Multi-missile specified time collaborative interception terminal guidance method

Abstract

The invention relates to the field of guidance methods, and discloses a multi-missile specified time collaborative interception terminal guidance method, which comprises the following steps of: constructing a guidance model for intercepting a maneuvering target; deducing an estimated residual flight time expression according to the guidance model of the intercepted maneuvering target; defining a specified attack time error according to the estimated residual flight time expression; according to a specified attack time error, deriving an expression for estimating a first-order derivative of the residual flight time; deriving a specified attack time error and estimating by adopting a fixed time neural network interference observer; designing a specified time interception guidance law of the hypersonic speed target; on the basis of a proposed fixed time neural network interference observer and a specified time interception guidance law, specified time interception of the hypersonic speed target is realized; the method provided by the invention effectively solves the problem of low calculation efficiency in the guidance law design for cooperatively intercepting the hypersonic speed target at the specified time by the plurality of interception bullets.

Description

Technical Field

[0001] This invention relates to the field of guidance methods, specifically a multi-missile time-coordinated interception terminal guidance method. Background Technology

[0002] When intercepting hypersonic targets, the terminal guidance phase directly determines the interception accuracy and damage effectiveness of the interceptor missile. With the increasing use of anti-detection and anti-interception methods for hypersonic targets, the interception capability of a single interceptor missile is insufficient under short interception time windows and limited overload constraints. Coordinated guidance of multiple interceptor missiles can effectively improve the interception probability. Existing literature typically considers the interception guidance problem of maneuvering targets with controllable axial velocity, but this is not applicable to most hypersonic missiles. While trajectory shaping and parameter iteration are used to design a specified-time interception guidance law based on a virtual relative model, computational efficiency issues exist. To address the problems in the design of guidance laws for coordinated interception of hypersonic targets by multiple interceptor missiles at a specified time, this invention estimates the unknowns caused by target maneuvering and velocity changes based on a fixed-time neural network interference observer, and designs a specified-time coordinated interception guidance law based on a specified-time error model, proposing a terminal guidance method for coordinated interception of multiple missiles at a specified time. Summary of the Invention

[0003] The purpose of this invention is to provide a method for coordinated interception and terminal guidance of multiple missiles at a specified time, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a multi-missile time-coordinated interception terminal guidance method, comprising the following steps:

[0005] Step S1: Based on the characteristics of the target and the interceptor, construct a guidance model for intercepting maneuvering targets;

[0006] Step S2: Derive the expression for the estimated remaining flight time based on the guidance model for intercepting maneuvering targets;

[0007] Step S3: Define the specified attack time error based on the expression for the estimated remaining flight time;

[0008] Step S4: Based on the specified attack time error, derive the expression for the first derivative of the estimated remaining flight time. ;

[0009] Step S5: Calculate the specified attack time error. Differentiation and a fixed-time neural network disturbance observer are used to... Make an estimate;

[0010] Step S6: Based on the specified attack time error Differentiation and a fixed-time neural network disturbance observer are used to... Estimation is performed, a time-specified interception guidance law for hypersonic targets is designed, and the update law for neural network weights and the update law for the square root estimate of the upper bound of the neural network estimation error are given.

[0011] Step S7: When multiple interceptor missiles are in terminal flight, a two-dimensional planar maneuvering target interception guidance model is considered. Based on the proposed fixed-time neural network jamming observer and the specified-time interception guidance law, the specified-time interception of hypersonic targets is achieved.

[0012] As a preferred embodiment, in step S1, based on the characteristics of the target and the interceptor, the following guidance model for intercepting maneuvering targets is constructed:

[0013]

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] in, The relative distance between the projectile and the target. For the viewing angle, , These are the leading angles of the missile and the target, respectively. These are the missile acceleration and the target acceleration, respectively. For missile and target speed, , These are the missile's drag and lift, respectively. , These represent the drag and lift of the target, respectively. The drag coefficient, The lift coefficient, These are the dynamic pressures of the missile and the target, respectively. Atmospheric density, These are the reference area and mass of the missile and the target, respectively. It is the acceleration due to gravity;

[0022] In a two-dimensional attack plane, a guided target for coordinated interception of a hypersonic target by multiple interceptor missiles at a specified attack time is described as follows:

[0023]

[0024] in, The specified attack time is set.

[0025] As a preferred embodiment: the two-dimensional guidance model for intercepting maneuvering targets in S2 assumes... , and Since it is a constant, the following expression for the estimated remaining flight time can be derived.

[0026]

[0027] in, , .

[0028] Preferably: in step S3, for the equation The estimated remaining flight time, if it meets the requirements Then when At that time, it can be guaranteed The attack time error is defined as follows.

[0029]

[0030] in, This refers to the current moment.

[0031] Preferably, in step S4, the attack time error is specified. As can be seen from the definition, when hour, Terminal guidance end time ,but This enables the interception of hypersonic targets at a specified time.

[0032] As can be seen from note 1, the equation The mid-range guided target can be transformed into

[0033]

[0034] Equivalence Differentiating along the system trajectory yields

[0035]

[0036] Equation from the maneuvering target interception guidance model to the equation as well as The definition can be obtained The derivative satisfies the following equation

[0037]

[0038]

[0039]

[0040] Equation to the equation Substitute into the equation From the middle

[0041]

[0042]

[0043] And order , , Then the equation It can be simplified to

[0044] .

[0045] Preferably, in step S5, for the maneuvering target, due to the limited output of its actuator, the target maneuver... It is bounded, and it is assumed that... .

[0046] For the specified attack time error Differentiate and convert the equation Substituting, we can obtain

[0047]

[0048] in, ;

[0049] Considering the inability to obtain target maneuver information during the terminal guidance phase, a fixed-time neural network jamming observer is proposed by combining RBF NNs with a jamming observer. Make an estimate

[0050]

[0051] in

[0052]

[0053]

[0054]

[0055] For interference The estimated value, To specify the attack time error The estimated value, , These are estimates of the optimal weights for the neural network. For positive integers, For Gaussian functions, The number of neurons, The input to the neural network is assumed, and the neural network estimation error is assumed to be... satisfy , , for The estimated value, All are positive integers and satisfy the following conditions: , , , .

[0056] Preferably, in step S6, based on the equation Sum of equations The following hypersonic target interception guidance law is designed for a specified time.

[0057]

[0058] in, All are positive numbers and satisfy the following conditions: .

[0059] The following update laws are given for neural network weights and for the square root estimate of the upper bound of the neural network estimation error:

[0060]

[0061]

[0062] in, All are normal numbers.

[0063] As a preferred embodiment: In step S7, regarding the guidance problem of multiple interceptor missiles coordinating to intercept hypersonic targets at a specified time, if assumption 5-1 holds, consider the equation... to the equation The two-dimensional planar maneuvering target interception guidance model shown is based on the proposed fixed-time neural network jamming observer. and the designated time interception guidance law It can achieve the equation The guided target shown.

[0064] Compared with the prior art, the beneficial effects of this invention are as follows:

[0065] This invention addresses the problems in the design of guidance laws for the coordinated interception of hypersonic targets by multiple interceptor missiles at a specified time. It estimates the unknowns caused by target maneuvering and velocity changes based on a fixed-time neural network interference observer, and designs a coordinated interception guidance law based on a specified-time error model. This effectively solves the computational efficiency problem in the design of guidance laws for the coordinated interception of hypersonic targets by multiple interceptor missiles at a specified time. Attached Figure Description

[0066] Figure 1 This is a flowchart of the method in an embodiment of the present invention;

[0067] Figure 2 This is a diagram showing the results of multi-missile coordinated interception of hypersonic targets at a specified time, according to an embodiment of the present invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Example

[0070] Please see Figure 1 The multi-missile time-coordinated interception terminal guidance method shown in the diagram includes the following steps:

[0071] Step S1: Based on the characteristics of the target and the interceptor, construct a guidance model for intercepting maneuvering targets;

[0072] Step S2: Derive the expression for the estimated remaining flight time based on the guidance model for intercepting maneuvering targets;

[0073] Step S3: Define the specified attack time error based on the expression for the estimated remaining flight time;

[0074] Step S4: Based on the specified attack time error, derive the expression for the first derivative of the estimated remaining flight time. ;

[0075] Step S5: Calculate the specified attack time error. Differentiation and a fixed-time neural network disturbance observer are used to... Make an estimate;

[0076] Step S6: Based on the specified attack time error Differentiation and a fixed-time neural network disturbance observer are used to... Estimation is performed, a time-specified interception guidance law for hypersonic targets is designed, and the update law for neural network weights and the update law for the square root estimate of the upper bound of the neural network estimation error are given.

[0077] Step S7: When multiple interceptor missiles are in terminal flight, a two-dimensional planar maneuvering target interception guidance model is considered. Based on the proposed fixed-time neural network jamming observer and the specified-time interception guidance law, the specified-time interception of hypersonic targets is achieved.

[0078] In this embodiment, based on the characteristics of the target and the interceptor, the following guidance model for intercepting maneuvering targets is constructed in step S1:

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] in, The relative distance between the projectile and the target. For the viewing angle, , These are the leading angles of the missile and the target, respectively. These are the missile acceleration and the target acceleration, respectively. For missile and target speed, , These are the missile's drag and lift, respectively. , These represent the drag and lift of the target, respectively. The drag coefficient, The lift coefficient, These are the dynamic pressures of the missile and the target, respectively. Atmospheric density, These are the reference area and mass of the missile and the target, respectively. It is the acceleration due to gravity;

[0088] In a two-dimensional attack plane, a guided target for coordinated interception of a hypersonic target by multiple interceptor missiles at a specified attack time is described as follows:

[0089]

[0090] in, The specified attack time is set.

[0091] Furthermore, the two-dimensional guidance model for intercepting maneuvering targets in S2 assumes... , and Since it is a constant, the following expression for the estimated remaining flight time can be derived.

[0092]

[0093] in, , .

[0094] Furthermore, in step S3, for the equation The estimated remaining flight time, if it meets the requirements Then when At that time, it can be guaranteed The attack time error is defined as follows.

[0095]

[0096] in, This refers to the current moment.

[0097] In this embodiment, in step S4, the specified attack time error is determined. As can be seen from the definition, when hour, Terminal guidance end time ,but This enables the interception of hypersonic targets at a specified time.

[0098] As can be seen from note 1, the equation The mid-range guided target can be transformed into

[0099]

[0100] Differentiating the equation along the system trajectory yields...

[0101]

[0102] Equation from the maneuvering target interception guidance model to the equation as well as The definition can be obtained The derivative satisfies the following equation

[0103]

[0104]

[0105]

[0106] Equation to the equation Substitute into the equation From the middle

[0107]

[0108]

[0109] And order , , Then the equation It can be simplified to

[0110] ;

[0111] Furthermore, in step S5, for the maneuvering target, due to the limited output of its actuator, the target's maneuvering... It is bounded, and it is assumed that... .

[0112] For the specified attack time error Differentiate and convert the equation Substituting, we can obtain

[0113]

[0114] in, ;

[0115] Considering the inability to obtain target maneuver information during the terminal guidance phase, a fixed-time neural network jamming observer is proposed by combining RBF NNs with a jamming observer. Make an estimate

[0116]

[0117] in

[0118]

[0119]

[0120]

[0121] For interference The estimated value, To specify the attack time error The estimated value, , These are estimates of the optimal weights for the neural network. For positive integers, For Gaussian functions, The number of neurons, The input to the neural network is assumed, and the neural network estimation error is assumed to be... satisfy , , for The estimated value, All are positive integers and satisfy the following conditions: , , , .

[0122] Furthermore, in step S6, based on the equation Sum of equations The following hypersonic target interception guidance law is designed for a specified time.

[0123]

[0124] in, All are positive numbers and satisfy the following conditions: .

[0125] The following update laws are given for neural network weights and for the square root estimate of the upper bound of the neural network estimation error:

[0126]

[0127]

[0128] in, All are normal numbers.

[0129] Furthermore, in step S7, regarding the guidance problem of multiple interceptor missiles coordinating to intercept hypersonic targets at a specified time, if assumption 5-1 holds, consider the equation... to the equation The two-dimensional planar maneuvering target interception guidance model shown is based on the proposed fixed-time neural network jamming observer. and the designated time interception guidance law It can achieve the equation The guided target shown.

[0130] The proof is as follows, and the Lyapunov function is constructed as shown below.

[0131]

[0132] in, Equivalence Differentiate along the system trajectory and apply the equation Equation Sum of equations Substituting, we can obtain

[0133]

[0134] By the lemma, there exist positive constants. This makes the following inequality hold.

[0135]

[0136]

[0137] Equation Sum of equations Substitute into the equation In the middle, after simplification and rearrangement, we can obtain

[0138]

[0139] in,

[0140] , , .Depend on From the definition, we can know It is bounded. The domain that will converge to zero within a fixed time, and Both are bounded.

[0141] Further construct the following Lyapunov function

[0142]

[0143] Equivalence Differentiate along the system trajectory and apply the guidance law Substituting and simplifying, we get

[0144]

[0145] in, , As can be seen from the above proof process, It is bounded. The domain that converges to zero within a fixed time can thus achieve the equation. Medium-range guided target.

[0146] Simulation analysis was performed on the method proposed in this embodiment. Table 1 shows the initial lead angle and initial velocity of the three interceptor missiles at the initial moment of terminal guidance, the initial lead angle of the hypersonic target, and the initial relative distance and initial line-of-sight angle between the interceptor missiles and the hypersonic target. The initial position of the hypersonic target in the guidance plane is (0, 22) km, and the initial velocity is... m / s, maneuvering mode is Set a specified attack time s, the maximum normal acceleration of the interceptor missile g, the simulation step size is 1ms, the aerodynamic parameters of the interceptor are shown in Table 2, and the reference area of ​​the interceptor is 0.1127. The hypersonic target has a mass of 245 kg and a reference area of ​​0.4839 m². The aerodynamic parameters are shown in Table 3. The interceptor missile 1 has a mass of 907 kg and a reference area of ​​0.4839 m². Its guidance parameters are as follows: , , , The guidance parameters of interceptor missile 2 are: , , , The guidance parameters of interceptor missile 3 are: , , , The remaining guidance parameters of the three interceptor missiles are identical, and are respectively... , , , , , , , , , , The number of neurons is set to 20. Neuron center matrix The coordinates are all in the range [-55, 55] and [-5, 5]. , The Gaussian function width is determined by uniformly selecting values ​​between these ranges. Simulation results of three interceptor missiles coordinating to intercept a hypersonic target at a specified time are as follows: Figure 2 As shown.

[0147] Table 1 Initial conditions for interceptor missiles and hypersonic targets

[0148]

[0149] Table 2. Lift and Drag Coefficients of Interceptor Projectiles

[0150]

[0151] Table 3 Drag coefficients of hypersonic targets

[0152]

[0153] Depend on Figure 2 As can be seen from (a) and (d), all three interceptor missiles were able to effectively intercept hypersonic targets within the specified time, with miss distances of 0.51m, 0.75m, and 0.23m, respectively, and interception times of 7.259s, 7.191s, and 7.303s, respectively. Figure 2 (c) gives the specified attack time errors of the three interceptor missiles at the end of terminal guidance as 0.059s, -0.009s, and 0.103s, respectively. Figure 2 As can be seen from the convergence curves of the specified attack time error and the estimated value of the specified attack time error in (c) and (f), the designed fixed-time neural network disturbance observer can effectively estimate unknown disturbances.

[0154] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0155] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multi-missile time-coordinated interception terminal guidance method, characterized in that, Includes the following steps: Step S1: Based on the characteristics of the target and the interceptor, construct a guidance model for intercepting maneuvering targets; Step S2: Derive the expression for the estimated remaining flight time based on the guidance model for intercepting maneuvering targets; Step S3: Define the specified attack time error based on the expression for the estimated remaining flight time; Step S4: Based on the specified attack time error, derive the expression for the first derivative of the estimated remaining flight time. ; Step S5: Calculate the specified attack time error. Differentiation and a fixed-time neural network disturbance observer are used to... Make an estimate; Step S6: Based on the specified attack time error Differentiation and a fixed-time neural network disturbance observer are used to... Estimation is performed, a time-specified interception guidance law for hypersonic targets is designed, and the update law for neural network weights and the update law for the square root estimate of the upper bound of the neural network estimation error are given. Step S7: When multiple interceptor missiles are in terminal flight, a two-dimensional planar maneuvering target interception guidance model is considered. Based on the proposed fixed-time neural network jamming observer and the specified-time interception guidance law, the specified-time interception of hypersonic targets is achieved.

2. The multi-missile time-coordinated interception terminal guidance method according to claim 1, characterized in that: In step S1, based on the characteristics of the target and the interceptor, the following guidance model for intercepting maneuvering targets is constructed: ， ， ， ， ， ， ， ， in, The relative distance between the projectile and the target. For the viewing angle, , These are the leading angles of the missile and the target, respectively. These are the missile acceleration and the target acceleration, respectively. For missile and target speed, , These are the missile's drag and lift, respectively. , These represent the drag and lift of the target, respectively. The drag coefficient, The lift coefficient, These are the dynamic pressures of the missile and the target, respectively. Atmospheric density, These are the reference area and mass of the missile and the target, respectively. It is the acceleration due to gravity; In a two-dimensional attack plane, a guided target for coordinated interception of a hypersonic target by multiple interceptor missiles at a specified attack time is described as follows: ， in, The specified attack time is set.

3. The multi-missile time-coordinated interception terminal guidance method according to claim 2, characterized in that: The two-dimensional guidance model for intercepting maneuvering targets in S2 assumes... , and Since it is a constant, the following expression for the estimated remaining flight time can be derived. ， in, , .

4. The multi-missile time-coordinated interception terminal guidance method according to claim 3, characterized in that: In step S3, for the equation The estimated remaining flight time, if it meets the requirements Then when At that time, it can be guaranteed The attack time error is defined as follows. ， in, This refers to the current moment.

5. The multi-missile time-coordinated interception terminal guidance method according to claim 4, characterized in that: In step S4, the attack time error is specified. As can be seen from the definition, when hour, Terminal guidance end time ,but This enables the interception of hypersonic targets at a specified time. As can be seen from note 1, the equation The mid-range guided target can be transformed into ， Equivalence Differentiating along the system trajectory yields ， Equation from the maneuvering target interception guidance model to the equation as well as The definition can be obtained The derivative satisfies the following equation ， ， ， Equation to the equation Substitute into the equation From the middle ， ， And order , , Then the equation It can be simplified to 。 6. The multi-missile time-coordinated interception terminal guidance method according to claim 5, characterized in that: In step S5, for the maneuvering target, due to the limited output of its actuator, the target's maneuverability is limited. It is bounded, and it is assumed that... , For the specified attack time error By differentiating and substituting the equation, we can obtain... ， in, ; Considering the inability to obtain target maneuver information during the terminal guidance phase, a fixed-time neural network jamming observer is proposed by combining RBF NNs with a jamming observer. Make an estimate ， in ， ， ， For interference The estimated value, To specify the attack time error The estimated value, , These are estimates of the optimal weights for the neural network. For positive integers, For Gaussian functions, The number of neurons, The input to the neural network is assumed, and the neural network estimation error is assumed to be... satisfy , , for The estimated value, All are positive integers and satisfy the following conditions: , , , .

7. The multi-missile time-coordinated interception terminal guidance method according to claim 6, characterized in that: In step S6, based on the equation Sum of equations The following hypersonic target interception guidance law is designed for a specified time. ， in, All are positive numbers and satisfy the following conditions: , The following update laws are given for neural network weights and for the square root estimate of the upper bound of the neural network estimation error: ， ， in, All are normal numbers.

8. The multi-missile time-coordinated interception terminal guidance method according to claim 7, characterized in that: In step S7, regarding the guidance problem of multiple interceptor missiles coordinating to intercept hypersonic targets at a specified time, if assumption 5-1 holds, consider the equation... to the equation The two-dimensional planar maneuvering target interception guidance model shown is based on the proposed fixed-time neural network jamming observer. and the designated time interception guidance law It can achieve the equation The guided target shown.

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