statistical score satisfies the following conditions:
where logP (D-G) represents the bayesian statistical score of threat value assessment, the accuracy of the threat value assessment will also be different for different parameters for the same network structure. The present embodiment optimizes threat value assessment network parameters in order to more accurately assess threat values at indefinite times. The idea of the optimization algorithm is that under the condition that threat degree evaluation network structure and underwater environment observation data are determined, bayesian reasoning is utilized to calculate the occurrence probability of missing data, and expected sufficient statistical factors are utilized to complete a missing data set, so that the optimal parameters of the current model are estimated again.
Is provided withFor the current estimation of the parameter θ, +.>Is based on->Repairing the obtained complete data; let θ be based on->Is:
wherein,representing the weight; />X in (2) I Representing the updated positions in all directions (same as the updated positions in step 2); x is x i The position in the target direction is indicated, and in particular, the target direction refers to a specific direction among all directions, but only one direction;
when (when)In the time of setting-> Representing the null set and performing t1 iterations, calculating the desired log-likelihood function Q (θ|θ) t1 ) Q (theta |theta) t1 ) Reaching a maximum value of θ, where θ t+1 ＝argsup Q(θ∣θ t+1 )。
Set up based on ground target observation data sample X I ＝x i ，D i The characteristic functions of (a) are:
wherein X is I =k and pi (X I )＝J，π(X I ) The parent node is valued, and the parent node can be simplified and obtained by the following steps:
the above simplification can be obtained:
therefore, when θ takes the following value, namely:
Q(θ∣θ t ) The best Bayesian statistical score for threat level assessment is obtained, and the best parameter solution is the threat level finally output by the threat value model. In particular, threat values refer to the probability of dropping a reentry vehicle, and knowing only the drop probability does not know the location of the drop, and is not of practical significance. On the contrary, only the falling position is known, but the falling probability is not known, and the method has no practical meaning. Therefore, the prevention can be performed in advance only if both the falling probability and the falling position are known. Therefore, after the threat level is obtained, the threat level is combined with the position of the reentry vehicle at the time t+1, and the final reentry vehicle threat level can be judged. In particular, it is common knowledge in the art to determine the threat level of a reentry vehicle using threat values and the position of the descent of the reentry vehicle, and therefore, the principle thereof will not be repeated.
In particular, the threat value assessment model is not a single calculation formula, but a generic term of posterior probability, bayesian statistical score and likelihood function, which is called threat value assessment model.
In summary, according to the method for calculating the threat degree of the reentry vehicle provided by the embodiment of the invention, the initial speed and the initial position of the reentry vehicle are obtained by determining the reentry vehicle to be monitored, the optimal track of the reentry vehicle in each flight direction and the optimal position corresponding to each optimal track are determined through the historical database, the optimal value is determined by utilizing the optimal position, the update speed and the update position of the reentry vehicle are obtained again by using the update time, and a space motion model is constructed according to the optimal value, the initial speed and the optimal position; constructing a threat value evaluation model based on the reentry vehicle, and determining the threat value of the reentry vehicle according to the threat value evaluation model and the space motion model to determine the threat degree of the reentry vehicle; compared with the semi-analytic method in the related art, the threat degree of the reentry vehicle to the ground can be judged by only constructing a space motion model and a threat value evaluation model through the reentry vehicle. The threat of falling of the reentry vehicle can be rapidly judged, the whole calculation process is simplified, and the efficiency is greatly improved.
Example 2
Referring to the schematic connection of each module of the threat level calculation system of the reentry vehicle shown in fig. 2, the embodiment further provides a threat level calculation system of the reentry vehicle, where the system is applied to the threat level calculation method of the reentry vehicle in the above embodiment, and the system includes:
and a selection module: and selecting the reentry vehicle to be monitored, and determining the initial speeds and initial positions of all flight directions of the reentry vehicle.
And a determination module: determining an optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position; and determining an optimal position and an optimal value through all the optimal positions.
The processing module is used for: updating and obtaining the updating speed and the updating position of the reentry vehicle in all directions according to time.
Spatial motion module: and establishing a space motion model according to the optimal position, the optimal value, the initial speed, the initial position, the updating speed and the updating position.
Threat value module: and establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model.
In summary, according to the threat degree calculation system for the reentry vehicle provided by the embodiment of the invention, the initial speed and the initial position of the reentry vehicle are obtained by determining the reentry vehicle to be monitored, the optimal track of the reentry vehicle in each flight direction and the optimal position corresponding to each optimal track are determined by the historical database, the optimal value is determined by using the optimal position, the update speed and the update position of the reentry vehicle are obtained again by using the update time, and a space motion model is constructed according to the optimal value, the initial speed and the optimal position; constructing a threat value evaluation model based on the reentry vehicle, and determining the threat value of the reentry vehicle according to the threat value evaluation model and the space motion model to determine the threat degree of the reentry vehicle; compared with the semi-analytic method in the related art, the threat degree of the reentry vehicle to the ground can be judged by only constructing a space motion model and a threat value evaluation model through the reentry vehicle. The threat of falling of the reentry vehicle can be rapidly judged, the whole calculation process is simplified, and the efficiency is greatly improved.
Example 3
The present embodiment proposes a computer-readable storage medium, on which a computer program is stored, which when executed by a processor performs the steps of the acceleration parameter identification method described in the above embodiment 1. The specific implementation can be referred to method embodiment 1, and will not be described herein.
In addition, referring to the schematic structural diagram of an electronic device shown in fig. 3, the present embodiment further proposes an electronic device, which includes a bus 300, a processor 301, a transceiver 302, a bus interface 303, a memory 304, and a user interface 305. The electronic device includes a memory 304.
In this embodiment, the electronic device further includes: one or more programs stored on memory 304 and executable on processor 301, configured to be executed by the processor for performing steps (1) through (5) below:
(1) And selecting the reentry vehicle to be monitored, and determining the initial speeds and initial positions of all flight directions of the reentry vehicle.
(2) Determining an optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position; and determining an optimal position and an optimal value through all the optimal positions.
(3) Updating and obtaining the updating speed and the updating position of the reentry vehicle in all directions according to time.
(4) And establishing a space motion model according to the optimal position, the optimal value, the initial speed, the initial position, the updating speed and the updating position.
(5) And establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model.
A transceiver 302 for receiving and transmitting data under the control of the processor 301.
Where bus architecture (represented by bus 300), bus 300 may comprise any number of interconnected buses and bridges, with bus 300 linking together various circuits, including one or more processors, as represented by processor 301, and memory, as represented by memory 304. Bus 300 may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., as are well known in the art and, therefore, will not be described further herein. Bus interface 303 provides an interface between bus 300 and transceiver 302. The transceiver 302 may be one element or may be a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. For example: the transceiver 302 receives external data from other devices. The transceiver 302 is used to transmit the data processed by the processor 301 to other devices. Depending on the nature of the computing system, a user interface 305 may also be provided, such as a keypad, display, speaker, microphone, joystick.
The processor 301 is responsible for managing the bus 300 and general processing as described above for running the general operating system 3041. And memory 304 may be used to store data used by processor 301 in performing operations.
Alternatively, the processor 301 may be, but is not limited to: a central processing unit, a single chip microcomputer, a microprocessor or a programmable logic device.
It is to be appreciated that the memory 304 in embodiments of the present application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (Double Data Rate SDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (SLDRAM), and Direct RAM (DRRAM). The memory 304 of the system and method described in this embodiment is intended to comprise, without being limited to, these and any other suitable types of memory.
In some implementations, the memory 304 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system 3041 and application programs 3042.
The operating system 3041 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 3042 includes various application programs such as a Media Player (Media Player), a Browser (Browser), and the like for realizing various application services. A program implementing the method of the embodiment of the present application may be included in the application program 3042.
The foregoing is merely a specific implementation of the embodiment of the present invention, but the protection scope of the embodiment of the present invention is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the embodiment of the present invention, and the changes or substitutions are covered by the protection scope of the embodiment of the present invention. Therefore, the protection scope of the embodiments of the present invention shall be subject to the protection scope of the claims.
Claims (4)
1. A method for calculating threat level of a reentry vehicle, comprising:
selecting a reentry vehicle to be monitored, and determining initial speeds and initial positions of all flight directions of the reentry vehicle;
determining an optimal track of each flight direction by utilizing a historical database, wherein each optimal track corresponds to an optimal position;
determining an optimal position and an optimal value through all the optimal positions;
updating according to time and obtaining the updating speed and the updating position of the reentry vehicle in all directions;
establishing a space motion model according to the optimal position, the optimal value, the initial speed, the initial position, the updating speed and the updating position;
and establishing a threat value evaluation model of the reentry vehicle, and obtaining a threat degree value of the reentry vehicle based on the spatial motion model and the threat value evaluation model.
2. The method of claim 1, wherein the spatial motion model satisfies the following equation:
V id (t+1)＝w s *V id (t)+c 1 *r 1 *[(p id (t)-x id (t))]+c 2 *r 2 *[(g gd (t)-x id (t))]；
x id (t+1)＝x id (t)+V id (t+1)，1≤d≤14；
wherein d represents the space in which the reentry vehicle is locatedDimension, w s Representing the inertial factor, i representing the direction of movement of the reentry vehicle, c 1 Represents a first acceleration constant, c 2 Represents a second acceleration constant, t represents an initial time, x id (t) represents an initial position, V id (t+1) represents the movement speed of the reentry vehicle in the movement direction i at time t+1, r 1 And r 2 Represents a uniform random number between 0 and 1, p id (t) represents the optimal value of the optimal position of the reentry vehicle in the direction of motion i at time t, V id (t) represents the initial speed of the reentry vehicle at time t, x id (t) represents the position of the reentry vehicle at time t, x id (t+1) represents the position of the reentry vehicle at time t+1, g gd (t) represents the optimal position of the reentry vehicle in all directions of motion at time t.
3. The reentry vehicle threat level calculation method of claim 2, wherein the inertia factor satisfies:
wherein w is max Representing the maximum value of the inertial factor of the reentry vehicle in the direction of motion, w g Represents the fundamental inertia of the reentry vehicle in the direction of motion, ni represents the current iteration number, ni max Representing the maximum number of iterations.
4. The reentry vehicle threat level calculation method of claim 2, wherein the first acceleration constant and the second acceleration constant satisfy:
wherein c 1min The minimum value of the acceleration weight factor representing the extreme value of the balance motion direction, c 1max Maximum value of acceleration weight factor representing extreme value of balance motion direction, c 2min Minimum value of acceleration weight factor representing global extremum of balance motion direction c 2max Maximum value of acceleration weight factor representing global extremum of balance motion direction, ni max Represents the maximum number of iterations, and Ni represents the current number of iterations.
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