Cooperative defense control method and system for underwater manned and unmanned cluster

Abstract

The invention provides a cooperative defense control method and system for an underwater manned / unmanned cluster, and the method comprises the following steps: constructing an interference type UUV target optimization function, and obtaining the control input of the current interference type UUV for the maximum interference of a dangerous target detection range; constructing a dangerous target identification bait type UUV probability model, obtaining the maximum identification probability of the dangerous target to the bait type UUV, and obtaining the control input corresponding to the bait type UUV; a dangerous target identification manned platform probability model is constructed, the identification probability of the minimized dangerous target to the manned platform is obtained, and the control input of the manned platform is obtained; according to the control input corresponding to each interference type UUV, the bait type UUV and the manned platform, controlling the UUVs to synchronously execute maneuvering, and updating the positions of the UUVs; according to the method, the interference type UUV actively suppresses a dangerous target detection range, the bait type UUV simulates a manned platform feature attraction attack and a multi-cooperation mechanism of active avoidance of the manned platform, and the survival probability of the manned platform under the dangerous target attack is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of technology, and in particular to a collaborative defense control method and system for underwater manned and unmanned swarms. Background Technology

[0002] With the rapid development of UUVs and other unmanned systems, underwater operations are gradually forming manned-unmanned swarms centered around manned platforms and involving multiple UUVs in collaboration. During these operations, the swarms may face attacks from dangerous targets. Therefore, developing effective defensive decisions is crucial for the swarms to effectively respond to such attacks.

[0003] The guidance system and method for anti-interception and coordinated attack of UAV swarms, disclosed in publication number CN117176289A, includes a swarm communication system, a switching system, a frequency adjustment system, a coordinated control system, an identification and tracking system, and a path planning and obstacle avoidance system. The swarm communication system enables communication within the UAV swarm, allowing UAVs in the swarm to exchange information and coordinate operations. The switching system monitors interference in the current communication frequency band and automatically switches to a less congested frequency band as needed.

[0004] Currently, there is a lack of a targeted architecture for collaborative defense of heterogeneous manned and unmanned underwater clusters. It fails to distinguish the collaborative mechanisms between two types of heterogeneous unmanned platforms: interference suppression and deception / camouflage. Furthermore, it lacks a collaborative control model based on dynamic detection range compression and identification probability optimization. As a result, it cannot effectively cope with the high-precision detection and attacks on manned platforms by underwater threats such as dangerous targets. This leads to insufficient reliability of underwater collaborative defense and reduces the probability of manned platforms surviving under attacks from dangerous targets. Summary of the Invention

[0005] In view of this, the present invention proposes an intelligent collaborative defense control method and system for underwater manned and unmanned swarms. Through multiple collaborative mechanisms, including interference-type UUVs actively suppressing the detection range of dangerous targets, decoy-type UUVs simulating the characteristics of manned platforms to attract attacks, and manned platforms actively avoiding attacks, the survival probability of manned platforms under attacks from dangerous targets is effectively improved.

[0006] The technical solution of the present invention is implemented as follows: In the first aspect, the present invention provides a collaborative defense and control method for underwater manned and unmanned swarms, wherein the underwater manned and unmanned swarms include manned platforms and multiple UUV unmanned swarms, and the types of UUV unmanned swarms include interference-type UUVs and decoy-type UUVs. Interference-type UUVs are used to reduce the detection range of dangerous targets; decoy-type UUVs are used to disguise themselves as manned platforms to attract dangerous targets to attack.

[0007] The method includes the following steps:

[0008] S1, construct a global coordinate system, initialize the position and velocity states of the manned platform, the jamming UUV, the decoy UUV, and the dangerous target, and set the jamming coefficient of the jamming UUV and the camouflage coefficient of the decoy UUV;

[0009] S2, based on the location of the dangerous target, the location of each interfering UUV and its interference coefficient, construct the interfering UUV target optimization function, and based on the interfering UUV target optimization function, obtain the control input that maximizes the interference of the current interfering UUV on the detection range of the dangerous target;

[0010] S3. Based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient, construct a probability model for dangerous target to identify decoy UUV. Based on the probability model for dangerous target to identify decoy UUV, obtain the probability of maximizing the dangerous target to identify the decoy UUV, and obtain the control input of the corresponding decoy UUV.

[0011] S4. Construct a probability model for identifying a manned platform from a dangerous target based on the distance between the dangerous target and the manned platform. Based on the probability model for identifying a manned platform from a dangerous target, obtain the probability of the dangerous target identifying the manned platform by minimizing the probability, and obtain the control input of the manned platform.

[0012] S5 controls each of the jamming UUVs, decoy UUVs, and manned platforms to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

[0013] Based on the above technical solutions, preferably, in step S1, the global coordinate system takes the initial position of the manned platform as the origin, the eastward direction as the positive x-axis, the northward direction as the positive y-axis, and the vertical upward direction as the positive z-axis; the initial position vector values ​​and velocity vector values ​​of the manned platform, the jamming UUV, the decoy UUV, and the dangerous target in the three coordinate axes of the global coordinate system are obtained; the jamming coefficient of the jamming UUV is used to characterize the strength of the jamming ability of the corresponding jamming UUV to interfere with the range of the dangerous target; the camouflage coefficient of the decoy UUV is used to characterize the strength of the ability of the corresponding decoy UUV to simulate the characteristics of the manned platform to attract the dangerous target.

[0014] Based on the above technical solutions, preferably, step S2 includes the following sub-steps:

[0015] Obtain the distance between the interfering UUV and the dangerous target, and establish a negative exponential relationship between the square of the distance between the interfering UUV and the dangerous target and the first distance attenuation coefficient to construct the first distance attenuation term;

[0016] Based on the product of the first distance attenuation term and the interference intensity coefficient corresponding to the interference type UUV, construct the target optimization function for the interference type UUV;

[0017] Based on the target optimization function of the interference-type UUV, the interference value of the interference-type UUV to the dangerous target in the current state is calculated. With the goal of maximizing the detection range of the dangerous target, the optimal control input of the corresponding interference-type UUV is solved.

[0018] Based on the above technical solutions, preferably, step S2 further includes obtaining the actual detection range of the dangerous target after interference, including the following sub-steps:

[0019] Iterate through all interfering UUVs, determine whether they are within the initial detection range of the dangerous target, and obtain the number of effective interfering UUVs within the initial detection range of the dangerous target;

[0020] For each effective interference-type UUV, the corresponding interference effect factor is calculated based on its interference coefficient and distance from the hazardous target;

[0021] The initial detection range of the dangerous target is preset. The interference effect factors corresponding to all effective interference UUVs are multiplied together, and the result is multiplied with the initial detection range of the dangerous target to obtain the true detection range of the dangerous target after interference.

[0022] Based on the above technical solutions, preferably, step S3 includes the following sub-steps:

[0023] Obtain the distance between the decoy UUV and the dangerous target;

[0024] The optimal recognition distance between the decoy UUV and the dangerous target is preset. The square of the difference between the current distance and the optimal recognition distance is calculated and multiplied by the second distance attenuation coefficient to construct the first negative exponential function as the exponential term.

[0025] Add the first negative exponential function to the first correction coefficient, and calculate the reciprocal of the sum as the second distance attenuation term;

[0026] Based on the product of the second distance attenuation term and the camouflage coefficient corresponding to the decoy UUV, a probabilistic model for identifying decoy UUVs as dangerous targets is constructed.

[0027] Based on the probability model for identifying decoy UUVs in the presence of dangerous targets, the probability of a dangerous target recognizing a current decoy UUV is calculated. With the goal of maximizing this recognition probability, the optimal control input for the corresponding decoy UUV is solved.

[0028] Based on the above technical solutions, preferably, step S4 includes the following sub-steps:

[0029] Obtain the distance between the manned platform and the dangerous target, and construct a second negative exponential function by multiplying the square of the distance between the interfering UUV and the dangerous target by the third distance attenuation coefficient as the exponential term;

[0030] Add the second negative exponential function to the second correction coefficient, and construct a probability model for identifying manned platforms of dangerous targets based on the reciprocal of the sum.

[0031] Based on the probability model for identifying manned platforms by dangerous targets, the probability of a dangerous target identifying a manned platform in the current state is calculated. With the goal of minimizing this identification probability, the optimal control input for the corresponding manned platform is solved.

[0032] Based on the above technical solutions, preferably, step S5 includes the following sub-steps:

[0033] The control input of the current interfering UUV is calculated by multiplying the difference vector between the current position of the dangerous target and the current position of the corresponding interfering UUV by the gain coefficient of the corresponding interfering UUV.

[0034] The updated position of the interfering UUV at the next moment is calculated by adding the current position of the interfering UUV at the current moment with the control input of the current interfering UUV.

[0035] The distance deviation of the decoy UUV is calculated based on the difference vector between the current location of the dangerous target and the current location of the corresponding decoy UUV, and the difference between the vector and the optimal recognition distance.

[0036] Based on the difference vector between the current position of the dangerous target and the current position of the corresponding decoy UUV, the unit vector pointing the decoy UUV towards the dangerous target is calculated.

[0037] The control input of the current decoy UUV is calculated based on the distance deviation of the decoy UUV, the unit vector of the decoy UUV pointing towards the dangerous target, and the corresponding gain coefficient of the decoy UUV.

[0038] The updated position of the decoy UUV at the next moment is calculated by adding the current position of the decoy UUV at the current moment with the control input of the current decoy UUV.

[0039] Based on the difference vector between the current position of the dangerous target and the current position of the manned platform, and the target safety distance between the dangerous target and the manned platform, the safety distance deviation of the manned platform is calculated.

[0040] Based on the difference vector between the current position of the manned platform and the current position of the dangerous target, the unit vector pointing from the dangerous target to the manned platform is calculated;

[0041] The control input of the manned platform is calculated based on the safe distance deviation of the manned platform, the unit vector of the dangerous target pointing to the manned platform, and the gain coefficient of the manned platform.

[0042] The updated position of the manned platform at the next moment is calculated by adding the current position of the manned platform to the control input of the manned platform.

[0043] Secondly, the present invention provides a cooperative defense control system for underwater manned and unmanned swarms, implemented using a cooperative defense control method for underwater manned and unmanned swarms, including:

[0044] The initialization module is used to build a global coordinate system, initialize the position and velocity states of manned platforms, jamming UUVs, decoy UUVs and dangerous targets, and set the jamming coefficient of jamming UUVs and the camouflage coefficient of decoy UUVs.

[0045] The interference-type UUV control module is used to construct an interference-type UUV target optimization function based on the location of the hazardous target, the location of each interference-type UUV and its interference coefficient, and obtain the control input that maximizes the interference of the current interference-type UUV on the detection range of the hazardous target based on the interference-type UUV target optimization function;

[0046] The decoy UUV control module is used to construct a probability model for identifying the decoy UUV based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient. Based on the probability model for identifying the decoy UUV, the module obtains the maximum probability of the dangerous target recognizing the decoy UUV and obtains the control input for the corresponding decoy UUV.

[0047] The manned platform control module is used to construct a probability model for identifying the manned platform based on the distance between the dangerous target and the manned platform. Based on the probability model, it obtains the minimum probability of the dangerous target identifying the manned platform and thus obtains the control input for the manned platform.

[0048] The action execution module is used to control each jamming UUV, decoy UUV, and manned platform to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

[0049] Thirdly, the present invention provides an electronic device, including at least one processor, at least one memory, a communication interface, and a bus; wherein the processor, memory, and communication interface communicate with each other through the bus; the memory stores a program for a collaborative defense control method for an underwater manned / unmanned swarm that can be executed by the processor, and the program for the collaborative defense control method for an underwater manned / unmanned swarm is configured to implement such a collaborative defense control method for an underwater manned / unmanned swarm.

[0050] Fourthly, the present invention provides a computer-readable storage medium storing a program for a collaborative defense control method for an underwater manned / unmanned swarm, wherein the program, when executed, implements the collaborative defense control method for an underwater manned / unmanned swarm.

[0051] The cooperative defense and control method and system for underwater manned and unmanned swarms of the present invention have the following advantages over the prior art:

[0052] (1) Through the multi-coordinated mechanism of actively suppressing the detection range of dangerous targets by interference-type UUVs, attracting attacks by simulating the characteristics of manned platforms by decoy-type UUVs, and actively avoiding manned platforms, the risk of manned platforms being identified and hit is greatly reduced, providing efficient protection for core equipment and personnel.

[0053] (2) By adopting a control strategy based on probability models and optimization objectives, the jamming UUV, decoy UUV and manned platform can autonomously calculate the optimal control command according to the real-time battlefield situation, thus realizing the intelligent and adaptive collaborative defense of the cluster. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart of the collaborative defense control method for underwater manned and unmanned swarms according to the present invention. Detailed Implementation

[0056] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0057] like Figure 1 As shown, the present invention provides a collaborative defense and control method for underwater manned and unmanned swarms. The underwater manned and unmanned swarms include manned platforms and multiple UUV unmanned swarms. The types of UUV unmanned swarms include interference UUVs and decoy UUVs. Interference UUVs are used to reduce the detection range of dangerous targets; decoy UUVs are used to disguise themselves as manned platforms to attract dangerous targets to attack.

[0058] It should be noted that the manned-unmanned swarm consists of manned platforms and multiple UUVs. There are two types of UUVs: jamming and decoy. Let the number of manned platforms in the swarm be 1, the number of jamming UUVs be m, the number of decoy UUVs be n, and the number of dangerous targets be 1. The jamming UUVs can interfere with the dangerous targets, reducing their detection range. The decoy UUVs can disguise the characteristics of manned platforms, thereby luring the dangerous targets to identify the decoy UUVs as manned platforms, thus inducing the dangerous targets to attack them and protecting the manned platforms from attack.

[0059] In this embodiment, a multi-coordinated mechanism is employed, which involves an interference-type UUV actively suppressing the detection range of dangerous targets, a decoy-type UUV simulating the characteristics of manned platforms to attract attacks, and manned platforms actively avoiding attacks. This greatly reduces the risk of manned platforms being identified and hit, providing efficient protection for core equipment and personnel.

[0060] The method includes the following steps:

[0061] S1. Construct a global coordinate system, initialize the position and velocity states of the manned platform, the jamming UUV, the decoy UUV, and the dangerous target, and set the jamming coefficient of the jamming UUV and the camouflage coefficient of the decoy UUV.

[0062] In step S1, the global coordinate system is defined with the initial position of the manned platform as the origin, the eastward direction as the positive x-axis, the northward direction as the positive y-axis, and the vertical upward direction as the positive z-axis. The initial position vector values ​​and velocity vector values ​​of the manned platform, the jamming UUV, the decoy UUV, and the dangerous target in the three coordinate axes of the global coordinate system are obtained.

[0063] It should be noted that some people's platform location is p s =[x s y s , z s ] T The speed is v s =[v sx v sy v sz ] T The number of interfering UUVs is m, and the position of the i-th interfering UUV is p. m,i =[x m,i y m,i , z m,i ] T The speed is v m,i =[v m,i,x v m,i,y v m,i,z ] T The interference coefficient of the interfering UUV is η. iThe interference coefficient of the interference-type UUV is used to characterize the strength of the interference capability of the corresponding interference-type UUV to the range of dangerous targets.

[0064] The number of decoy UUVs is n, and the position of the j-th decoy UUV is p. n,j =[x n,j y n,j , z n,j ] T The speed is v n,j =[v n,j,x v n,j,y v n,j,z ] T The camouflage coefficient is ξ j The camouflage coefficient of a decoy UUV is used to characterize the ability of the corresponding decoy UUV to simulate the characteristics of a manned platform and attract dangerous targets.

[0065] The location of the dangerous target is p g =[x g y g , z g ] T The speed is v g =[v gx v gy v gz ] T The detection range of a dangerous target under undisturbed conditions is R. g .

[0066] S2. Based on the location of the dangerous target, the location of each interfering UUV and its interference coefficient, construct the interfering UUV target optimization function. Based on the interfering UUV target optimization function, obtain the control input that maximizes the interference of the current interfering UUV on the detection range of the dangerous target.

[0067] Step S2 includes the following sub-steps:

[0068] Obtain the distance between the interfering UUV and the dangerous target, and establish a negative exponential relationship between the square of the distance between the interfering UUV and the dangerous target and the first distance attenuation coefficient to construct the first distance attenuation term;

[0069] Based on the product of the first distance attenuation term and the interference intensity coefficient corresponding to the interference type UUV, construct the target optimization function for the interference type UUV;

[0070] Based on the target optimization function of the interference-type UUV, the interference value of the interference-type UUV to the dangerous target in the current state is calculated. With the goal of maximizing the detection range of the dangerous target, the optimal control input of the corresponding interference-type UUV is solved.

[0071] In this embodiment, the expression for the UUV objective optimization function is:

[0072]

[0073] In the formula, u m,i is the control input for the i-th interference-type UUV, a is the interference attenuation coefficient, a>0.

[0074] In this embodiment, by constructing a target optimization function with the interference coefficient and negative exponential distance attenuation term as the core, the jamming UUV can autonomously calculate and dynamically adjust its optimal control command to approach dangerous targets, thereby maximizing the suppression of the detection range of dangerous targets and improving the overall defense capability.

[0075] Step S2 also includes obtaining the actual detection range of the dangerous target after interference, including the following sub-steps:

[0076] Iterate through all interfering UUVs, determine whether they are within the initial detection range of the dangerous target, and obtain the number of effective interfering UUVs within the initial detection range of the dangerous target;

[0077] For each effective interference-type UUV, the corresponding interference effect factor is calculated based on its interference coefficient and distance from the hazardous target;

[0078] The initial detection range of the dangerous target is preset. The interference effect factors corresponding to all effective interference UUVs are multiplied together, and the result is multiplied with the initial detection range of the dangerous target to obtain the true detection range of the dangerous target after interference.

[0079] In this embodiment, the expression for obtaining the true detection range of a dangerous target after interference is:

[0080]

[0081] In the formula, a is the interference attenuation coefficient, a>0; ||·|| represents the Euclidean distance, which means that the interfering UUV will only interfere with the dangerous target when it is within the uninterrupted detection range Rg; m0 represents the number of interfering UUVs interfering with the dangerous target, 1≤m0≤m; when the dangerous target is uninterrupted, R′ g =R g .

[0082] In this embodiment, by comprehensively considering the number of effective jamming UUVs, their individual jamming capabilities, and their relative distance to dangerous targets, the superimposed jamming effect is accurately quantified by multiplication. This allows for the dynamic calculation of the actual detection range of dangerous targets after being jammed, providing the entire cluster with real-time and accurate environmental perception capabilities. This provides a key decision-making basis for the deployment of decoys and the formulation of manned platform avoidance strategies.

[0083] S3. Based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient, construct a probability model for dangerous target to identify decoy UUV. Based on the probability model for dangerous target to identify decoy UUV, obtain the probability of maximizing the dangerous target's recognition of the decoy UUV, and obtain the control input of the corresponding decoy UUV.

[0084] Step S3 includes the following sub-steps:

[0085] Obtain the distance between the decoy UUV and the dangerous target;

[0086] The optimal recognition distance between the decoy UUV and the dangerous target is preset. The square of the difference between the current distance and the optimal recognition distance is calculated and multiplied by the second distance attenuation coefficient to construct the first negative exponential function as the exponential term.

[0087] Add the first negative exponential function to the first correction coefficient, and calculate the reciprocal of the sum as the second distance attenuation term;

[0088] Based on the product of the second distance attenuation term and the camouflage coefficient corresponding to the decoy UUV, a probabilistic model for identifying decoy UUVs as dangerous targets is constructed.

[0089] Based on the probability model for identifying decoy UUVs in the presence of dangerous targets, the probability of a dangerous target recognizing a current decoy UUV is calculated. With the goal of maximizing this recognition probability, the optimal control input for the corresponding decoy UUV is solved.

[0090] It should be noted that when there are multiple targets within the detection range of a dangerous target, such as when the dangerous target detects both a manned platform and a decoy UUV, the dangerous target will prioritize attacking the target with the higher probability of identification. Therefore, the goal of a manned platform is to minimize the probability of being identified by the dangerous target, while the goal of a decoy UUV is to maximize the probability of being identified by the dangerous target as a manned platform.

[0091] The expression for the dangerous target identification decoy UUV probability model in this embodiment is:

[0092]

[0093] In the formula, p(p g ,p n,j ξ represents the probability of a dangerous target recognizing a decoy UUV in the current state, λ is the second distance attenuation coefficient, μ is the first correction coefficient, R0 is the optimal recognition distance, λ>0, μ>0, R0>0, and ξ j ξ is the camouflage coefficient, 0 < ξ j <1;‖p g -p n，j ‖ represents the distance between the dangerous target and the j-th decoy UUV, ‖p g -p n，jThe closer the decoy UUV is to R0, the higher the probability that a dangerous target will mistake it for a manned platform; n,j This is the control input for the j-th decoy UUV.

[0094] Based on the above control strategy for decoy UUVs, the decoy UUV should maintain the optimal identification distance from the dangerous target to maximize the attack effect. The optimal identification distance is determined by the following considerations: if the dangerous target is too close to the decoy UUV, it will see through the decoy UUV's camouflage, rendering the decoy effect ineffective; if the dangerous target is too far away from the decoy UUV, the camouflage features of the decoy UUV will not be obvious to the dangerous target, and the probability of the dangerous target identifying the decoy UUV as a manned platform will also decrease. Therefore, there exists an optimal identification distance at which the dangerous target is more likely to identify the decoy UUV as a manned platform.

[0095] This embodiment introduces an optimal identification distance parameter and constructs a probability model that integrates the camouflage coefficient and the negative exponential distance function. The decoy UUV can accurately quantify the probability of itself being misidentified by dangerous targets and generate optimal control commands to drive itself to maintain the best deception distance from dangerous targets. This effectively improves the success rate of deception as a false target, actively attracts and disperses the firepower of dangerous targets, and builds a reliable second deception defense barrier for manned platforms.

[0096] S4. Construct a probability model for identifying a manned platform from a dangerous target based on the distance between the dangerous target and the manned platform. Based on the probability model for identifying a manned platform from a dangerous target, obtain the probability of the dangerous target identifying the manned platform by minimizing the probability, and obtain the control input of the manned platform.

[0097] Step S4 includes the following sub-steps:

[0098] Obtain the distance between the manned platform and the dangerous target, and construct a second negative exponential function by multiplying the square of the distance between the interfering UUV and the dangerous target by the third distance attenuation coefficient as the exponential term;

[0099] Add the second negative exponential function to the second correction coefficient, and construct a probability model for identifying manned platforms of dangerous targets based on the reciprocal of the sum.

[0100] Based on the probability model for identifying manned platforms by dangerous targets, the probability of a dangerous target identifying a manned platform in the current state is calculated. With the goal of minimizing this identification probability, the optimal control input for the corresponding manned platform is solved.

[0101] In this embodiment, the expression for the probability model of identifying dangerous targets on a manned platform is:

[0102]

[0103] In the formula, β is the third distance attenuation coefficient, γ is the second correction coefficient, and R′ represents the actual detection range of the manned platform within the dangerous target. g Within the space, the closer a dangerous target is to a manned platform, the higher the probability that the dangerous target will identify the manned platform. s For manned platforms, control inputs are required.

[0104] This embodiment constructs a probability model with negative exponential decay based on the squared distance. This allows manned platforms to identify the probability of being detected by dangerous targets in real time and generate optimal evasion instructions with the goal of minimizing this probability. This drives the platform to continuously move away from dangerous targets or maintain a safe distance, thereby significantly reducing the risk of being detected, identified, and attacked. Ultimately, this ensures the survivability of core combat units in the collaborative defense system.

[0105] S5 controls each of the jamming UUVs, decoy UUVs, and manned platforms to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

[0106] Step S5 includes the following sub-steps:

[0107] The control input of the current interfering UUV is calculated by multiplying the difference vector between the current position of the dangerous target and the current position of the corresponding interfering UUV by the gain coefficient of the corresponding interfering UUV.

[0108] The updated position of the interfering UUV at the next moment is calculated by adding the current position of the interfering UUV at the current moment with the control input of the current interfering UUV.

[0109] The expression for the location update of the interfering UUV is:

[0110] p m，i,new =p m，i,current +u m，i

[0111] u m,i =k m，i ·(p g -p m，i，current )

[0112] In the formula, k m，i Let p be the gain coefficient of the i-th interfering UUV. m，i，current p represents the current location of the i-th jamming UUV. m，i，new This is the update position for the next moment of the interference-type UUV.

[0113] The distance deviation of the decoy UUV is calculated based on the difference vector between the current location of the dangerous target and the current location of the corresponding decoy UUV, and the difference between the vector and the optimal recognition distance.

[0114] Based on the difference vector between the current position of the dangerous target and the current position of the corresponding decoy UUV, the unit vector pointing the decoy UUV towards the dangerous target is calculated.

[0115] The control input of the current decoy UUV is calculated based on the distance deviation of the decoy UUV, the unit vector of the decoy UUV pointing towards the dangerous target, and the corresponding gain coefficient of the decoy UUV.

[0116] The updated position of the decoy UUV at the next moment is calculated by adding the current position of the decoy UUV at the current moment with the control input of the current decoy UUV.

[0117] One algorithm for updating the position of decoy UUVs is

[0118] p n，j，new =p n，j，current +u n，j

[0119]

[0120] In the formula, k n，j Let p be the gain coefficient of the j-th decoy UUV. n，j，current For the current location of the j-th decoy UUV, p n，j，new This is the updated position of the decoy UUV at the next moment; Let |p| represent the unit vector pointing from the j-th decoy UUV towards the dangerous target. g -p n,j，current || represents the current distance between the j-th decoy UUV and the dangerous target, (||p g -p n，j ||-R0) represents the deviation between the current distance and the optimal recognition distance.

[0121] Based on the difference vector between the current position of the dangerous target and the current position of the manned platform, and the target safety distance between the dangerous target and the manned platform, the safety distance deviation of the manned platform is calculated.

[0122] Based on the difference vector between the current position of the manned platform and the current position of the dangerous target, the unit vector pointing from the dangerous target to the manned platform is calculated;

[0123] The control input of the manned platform is calculated based on the safe distance deviation of the manned platform, the unit vector of the dangerous target pointing to the manned platform, and the gain coefficient of the manned platform.

[0124] The updated position of the manned platform at the next moment is calculated by adding the current position of the manned platform to the control input of the manned platform.

[0125] The expression for updating the platform location is:

[0126] p s,new =p s,current +u s

[0127]

[0128] In the formula, k s p represents the gain coefficient for manned platforms. s,current This is the current location of the platform, p s,new This is the next updated location on the platform. Let ||p| represent the unit vector pointing from the hazardous target to the manned platform. g -p s，current || represents the current distance between the hazardous target and the manned platform, and || represents the target safe distance between the manned platform and the hazardous target. (||p g -p s，current ||-R1) represents the deviation between the current distance and the target's safe distance.

[0129] This embodiment employs a control strategy based on a probability model and optimization objectives, enabling jamming UUVs, decoy UUVs, and manned platforms to autonomously calculate optimal control commands based on the real-time battlefield situation, thus achieving intelligent and adaptive collaborative defense of the cluster.

[0130] Secondly, the present invention provides a cooperative defense control system for underwater manned and unmanned swarms, implemented using a cooperative defense control method for underwater manned and unmanned swarms, including:

[0131] The initialization module is used to build a global coordinate system, initialize the position and velocity states of manned platforms, jamming UUVs, decoy UUVs and dangerous targets, and set the jamming coefficient of jamming UUVs and the camouflage coefficient of decoy UUVs.

[0132] The interference-type UUV control module is used to construct an interference-type UUV target optimization function based on the location of the hazardous target, the location of each interference-type UUV and its interference coefficient, and obtain the control input that maximizes the interference of the current interference-type UUV on the detection range of the hazardous target based on the interference-type UUV target optimization function;

[0133] The decoy UUV control module is used to construct a probability model for identifying the decoy UUV based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient. Based on the probability model for identifying the decoy UUV, the module obtains the maximum probability of the dangerous target recognizing the decoy UUV and obtains the control input for the corresponding decoy UUV.

[0134] The manned platform control module is used to construct a probability model for identifying the manned platform based on the distance between the dangerous target and the manned platform. Based on the probability model, it obtains the minimum probability of the dangerous target identifying the manned platform and thus obtains the control input for the manned platform.

[0135] The action execution module is used to control each jamming UUV, decoy UUV, and manned platform to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

[0136] It should be noted that this system corresponds to the aforementioned intelligent collaborative defense and control method for underwater manned and unmanned swarms. All implementation methods in the above method embodiments are applicable to the embodiments of this system and can achieve the same technical effect.

[0137] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0138] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0139] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0140] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0141] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0142] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0143] Furthermore, it should be noted that in the system and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0144] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing system. The computing system can be a known general-purpose system. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0145] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A collaborative defense and control method for underwater manned and unmanned swarms, characterized in that, The underwater manned and unmanned cluster includes manned platforms and multiple UUV unmanned clusters. The types of UUV unmanned clusters include interference UUVs and decoy UUVs. Interference UUVs are used to reduce the detection range of dangerous targets. Decoy UUVs are used to disguise themselves as manned platforms to lure dangerous targets for attack. The method includes the following steps: S1, construct a global coordinate system, initialize the position and velocity states of the manned platform, the jamming UUV, the decoy UUV, and the dangerous target, and set the jamming coefficient of the jamming UUV and the camouflage coefficient of the decoy UUV; S2, based on the location of the dangerous target, the location of each interfering UUV and its interference coefficient, construct the interfering UUV target optimization function, and based on the interfering UUV target optimization function, obtain the control input that maximizes the interference of the current interfering UUV on the detection range of the dangerous target; S3. Based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient, construct a probability model for dangerous target to identify decoy UUV. Based on the probability model for dangerous target to identify decoy UUV, obtain the probability of maximizing the dangerous target to identify the decoy UUV, and obtain the control input of the corresponding decoy UUV. S4. Construct a probability model for identifying a manned platform from a dangerous target based on the distance between the dangerous target and the manned platform. Based on the probability model for identifying a manned platform from a dangerous target, obtain the probability of the dangerous target identifying the manned platform by minimizing the probability, and obtain the control input of the manned platform. S5 controls each of the jamming UUVs, decoy UUVs, and manned platforms to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

2. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 1, characterized in that: In step S1, the global coordinate system is established with the initial position of the manned platform as the origin, the eastward direction as the positive x-axis, the northward direction as the positive y-axis, and the vertical upward direction as the positive z-axis. The initial position vector values ​​and velocity vector values ​​of the manned platform, the jamming UUV, the decoy UUV, and the hazardous target in the three coordinate axes of the global coordinate system are obtained. The jamming coefficient of the jamming UUV is used to characterize the strength of its jamming capability against the hazardous target's range. The camouflage coefficient of the decoy UUV is used to characterize the ability of the corresponding decoy UUV to simulate the characteristics of a manned platform and attract dangerous targets.

3. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 2, characterized in that, Step S2 includes the following sub-steps: Obtain the distance between the interfering UUV and the dangerous target, and establish a negative exponential relationship between the square of the distance between the interfering UUV and the dangerous target and the first distance attenuation coefficient to construct the first distance attenuation term; Based on the product of the first distance attenuation term and the interference intensity coefficient corresponding to the interference type UUV, construct the target optimization function for the interference type UUV; Based on the target optimization function of the interference-type UUV, the interference value of the interference-type UUV to the dangerous target in the current state is calculated. With the goal of maximizing the detection range of the dangerous target, the optimal control input of the corresponding interference-type UUV is solved.

4. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 3, characterized in that, Step S2 also includes obtaining the actual detection range of the dangerous target after interference, including the following sub-steps: Iterate through all interfering UUVs, determine whether they are within the initial detection range of the dangerous target, and obtain the number of effective interfering UUVs within the initial detection range of the dangerous target; For each effective interference-type UUV, the corresponding interference effect factor is calculated based on its interference coefficient and distance from the hazardous target; The initial detection range of the dangerous target is preset. The interference effect factors corresponding to all effective interference UUVs are multiplied together, and the result is multiplied with the initial detection range of the dangerous target to obtain the true detection range of the dangerous target after interference.

5. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 1, characterized in that, Step S3 includes the following sub-steps: Obtain the distance between the decoy UUV and the dangerous target; The optimal recognition distance between the decoy UUV and the dangerous target is preset. The square of the difference between the current distance and the optimal recognition distance is calculated and multiplied by the second distance attenuation coefficient to construct the first negative exponential function as the exponential term. Add the first negative exponential function to the first correction coefficient, and calculate the reciprocal of the sum as the second distance attenuation term; Based on the product of the second distance attenuation term and the camouflage coefficient corresponding to the decoy UUV, a probabilistic model for identifying decoy UUVs as dangerous targets is constructed. Based on the probability model for identifying decoy UUVs in the presence of dangerous targets, the probability of a dangerous target recognizing a current decoy UUV is calculated. With the goal of maximizing this recognition probability, the optimal control input for the corresponding decoy UUV is solved.

6. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 1, characterized in that, Step S4 includes the following sub-steps: Obtain the distance between the manned platform and the dangerous target, and construct a second negative exponential function by multiplying the square of the distance between the interfering UUV and the dangerous target by the third distance attenuation coefficient as the exponential term; Add the second negative exponential function to the second correction coefficient, and construct a probability model for identifying manned platforms of dangerous targets based on the reciprocal of the sum. Based on the probability model for identifying manned platforms by dangerous targets, the probability of a dangerous target identifying a manned platform in the current state is calculated. With the goal of minimizing this identification probability, the optimal control input for the corresponding manned platform is solved.

7. The cooperative defense and control method for underwater manned / unmanned swarms as described in claim 1, characterized in that: Step S5 includes the following sub-steps: The control input of the current interfering UUV is calculated by multiplying the difference vector between the current position of the dangerous target and the current position of the corresponding interfering UUV by the gain coefficient of the corresponding interfering UUV. The updated position of the interfering UUV at the next moment is calculated by adding the current position of the interfering UUV at the current moment with the control input of the current interfering UUV. The distance deviation of the decoy UUV is calculated based on the difference vector between the current location of the dangerous target and the current location of the corresponding decoy UUV, and the difference between the vector and the optimal recognition distance. Based on the difference vector between the current position of the dangerous target and the current position of the corresponding decoy UUV, the unit vector pointing the decoy UUV towards the dangerous target is calculated. The control input of the current decoy UUV is calculated based on the distance deviation of the decoy UUV, the unit vector of the decoy UUV pointing towards the dangerous target, and the corresponding gain coefficient of the decoy UUV. The updated position of the decoy UUV at the next moment is calculated by adding the current position of the decoy UUV at the current moment with the control input of the current decoy UUV. Based on the difference vector between the current position of the dangerous target and the current position of the manned platform, and the target safety distance between the dangerous target and the manned platform, the safety distance deviation of the manned platform is calculated. Based on the difference vector between the current position of the manned platform and the current position of the dangerous target, the unit vector pointing from the dangerous target to the manned platform is calculated; The control input of the manned platform is calculated based on the safe distance deviation of the manned platform, the unit vector of the dangerous target pointing to the manned platform, and the gain coefficient of the manned platform. The updated position of the manned platform at the next moment is calculated by adding the current position of the manned platform to the control input of the manned platform.

8. A collaborative defense and control system for underwater manned and unmanned swarms, characterized in that, The method is implemented using the cooperative defense and control method for underwater manned / unmanned swarms as described in any one of claims 1-7, including: The initialization module is used to build a global coordinate system, initialize the position and velocity states of manned platforms, jamming UUVs, decoy UUVs and dangerous targets, and set the jamming coefficient of jamming UUVs and the camouflage coefficient of decoy UUVs. The interference-type UUV control module is used to construct an interference-type UUV target optimization function based on the location of the hazardous target, the location of each interference-type UUV and its interference coefficient, and obtain the control input that maximizes the interference of the current interference-type UUV on the detection range of the hazardous target based on the interference-type UUV target optimization function; The decoy UUV control module is used to construct a probability model for identifying the decoy UUV based on the distance between the dangerous target and the decoy UUV and the camouflage coefficient. Based on the probability model for identifying the decoy UUV, the module obtains the maximum probability of the dangerous target recognizing the decoy UUV and obtains the control input for the corresponding decoy UUV. The manned platform control module is used to construct a probability model for identifying the manned platform based on the distance between the dangerous target and the manned platform. Based on the probability model, it obtains the minimum probability of the dangerous target identifying the manned platform and thus obtains the control input for the manned platform. The action execution module is used to control each jamming UUV, decoy UUV, and manned platform to perform synchronous maneuvers, update their respective positions, and form a coordinated defense based on the control inputs corresponding to each.

9. An electronic device, characterized in that, It includes at least one processor, at least one memory, a communication interface, and a bus; wherein the processor, memory, and communication interface communicate with each other through the bus; the memory stores a program for a collaborative defense control method for an underwater manned / unmanned swarm that can be executed by the processor, and the program for the collaborative defense control method for an underwater manned / unmanned swarm is configured to implement the collaborative defense control method for an underwater manned / unmanned swarm as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program for a collaborative defense control method for an underwater manned / unmanned swarm. When the program is executed, it implements the collaborative defense control method for an underwater manned / unmanned swarm as described in any one of claims 1-7.

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