CN112506218B - Reentry vehicle any no-fly zone around-flying method based on intelligent trajectory prediction - Google Patents
Reentry vehicle any no-fly zone around-flying method based on intelligent trajectory prediction Download PDFInfo
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Abstract
A reentry aircraft arbitrary no-fly zone fly-around method based on track intelligent prediction provides a reentry aircraft track rapid prediction method, a prediction track and no-fly zone relation rapid determination method and aircraft tilt angle symbol selection logic aiming at the characteristic that the attack angle and the tilt angle of a reentry aircraft cannot be changed, and guides the aircraft to fly around the no-fly zone with any shape by changing the symbol of the aircraft tilt angle. The invention enables the reentry aircraft to fly around the no-fly zone with any shape, thereby avoiding the step of preprocessing the irregular no-fly zone and enabling the autonomy of the aircraft to be higher; meanwhile, the defect that the flying area of the aircraft is enlarged due to the fact that the irregular no-fly zone is processed is avoided, and the aircraft has larger residual flying capacity after the flying area is processed. The method has small calculated amount and is suitable for the online use of the aircraft.
Description
Technical Field
The invention relates to a reentry vehicle any no-fly zone around-flying method based on intelligent trajectory prediction, and belongs to the technical field of guidance and control.
Background
The reentry aircraft has various execution tasks and complex flight environment, and may be threatened by weather, enemy interception weapons and the like in the flight process. In order to ensure the flight safety of the aircraft, these threat areas are usually defined as no-fly zones, and the flight trajectory is adjusted to make the aircraft bypass these no-fly zones. These no-fly zones are often complex and irregular in shape and difficult to interpret analytically. At present, the no-fly zone is often regarded as a standard circle, although the process of penetration is simplified, the no-fly zone around the aircraft is larger than the actual no-fly zone, and the capacity loss of the aircraft is caused.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method is characterized in that a reentry aircraft trajectory rapid prediction method, a prediction trajectory and no-fly zone relation rapid determination method and aircraft inclination angle symbol selection logic are provided, and the aircraft is guided to fly around the no-fly zone of any shape by changing the symbols of the aircraft inclination angles. The invention enables the reentry aircraft to fly around the no-fly area with any shape, thereby avoiding the step of preprocessing the irregular no-fly area and enabling the autonomy of the aircraft to be higher; meanwhile, the defect that the flying area of the aircraft is enlarged due to the fact that the irregular no-fly zone is processed is avoided, and the aircraft has larger residual flying capacity after the flying area is processed. The method has small calculation amount and is suitable for the online use of the aircraft.
The purpose of the invention is realized by the following technical scheme:
a reentry aircraft arbitrary no-fly zone fly-around method based on intelligent trajectory prediction comprises the following steps:
s1, establishing a reentry vehicle flight dynamics model;
s2, selecting different initial parameters of the aircraft, simultaneously setting an attack angle and a roll angle, and simulating by using the flight dynamics model in the S1 to obtain the terminal position of the aircraft; the initial parameters comprise height, speed, longitude, latitude, track angle and course angle;
s3, taking initial parameters, an attack angle, a roll angle and time of the aircraft as input, taking the terminal position of the aircraft as output, and training by adopting a BP neural network to obtain a trained neural network model;
s4, determining the position of a no-fly zone; predicting a flight track by using the trained neural network model according to the current attack angle and the current roll angle of the aircraft;
and S5, judging the position relation between the flight track and the no-fly zone, and adjusting the inclination angle of the aircraft when the aircraft is influenced by the no-fly zone.
According to the reentry vehicle any no-fly zone detouring method based on intelligent trajectory prediction, preferably, the no-fly zone is irregular.
Preferably, in the method for winding around the reentry aircraft in any no-fly zone based on intelligent trajectory prediction, in S2, the attack angle and the roll angle are both functions with speed as an independent variable.
Preferably, in S4, according to the longitude and latitude information of the no-fly zone, the position information of the no-fly zone in the geocentric coordinate system is calculated, and then according to a transformation matrix between the geocentric coordinate system and the aircraft position coordinate system, the coordinate information of the no-fly zone in the aircraft position coordinate system is calculated, that is, the position of the no-fly zone is determined.
Preferably, in S4, the method for predicting the flight trajectory by using the trained neural network model is as follows:
s41, acquiring the current altitude, speed, longitude, latitude, track angle and course angle of the aircraft;
s42, setting the flight time of the aircraft;
s43, taking the current altitude, speed, longitude, latitude, track angle, course angle of the aircraft and the flight time of the aircraft as input parameters, and predicting the flight track by using the trained neural network model.
Preferably, in S5, the position relationship between the flight trajectory and the no-fly zone is determined, and when the aircraft is affected by the no-fly zone, the method for adjusting the roll angle of the aircraft is as follows:
s51, the flight path is approximately a section of circular arc relative to the earth radius, and the current position of the aircraft is a path starting point p S The other end of the arc is a track end point p E The no-fly zone is represented by a plurality of characteristic points which are connected in sequence; calculating the distances between the track end point and all the characteristic points of the no-fly area; selecting the characteristic point p with the minimum distance and two characteristic points p connected with the point p 1 And p 2 ；
S52, calculating a line segment p 1 p、p 2 p、p S p、p E p relative to ginsengThe included angles of the examination directions are respectively recorded as
S53, if
Is in a size of->
And &>
If the arc end point is in the no-fly zone; otherwise, the track end point is outside the no-fly zone;
s54, if the track end point is outside the no-fly zone, recording the flight time t of the aircraft at the moment, and turning to S57, otherwise, turning to S55;
s55, calculating the track end point relative to the line segment p 1 p、p 2 Selecting a smaller value as the distance of the aircraft relative to the no-fly zone, and recording as d;
s56, adjusting the track prediction time t by adopting a dichotomy method, and calculating the corresponding track end point position p' E Repeating S52-S55 to determine the distance d 'of the aircraft relative to the no-fly zone after the track prediction time is adjusted until d' is smaller than a set threshold value delta d;
s57, determining track prediction time t when the track is intersected with the no-fly zone ⊥ ＝t′；
S58, setting a track prediction threshold t threshold Comparing the time t when the trajectory intersects the no-fly zone ⊥1 And t ⊥2 And t threshold The magnitude relationship of (a); if t ⊥1 And t ⊥2 Are all greater than t threshold The aircraft keeps flying at the current roll angle; if t is ⊥1 And t ⊥2 At least one of which is less than t threshold Then aircraft according to t ⊥1 And t ⊥2 Middle and largeDetermines the roll angle sign.
Compared with the prior art, the invention has the following beneficial effects:
aiming at the characteristic that the attack angle and the inclination angle of the reentry aircraft cannot be changed, the method designs a reentry aircraft trajectory rapid prediction method, a rapid judgment method of the relationship between the predicted trajectory and the no-fly zone and aircraft inclination angle symbol selection logic, and guides the aircraft to bypass the no-fly zone with any shape to fly by changing the symbol of the aircraft inclination angle. The invention enables the reentry aircraft to fly around the no-fly zone with any shape, thereby avoiding the step of preprocessing the irregular no-fly zone and enabling the autonomy of the aircraft to be higher; meanwhile, the defect that the flying-around area of the aircraft is enlarged due to the fact that an irregular flying-forbidden area is processed is avoided, and the aircraft has larger residual flying capacity after the flying-around flying-forbidden area. The method has small calculated amount and is suitable for the online use of the aircraft.
Drawings
Fig. 1 is a flowchart of a method for winding around any no-fly zone according to the present invention;
FIG. 2 is a schematic diagram of a method for fast track prediction according to the present invention;
fig. 3 is a schematic diagram of a method for determining a position relationship between an aircraft position and a no-fly zone according to the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
A reentry aircraft arbitrary no-fly zone detouring method is disclosed, as shown in fig. 1 and fig. 2, and the reentry aircraft arbitrary no-fly zone detouring method based on intelligent trajectory prediction can be divided into two modules, namely, an offline training module of an intelligent trajectory prediction network and an online detouring module of an arbitrary no-fly zone.
The off-line training module of the intelligent trajectory prediction network comprises the following steps:
step 1: determining parameters of the reentry vehicle, and establishing a flight dynamics model of the reentry vehicle;
and 2, step: aiming at the parameters of the reentry aircraft, setting different aircraft positions, speeds, attack angles, inclination angles and flight times, namely setting different parameter values, and carrying out simulation to obtain flight tracks of a series of aircraft as training samples;
and 3, step 3: and training the sample by adopting a BP neural network, taking the state, the attack angle, the inclination angle and the time of the aircraft as input, and taking the predicted position of the aircraft as output.
Further, the reentry vehicle dynamics model of step 1 is
Where, is the derivation, α is the angle of attack, R is the earth's center radius, and its dimensionless parameter is the earth's radius R 0 =6378km; theta and phi are longitude and latitude respectively; v is the aircraft speed, with dimensionless parameters of
And g is a 0 ＝9.81m/s 2 (ii) a Gamma is the angle of the flight path,is the angle between the velocity vector and the local horizontal plane; psi is the heading angle, measured clockwise from the local true north direction; sigma is a roll angle; />
For time, its dimensionless parameter is->
Omega is the rotational angular velocity of the earth, and the dimensionless parameter is->
P＝F eng /mg 0 Is the thrust acceleration of the solid pulse engine; nondimensionalized resistive acceleration D = ρ (V) c V) 2 S ref C D /(2mg 0 )，C D Lift acceleration L = ρ (V) for damping coefficient c V) 2 S ref C L /(2mg 0 )，C L Is the coefficient of lift, where ρ is the atmospheric density, S ref Is the reference area and m is the aircraft mass.
Further, the sample construction method in step 2 comprises:
(1) setting the value range of initial state variables (height, speed, longitude, latitude, track angle, course angle and flight time), and uniformly selecting state points from the value range as initial states.
(2) The angle of attack and the angle of roll being designed as a function of the magnitude of the speed
In the formula, V 1 、V mid 、V 2 、α max 、σ mid Determined from the aircraft characteristics and flight profile, where V 1 、V mid 、V 2 All the speed of switching the angle of attack profile is selected according to the aerodynamic characteristics of the aircraft, and V is the speed of switching the angle of attack profile according to the reentry task of the track 1 The value of (A) is between 5500 and 6000m/s, V 2 The value of (A) is between 2000 and 3000m/s, V mid The value of (a) is 4000-5000 m/s; alpha (alpha) ("alpha") max Is the maximum available angle of attack, α, of the aircraft L/Dmax The maximum lift-drag ratio attack angle of the aircraft is obtained; sigma mid The roll angle of the switching point, generally taken as σ mid ＝45°、σ 1 To the initial flight roll angle, σ 1 ＝60～80、σ 1 For end flight roll angle, σ 2 ＝20-40。
(3) And (3) simulating by using the initial condition, the attack angle and the roll angle section shown in the formulas (2) and (3), and storing an initial state and the aircraft terminal position to form a training sample, wherein the initial state is sample input, and the aircraft terminal position is sample output.
The online fly-around module of any no-fly zone comprises the following four steps:
step 10: calculating the position information of the no-fly zone in the geocentric coordinate system according to the longitude and latitude information of the no-fly zone, and calculating the coordinate information of the no-fly zone in the aircraft position coordinate system according to a conversion matrix between the geocentric coordinate system and the aircraft position coordinate system;
step 20: according to the current attack angle and the current roll angle of the aircraft, quickly predicting the flight track by using an offline-trained neural network;
and step 30: judging whether the estimated aircraft track intersects with the no-fly zone or not and the intersection time of the estimated aircraft track and the no-fly zone, and analyzing the influence degree of the aircraft on the no-fly zone as a basis for judging the inclination angle symbol;
step 40: and according to a set inclination angle symbol judgment rule, deciding the inclination angle symbol of the aircraft, and guiding the aircraft to bypass the no-fly zone.
Further, the coordinate system of step 10 is defined as:
(1) center of earth coordinate system O E -X E Y E Z E : origin O E Located in the earth's center, O E X E Axis pointing to spring equinox, O E Z E Axial north pole, O E Y E The axis and the other two axes form a right-hand coordinate system;
(2) position coordinate system O P -X P Y P Z P : origin O P At the center of mass of the aircraft, O P X P The axis points to the north, O P Y P The axis points along the geocentric radial direction to the sky, O P Z P The axes and the other two axes form a right-hand coordinate system pointing east.
Further, the method for solving the coordinates of the geocentric coordinate system according to the longitude and latitude comprises
Wherein R is e Is the earth radius, phi is latitude, and theta is longitude.
Further, the conversion method from the geocentric coordinate system to the position coordinate system is
Wherein phi p And Θ p Respectively the longitude and latitude of the aircraft centroid. L (phi) p ,Θ p ) In the form of
For the irregular no-fly zone, the irregular no-fly zone is usually represented by a series of discrete characteristic points, and for each discrete point, the coordinates of the discrete point in the aircraft position coordinate system are obtained according to the conversion method.
Further, the specific method for quickly predicting the flight trajectory in step 20 is as follows:
(1) acquiring the motion state of the current aircraft, including position, speed, track angle and course angle;
(2) setting the flight time of the aircraft;
(3) and inputting the parameters into the trained neural network to obtain the output aircraft terminal position.
Further, the specific method for analyzing the threat situation of the aircraft in step 30 is (as shown in fig. 3):
(1) calculating the distance between the track prediction terminal and each characteristic point of the no-fly zone, selecting the characteristic point with the minimum distance as p, and recording two adjacent characteristic points as p 1 And p 2 . Note that the starting point of the track is p S End point is p E 。
(2) Calculating the line segment p 1 p、p 2 p、p S p、p E p relative to a reference direction (the reference direction being the true north direction, i.e. O of the position coordinate system) P X P Axis) of the shaft, respectively
(3) And judging the relationship between the track end point and the no-fly area according to the size of the angle. If it is
Is greater than or equal to>
And &>
If the track end point is in the no-fly zone, the track end point is in the no-fly zone; otherwise, the track end point is outside the no-fly zone.
(4) And if the track end point is not in the no-fly zone, recording the flight time t of the aircraft at the moment, and executing (7), otherwise, executing (5).
(5) If the track end point is in the no-fly zone, calculating the track end point relative to the line segment p 1 p、p 2 And selecting a smaller value as the distance of the aircraft relative to the no-fly zone, and recording the distance as d.
(6) The track prediction time t is changed by using a dichotomy method, and the corresponding track end point position p 'is calculated' E Repeating the above process to solve the distance d' relative to the no-fly zone,until d' is less than a set threshold Δ d.
(7) Recording the time t for evaluating the threat level of an aircraft ⊥ And = t' (i =1,2,i =1 corresponding to a trajectory with a positive roll angle sign, i =2 corresponding to a trajectory with a negative roll angle sign), the analysis of the threat situation of the aircraft is completed.
Furthermore, the attack angle and the roll angle of the aircraft are determined during the track design, and cannot be changed, and the lateral track of the aircraft can be changed only by changing the sign of the roll angle, so that the aircraft bypasses a no-fly zone. The specific method for judging the aircraft roll angle symbol in the fourth step is as follows:
(1) setting a trajectory prediction time threshold t threshold (0<t threshold ) Comparing the time t when the trajectory intersects the no-fly zone ⊥1 And t ⊥2 And t threshold The magnitude relationship of (a);
(2) if t is ⊥1 And t ⊥2 Are all greater than t threshold If the aircraft keeps the current roll angle flight, the current flight roll angle sign is changed;
(3) if t is ⊥1 And t ⊥2 At least one of which is less than t threshold Then aircraft according to t ⊥1 And t ⊥2 The larger of which determines the roll angle sign. If the original direction is t predicted ⊥1 And t ⊥2 If the smaller direction is consistent, multiplying the current roll angle symbol by-1 to change the current flight direction; otherwise, it is multiplied by 1.
The invention provides a method for rapidly predicting the trajectory of an aircraft, a method for rapidly judging the relation between the predicted trajectory and a no-fly area and aircraft inclination angle symbol selection logic, aiming at the defect that the existing reentry aircraft can only encircle a no-fly area with a regular shape. The capability of the reentry aircraft in the autonomous fly-around no-fly zone and the residual flight capability after the reentry aircraft bypasses the no-fly zone are effectively improved.
Those skilled in the art will appreciate that those matters not described in detail in the present specification are not particularly limited to the specific examples described herein.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.
Claims (5)
1. A reentry aircraft arbitrary no-fly zone fly-around method based on intelligent trajectory prediction is characterized by comprising the following steps:
s1, establishing a reentry vehicle flight dynamics model;
s2, selecting different initial parameters of the aircraft, simultaneously setting an attack angle and a roll angle, and simulating by using the flight dynamics model in the S1 to obtain the terminal position of the aircraft; the initial parameters comprise height, speed, longitude, latitude, track angle and course angle;
s3, taking initial parameters, an attack angle, a roll angle and time of the aircraft as input, taking the terminal position of the aircraft as output, and training by adopting a BP neural network to obtain a trained neural network model;
s4, determining the position of the no-fly zone; predicting a flight track by using the trained neural network model according to the current attack angle and the current roll angle of the aircraft;
s5, judging the position relation between the flight track and the no-fly zone, and adjusting the inclination angle of the aircraft when the aircraft is influenced by the no-fly zone; the method for adjusting the roll angle of the aircraft comprises the following steps:
s51, the flight track is approximately a section of circular arc relative to the earth radius, and the current position of the aircraft is a track starting point p S The other end of the arc is a track end point p E The no-fly zone is represented by a plurality of characteristic points which are connected in sequence; calculating the distance between the track end point and all the characteristic points of the no-fly area; selecting the characteristic point p with the minimum distance and two characteristic points p connected with the point p 1 And p 2 ；
S52, calculating a line segment p 1 p、p 2 p、p S p、p E The angle of p with respect to the reference direction is respectively noted
S53, if
Is greater than or equal to>
And &>
In between, the arc end point is in the no-fly zone; otherwise, the track end point is outside the no-fly zone;
s54, if the track end point is outside the no-fly zone, recording the flight time t of the aircraft at the moment, and turning to S57, otherwise, turning to S55;
s55, calculating the track end point relative to the line segment p 1 p、p 2 Selecting a smaller value as the distance of the aircraft relative to the no-fly zone, and recording the distance as d;
s56, adjusting the track prediction time t by adopting a dichotomy method, and calculating the corresponding track end point position p' E Repeating S52-S55 to determine the distance d 'of the aircraft relative to the no-fly zone after the track prediction time is adjusted until d' is smaller than a set threshold value delta d;
s57, determining track prediction time t when the track is intersected with the no-fly zone ⊥ ＝t′；
S58, setting a track prediction threshold t threshold Comparing the time t when the trajectory intersects the no-fly zone ⊥1 And t ⊥2 And t threshold The magnitude relationship of (1); if t is ⊥1 And t ⊥2 Are all greater than t threshold The aircraft keeps flying at the current roll angle; if t ⊥1 And t ⊥2 In at leastHas a value less than t threshold Then aircraft follows t ⊥1 And t ⊥2 The larger of which determines the roll angle sign.
2. The method for winding any no-fly-off area of the reentry vehicle based on intelligent trajectory prediction as claimed in claim 1, wherein the no-fly-off area is irregular.
3. The method for winding the flight in any no-fly-zone of the reentry vehicle based on intelligent trajectory prediction as claimed in claim 1, wherein in S2, the attack angle and the roll angle are both functions with speed as an independent variable.
4. The method for detouring any no-fly-zone of the reentry vehicle based on the intelligent prediction of the trajectory according to claim 1, wherein in S4, the position information of the no-fly zone in the geocentric coordinate system is calculated according to the latitude and longitude information of the no-fly zone, and then the coordinate information of the no-fly zone in the position coordinate system of the vehicle is calculated according to the transformation matrix between the geocentric coordinate system and the position coordinate system of the vehicle, so as to determine the position of the no-fly zone.
5. The method for any no-fly-zone fly-around of a reentry vehicle based on intelligent trajectory prediction as claimed in claim 1, wherein in S4, the method for predicting the flight trajectory by using the trained neural network model comprises:
s41, acquiring the current altitude, speed, longitude, latitude, track angle and course angle of the aircraft;
s42, setting the flight time of the aircraft;
s43, taking the current altitude, speed, longitude, latitude, track angle, course angle of the aircraft and the flight time of the aircraft as input parameters, and predicting the flight track by using the trained neural network model.
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| CN114637311B (en) * | 2022-03-17 | 2024-06-07 | 北京航空航天大学 | Guidance method and system based on maneuver avoidance of multiple forbidden zones |
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