An adaptive multi-unmanned aerial vehicle cooperative jamming method for radar networking

Abstract

The application discloses a kind of self-adapting multi-unmanned aerial vehicle cooperative jamming methods for radar networking, comprising: according to the number of unmanned aerial vehicles and the number of radars determines the number of deception points;According to the number of deception points, a unmanned aerial vehicle and a radar are separately matched, so that the distance sum of unmanned aerial vehicle and radar is minimum;The unmanned aerial vehicle closest to radar is regarded as host, and the radar closest to host is regarded as main radar, and the rest unmanned aerial vehicles are regarded as auxiliary machine, according to the coordinates of main radar, host coordinates, the azimuth angle of host and main radar, the heading angle of host and the deception jamming delay of host, the first deception point position parameter is calculated;According to the first deception point position parameter, the target point corresponding to auxiliary machine is determined, and the auxiliary machine is controlled to move to the corresponding target point, and the second deception point position parameter corresponding to auxiliary machine is calculated;First, second deception point position parameter is used for interfering radar networking.The application can be widely applied in radar deception jamming field to adaptively interfere with radars in unknown positions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar deception jamming, and in particular to a self-adaptive multi-unmanned aerial vehicle (UAV) cooperative jamming method for radar networking. BACKGROUND

[0002] The reconnaissance and detection means for UAVs are increasingly rich, among which, the radar detection technology is the most commonly used. The radar detection brings great threat to UAVs due to its flexible platform, rapid iteration of system, mature networking technology and other advantages, which makes a single UAV difficult to adapt to the changing environment. At present, based on the cooperation of multiple UAVs, the self-adaptive UAV anti-detection means in a variable environment, i.e., the self-adaptive anti-detection technology of multiple UAVs, has been widely valued. However, the existing UAV cooperative jamming method is still mainly the problem of flight path planning or the optimization problem under the limitation, and the existing technology is difficult to be applied to the complex and variable environment. SUMMARY

[0003] Therefore, the embodiment of the present application provides a self-adaptive multi-UAV cooperative jamming method for radar networking, so as to realize the flight path deception jamming of the radar networking with unknown position and scale, and achieve the purpose of self-adaptive anti-detection of multiple UAVs.

[0004] An aspect of the embodiment of the present application provides a self-adaptive multi-UAV cooperative jamming method for radar networking, comprising:

[0005] The number of deception points formed by the jammer carried on the UAV is determined according to the number of UAVs and the number of radars in the radar networking, wherein the number of radars and the number of UAVs are both plural, and each UAV carries a jammer;

[0006] One UAV is matched with one radar according to the number of deception points, so that the total distance between the UAVs and the radars is minimized, and the UAVs not matched with the radars are controlled to keep the original motion state;

[0007] The UAV closest to the radar is taken as a host, the radar closest to the host is taken as a main radar, the remaining UAVs are taken as auxiliary machines, the first deception point position parameter is calculated according to the main radar coordinates, the host coordinates, the azimuth angle between the host and the main radar, the heading angle of the host and the deception jamming and forwarding delay of the host;

[0008] The target point corresponding to the auxiliary machine is determined according to the first deception point position parameter, the auxiliary machine is controlled to move to the corresponding target point, and the second deception point position parameter is calculated according to the auxiliary radar coordinates closest to the auxiliary machine, the auxiliary machine coordinates, the azimuth angle between the auxiliary machine and the auxiliary radar, the heading angle of the auxiliary machine and the deception jamming and forwarding delay of the auxiliary machine;

[0009] Among them, the location parameters of the first and second deception points are used to interfere with the radar network.

[0010] Preferably, the process of calculating the deception point location parameters corresponding to each drone includes:

[0011] Determine the actual distance between the drone and the radar based on the drone's coordinates and the radar's coordinates;

[0012] The deception distance is determined based on the deception interference forwarding delay of the drone and the actual distance; the deception speed is determined based on the deception interference forwarding delay of the drone.

[0013] The distance vector between the deception point and the radar is determined based on the deception speed, the azimuth angle between the deception point and the radar, and the heading angle of the deception point.

[0014] The angle vector between the deception point and the radar's azimuth is determined based on the deception distance, deception speed, azimuth angle between the deception point and the radar, and heading angle of the deception point.

[0015] Among them, the azimuth angle between the deception point and the radar is the same as the azimuth angle between the UAV and the radar; the heading angle of the deception point is the same as the heading angle of the UAV.

[0016] Preferably, the step of determining the target point corresponding to the auxiliary machine based on the first deception point position parameter and controlling the auxiliary machine to move to the corresponding target point includes:

[0017] The auxiliary machine is controlled to move to the line segment formed by the radar that matches the first deception point and the auxiliary machine, and the foot of the perpendicular between the auxiliary machine and the line segment is taken as the target point.

[0018] If the perpendicular is outside the line segment, then the point on the line segment where the auxiliary machine forwarding delay is determined is taken as the target point.

[0019] Preferably, it further includes:

[0020] If the number of radars in the radar network changes, the number of deception points is recalculated, and the drone's trajectory is planned based on the recalculated number of deception points so that the drone moves to a new designated location to interfere with the radar network.

[0021] Preferably, if the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV's flight path is planned based on the recalculated number of deception points, including:

[0022] If the number of radars in a radar network increases while the number of deception points remains unchanged, the drone's flight path will remain the same.

[0023] Preferably, if the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV's flight path is planned based on the recalculated number of deception points, including:

[0024] If the number of radars in the radar network increases and the number of deception points that can be formed decreases, a first difference between the recalculated number of deception points and the number of deception points that can be formed is determined;

[0025] The latest n1 old deception points are retained, and the number of UAVs that have not been matched with radars is controlled to participate in the generation of new deception points according to the first difference, so that the sum of the old deception points and the new deception points is equal to the recalculated number of deception points, and n1 is the number of radars in the radar network.

[0026] Preferably, if the number of radars in the radar network changes, the number of deception points is recalculated, and the flight path of the UAV is planned according to the recalculated number of deception points, comprising:

[0027] If the number of radars in the radar network decreases, the deception points that are still in effect are retained;

[0028] The number of deception points is recalculated, and a second difference between the recalculated number of deception points and the number of deception points that are still in effect is determined;

[0029] The number of UAVs that have not been matched with radars is controlled to participate in the generation of new deception points according to the second difference, so that the sum of the deception points that are still in effect and the new deception points is equal to the recalculated number of deception points.

[0030] Another aspect of the embodiment of the application also provides an adaptive multi-UAV cooperative jamming device for a radar network, comprising:

[0031] A deception point number determination unit is configured to determine the number of deception points that can be formed by the jammer carried on the UAV according to the number of UAVs and the number of radars in the radar network; wherein the number of radars and the number of UAVs are both plural, and each UAV carries a jammer;

[0032] A UAV matching unit is configured to individually match one UAV with one radar according to the number of deception points, so that the sum of the distances between the UAV and the radars is minimized, and the UAV that has not been matched with the radars is controlled to keep the original motion state;

[0033] A first deception parameter calculation unit is configured to take the UAV closest to the radar as a master, take the radar closest to the master as a main radar, take the remaining UAVs as auxiliary machines, and calculate first deception point position parameters according to the main radar coordinates, the master coordinates, the azimuth angle between the master and the main radar, the heading angle of the master, and the deception jamming and forwarding delay of the master;

[0034] A second deception parameter calculation unit is configured to determine a target point corresponding to the auxiliary machine according to the first deception point position parameter, control the auxiliary machine to move to the corresponding target point, and calculate the second deception point position parameter according to the auxiliary radar coordinate closest to the auxiliary machine, the auxiliary machine coordinate, the azimuth angle between the auxiliary machine and the auxiliary radar, the heading angle of the auxiliary machine, and the deception jamming and retransmission delay of the auxiliary machine.

[0035] The first and second deception point position parameters are used for jamming radar networking.

[0036] Another aspect of the embodiment of the present application further provides an electronic device including a processor and a memory.

[0037] The memory is configured to store a program.

[0038] The processor executes the program to implement the method described above.

[0039] Another aspect of the embodiment of the present application further provides a computer readable storage medium, which stores a program. The program is executed by a processor to implement the method described above.

[0040] The embodiment of the present application further discloses a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device can read the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to execute the method described above.

[0041] The present application first determines the distribution of deception points, and then matches each unmanned aerial vehicle with a radar according to the number of deception points and the minimum sum of distances between the unmanned aerial vehicles and the radar, so that each unmanned aerial vehicle can jam one radar. The multi-unmanned aerial vehicle passive positioning solves the problem of the source of the radar position in cooperative jamming, thereby determining the main machine and the corresponding first deception point parameter, and the auxiliary machine and the corresponding second deception point parameter. The first and second deception point position parameters are used for jamming radar networking, and adaptive track deception jamming of radar networking with unknown position and scale is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0043] Figure 1 A flowchart of an adaptive multi-unmanned aerial vehicle cooperative jamming method for radar networking provided by the embodiment of the present application is shown.

[0044] Figure 2 A scene example diagram of multi-UAV cooperative jamming provided for an embodiment of the present application is shown in FIG. 1.

[0045] Figure 3 A scene example diagram of modeling the motion model of a single UAV provided for an embodiment of the present application is shown in FIG. 2.

[0046] Figure 4 A flowchart of adaptive jamming provided for an embodiment of the present application is shown in FIG. 3.

[0047] Figure 5 An example diagram of a simulation interface provided for an embodiment of the present application is shown in FIG. 4.

[0048] Figure 6 An example diagram of single-radar detection results provided for an embodiment of the present application is shown in FIG. 5.

[0049] Figure 7 A radar display diagram of a single radar affected by simple deception jamming provided for an embodiment of the present application is shown in FIG. 6. Figure 8

[0050] An example diagram of radar networking anti-deception jamming results provided for an embodiment of the present application is shown in FIG. 7. Figure 9

[0051] An example diagram of multi-UAV cooperative jamming results provided for an embodiment of the present application is shown in FIG. 8. Figure 10

[0052] An example diagram of adaptive UAV cooperative jamming results provided for an embodiment of the present application is shown in FIG. 9. Figure 11

[0053] A structural block diagram of an adaptive multi-UAV cooperative jamming device for radar networking provided for an embodiment of the present application is shown in FIG. 10. Figure 12 DETAILED DESCRIPTION In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0054] With reference to FIG. 10,

[0055] An adaptive multi-UAV cooperative jamming method for radar networking provided by an embodiment of the present application specifically includes the following steps: Figure 1

[0056] ​Step S100: determining the number of deception points formed by the jammer carried by the unmanned aerial vehicle according to the number of unmanned aerial vehicles and the number of radars in the radar network. The number of radars and the number of unmanned aerial vehicles are both pluralities, and each unmanned aerial vehicle carries a jammer.

[0057] Specifically, since a single unmanned aerial vehicle is difficult to interfere with multiple radars at the same time, it is assumed that the unmanned aerial vehicle only performs signal forwarding once at a certain time. Thus, the maximum number of deception points that can be formed is:

[0058]

[0059] wherein N is the number of unmanned aerial vehicles, n is the number of radars in the radar network, and are the upward and downward rounding respectively.

[0060] In order to generate effective deception points at the fusion center of the radar network, the unmanned aerial vehicle group can simultaneously deceive radars, and an example diagram of multi-unmanned aerial vehicle cooperative interference can be referred to Figure 2 .

[0061] In addition, since a single unmanned aerial vehicle cannot complete deception of multiple radars at the same time in a short time, in order to form as many deception points as possible, the flight path of the multi-unmanned aerial vehicle group needs to be planned, which can be approximated as an optimization problem, and the optimization model is:

[0062]

[0063]

[0064] wherein k is the number of deception points formed at a certain time, the objective function J is used to represent the energy consumption of the system. r , a r are the flight speed and acceleration of the unmanned aerial vehicle respectively, the greater the flight speed or acceleration, the greater the energy consumption required, c r is the number of jammers turned on in the unmanned aerial vehicle group, the unmanned aerial vehicles that do not contribute to cooperative interference should not perform deception jamming to save energy, r is the time consumed by the unmanned aerial vehicle in forming cooperative interference, the less the time, the shorter the path flown by the unmanned aerial vehicle, w v , w c , w t are the weight coefficients of the three respectively. The constraint conditions are the limit speed (v min , v max ) and the limit acceleration (a min , a max ) that the unmanned aerial vehicle can reach.

[0065] The greedy algorithm is used to solve the above model, and each part of the objective function is maximized as much as possible under the condition of increasing the restriction.

[0066] Step S110: According to the number of deception points, a single unmanned aerial vehicle is matched with a radar, so that the sum of the distances between the unmanned aerial vehicle and the radar is minimized, and the unmanned aerial vehicle not matched with the radar is controlled to keep the original motion state.

[0067] Specifically, each deception point needs unmanned aerial vehicles to complete together, and there are k groups. For each unmanned aerial vehicle, the radar closest to the unmanned aerial vehicle should be selected as much as possible, and the selection cannot be repeated, which is a typical task assignment problem. The Hungarian algorithm can be used to assign the unmanned aerial vehicle and the radar, so that the sum of the distances between the unmanned aerial vehicle and the radar is minimized. The unmanned aerial vehicle not assigned to the radar keeps the original motion state unchanged.

[0068] Step S120: The unmanned aerial vehicle closest to the radar is taken as the main machine, the radar closest to the main machine is taken as the main radar, the remaining unmanned aerial vehicles are taken as auxiliary machines, and the first deception point position parameter is calculated according to the main radar coordinate, the main machine coordinate, the azimuth angle between the main machine and the main radar, the heading angle of the main machine and the deception jamming and retransmission delay of the main machine.

[0069] Specifically, for each group of unmanned aerial vehicles, the unmanned aerial vehicle closest to the radar when the Hungarian algorithm is used is taken as the main machine, and the remaining unmanned aerial vehicles are taken as auxiliary machines. The motion speed of the main machine and the retransmission delay are kept unchanged. The process of calculating the deception point position parameter corresponding to each unmanned aerial vehicle includes:

[0070] S1, the real distance between the unmanned aerial vehicle and the radar is determined according to the unmanned aerial vehicle coordinate and the radar coordinate.

[0071] S2, the deception distance is determined according to the deception jamming and retransmission delay of the unmanned aerial vehicle and the real distance, and the deception speed is determined according to the deception jamming and retransmission delay of the unmanned aerial vehicle.

[0072] S3, the distance vector of the straight line distance between the deception point and the radar is determined according to the deception speed, the azimuth angle between the deception point and the radar and the heading angle of the deception point.

[0073] S4, the angle vector of the azimuth angle between the deception point and the radar is determined according to the deception distance, the deception speed, the azimuth angle between the deception point and the radar and the heading angle of the deception point.

[0074] The azimuth angle between the deception point and the radar is the same as the azimuth angle between the unmanned aerial vehicle and the radar; the heading angle of the deception point is the same as the heading angle of the unmanned aerial vehicle.

[0075] Specifically, considering the deception jamming problem in a two-dimensional plane, first, the motion model of a single unmanned aerial vehicle is modeled, and reference is made to Figure 3, set radar coordinates as (x0, y0), unmanned aerial vehicle coordinates as (x r ,y r ), the azimuth is recorded as θ, the heading angle is recorded as α, the deception jamming delay is t d , the generated deception point coordinates are (x f ,y f ), and the angle is the same as the unmanned aerial vehicle. Then the motion model of the deception point and the motion model of the deception point at the radar end are respectively:

[0076]

[0077] Derivation of the above formula can be obtained by simplifying:

[0078]

[0079] Substitute the motion model of the deception point and the motion model of the deception point at the radar end into the formula obtained by derivation, and the following formula can be obtained:

[0080]

[0081] The above formula is also applicable to the unmanned aerial vehicle. If the deception point track is given, that is, the parameters θ, α are known, and the deception jamming delay is known, r r , then:

[0082]

[0083] At this time, the motion speed of the unmanned aerial vehicle is:

[0084]

[0085] As described above, the process of deception jamming of the unmanned aerial vehicle can be completely described by the above formulas. That is, one of the unmanned aerial vehicle or the deception and the corresponding delay can be used to solve the other motion parameter.

[0086] Step S130: determining the target point corresponding to the auxiliary machine according to the first deception point position parameter, controlling the auxiliary machine to move to the corresponding target point, and calculating the second deception point position parameter according to the coordinates of the auxiliary radar closest to the auxiliary machine, the coordinates of the auxiliary machine, the azimuth of the auxiliary machine and the auxiliary radar, the heading angle of the auxiliary machine and the deception jamming delay of the auxiliary machine.

[0087] Specifically, the second deception point position parameter corresponding to the auxiliary machine can refer to the description in step S120.

[0088] The first and second deception point position parameters are used for jamming the radar network.

[0089] When the number of radars in the radar network changes, the conventional multi-UAV cooperative jamming may fail. Therefore, considering the change in the number of radars is an indispensable part of adaptive multi-UAV cooperative jamming.

[0090] Therefore, the present application can also include: if the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV flight path is planned according to the recalculated number of deception points, so that the UAV moves to a new designated location to jam the radar network.

[0091] Reference Figure 4 When the UAV group detects a change in the number of radars, the number of deception points needs to be recalculated, and then the flight path is re-planned according to the following cases.

[0092] Case one: the number of radars increases, and the number of deception points that can be formed remains unchanged. At this time, since the flight path has been formed previously, the increased radars do not affect the cooperative jamming, and the UAV group does not need to perform additional operations.

[0093] Specifically, if the number of radars in the radar network increases and the number of deception points that can be formed remains unchanged, the flight path of the UAV remains unchanged.

[0094] Case two: the number of radars increases, and the number of deception points that can be formed decreases. Assuming that the number of deception points that can be formed after the change is n1, the UAV side selects to retain the first n1 old deception points, and the redundant UAVs are used as auxiliary machines to participate in the generation of deception points. The specific calculation steps are referred to the previous multi-UAV cooperative jamming process.

[0095] Specifically, if the number of radars in the radar network increases and the number of deception points that can be formed decreases, the first difference between the recalculated number of deception points and the number of deception points that can be formed is determined.

[0096] The first n1 old deception points generated are retained, and the corresponding number of UAVs that have not been matched with radars are controlled to participate in the generation of new deception points according to the first difference, so that the sum of the old deception points and the new deception points is equal to the recalculated number of deception points, and n1 is the number of radars in the radar network after the number of radars increases. The number of deception points that can be formed.

[0097] Case three: the number of radars decreases. When a radar in the radar network suddenly stops working, it is likely to cause the previously planned deception points to fail, and the UAV side needs to determine whether the old deception points can continue to be generated, retain the deception points that are still effective, and use the remaining UAVs and redundant auxiliary machines to form new deception points.

[0098] Specifically, if the number of radars in the radar network decreases, the deception points that are still effective are retained.

[0099] The number of spoofing points is recalculated, and a second difference between the recalculated number of spoofing points and the number of still valid spoofing points is determined.

[0100] The corresponding number of UAVs not matched with the radar is controlled according to the second difference to participate in the generation of new spoofing points, so that the sum of the still valid spoofing points and the new spoofing points is equal to the recalculated number of spoofing points.

[0101] In order to describe the application in more detail, the practical application process of the application will be described in specific examples.

[0102] A signal level multi-UAV adaptive counter-reconnaissance interface for radar networking is designed using the matlab app designer platform, which is used for simulation verification and result display, and the interface diagram is as shown in Figure 5 .

[0103] The above interface can be divided into three parts: the left side is the UAV end, which is used to set various parameters of the UAV group, display the detection results and information of the UAV; the right side is the radar end, which is used to set various parameters of the radar, display the echo beam and detection information of the radar; the middle is the radar networking and the detection results of each radar. After running the program, the following results are displayed in turn:

[0104] Spoofing interference: when the UAV carries a jammer, the radar detects it, and a spoofing point appears, as shown in Figure 6 . Referring to Figure 7 and Figure 8 , the embodiment of the application provides a radar display diagram affected by simple spoofing interference of a single radar.

[0105] Radar networking: the number of radars increases, and the radar networking starts to run, and each radar can still detect many false targets, but only the true targets are retained in the fusion center, as shown in Figure 9 .

[0106] Cooperative jamming: the UAV group starts cooperative jamming and plans spoofing points, which can cause spoofing points in the fusion center of the radar networking, as shown in Figure 10 .

[0107] Adaptive cooperative jamming: when the number of radars changes, the UAV group needs to re-plan spoofing to maintain the spoofing of the radar networking, as shown in Figure 11 .

[0108] Compared with the traditional cooperative jamming technology, the embodiment of the application has the following three advantages according to the multi-UAV flight mode and the working characteristics of the radar networking:

[0109] (a) The multi-UAV passive positioning solves the problem of the source of the radar position in cooperative jamming.

[0110] (b) Realize the low energy consumption of multi-unmanned aerial vehicle cooperative deception jamming.

[0111] (c) Realize the multi-unmanned aerial vehicle cooperative deception jamming of radar number time-varying in radar networking.

[0112] Referring Figure 12 , the embodiment of the application provides a kind of adaptive multi-unmanned aerial vehicle cooperative jamming device for radar networking, comprising:

[0113] Deception point number determination unit, for determining the number of deception points that can be formed by jammer carried on unmanned aerial vehicle according to the number of unmanned aerial vehicle and the number of radar in radar networking;Wherein, the number of radar and unmanned aerial vehicle are plural, and each unmanned aerial vehicle carries a jammer;

[0114] Unmanned aerial vehicle matching unit, for according to the number of deception points, a unmanned aerial vehicle is matched with a radar alone, so that the distance sum of unmanned aerial vehicle and radar is minimum, and unmanned aerial vehicle not matched with radar keeps original motion state;

[0115] First deception parameter calculation unit, for taking the unmanned aerial vehicle closest to radar as host, and taking the radar closest to host as main radar, and taking the rest unmanned aerial vehicle as auxiliary machine, according to main radar coordinates, host coordinates, the azimuth angle of host and main radar, the heading angle of host and the deception jamming delay of host, calculate first deception point position parameter;

[0116] Second deception parameter calculation unit, for determining the target point corresponding to auxiliary machine according to first deception point position parameter, control auxiliary machine to move to corresponding target point, and according to the coordinates of auxiliary radar closest to auxiliary machine, auxiliary machine coordinates, the azimuth angle of auxiliary machine and auxiliary radar, the heading angle of auxiliary machine and the deception jamming delay of auxiliary machine, calculate second deception point position parameter;

[0117] Wherein, first and second deception point position parameters are used for jamming radar networking.

[0118] The embodiment of the application further discloses a computer program product or computer program, the computer program product or computer program includes computer instructions, the computer instructions are stored in computer readable storage medium. The processor of computer equipment can read the computer instructions from computer readable storage medium, and the processor executes the computer instructions, so that the computer equipment executes Figure 1 The method shown.

[0119] In some alternative embodiments, the function / operations mentioned in the block diagrams can not occur in the order mentioned in the operational illustrations. For example, depending on the involved function / operation, two blocks shown in succession can in fact be executed substantially concurrently or the blocks can sometimes be executed in reverse order, depending upon the functionality / operations involved. Furthermore, embodiments presented and described in the flowcharts are only examples of implementing the present application. Alternative embodiments can be implemented where various operations are changed, omitted, and / or added. For example, the order of the operations can be changed, and sub-operations described as part of a larger operation can be implemented independently.

[0120] Furthermore, although the present application is described in the context of functional modules, it is to be understood that one or more of the functions and / or features described can be integrated in a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It will also be appreciated that detailed discussion of the actual implementation of each module is not necessary to an understanding of the present application. Rather, the actual implementation of the modules, in light of the attributes, functions, and internal relationships of the various functional modules disclosed herein, will be apparent to one of ordinary skill in the art, given the benefit of this disclosure. Accordingly, the present application is not limited to the specific embodiments illustrated herein, but is applicable for use in all domains of engineering consistent with the technical concepts disclosed herein. It will also be appreciated that the particular conceptualization disclosed is merely exemplary and is not intended to limit the scope of the application, which is defined by the appended claims and their equivalents.

[0121] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the part of the technical solutions that make essential contributions to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0122] The logic and / or steps represented in the flowcharts and / or described herein, for example, can be embodied in non-transitory computer-readable media, executed by one or more computing devices, and / or in any other way. The logic and / or steps represented in the flowcharts and / or described herein, for example, can be considered a list of executable instructions for implementing logic functions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor- containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber (optical), and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by the instruction execution system, apparatus, or device.

[0123] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber (optical), and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by the instruction execution system, apparatus, or device.

[0124] It should be understood that aspects of the application can be implemented in hardware, software, firmware, or combinations thereof. In the embodiments described above, various steps or functions can be implemented in software or firmware that are stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following can be used: a combination of discrete logic circuits having logic gates for implementing logic functions upon an application of data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and so on, or a combination of any of them.

[0125] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials, or characteristics described can be combined in any appropriate way in any one or more embodiments or examples.

[0126] While the embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary and are not to be construed as limiting the scope of the application. The scope of the application is defined by the appended claims and their equivalents.

[0127] The above is a specific description of the preferred embodiment of the present application, but the present application is not limited to the described embodiment, and those skilled in the art can make various equivalent modifications or replacements without departing from the spirit of the present application, and these equivalent modifications or replacements are all included in the scope defined by the claims of the present application.

Claims

1. An adaptive multi-UAV cooperative jamming method for radar networking, characterized in that, include: The number of deception points that can be created by the jammer carried on the drones is determined based on the number of drones and the number of radars in the radar network; where both the number of radars and drones are multiple, and each drone carries one jammer. Based on the number of deception points, each drone is individually matched with a radar to minimize the total distance between the drone and the radar, while controlling drones not matched with radar to maintain their original motion state. The drone closest to the radar is taken as the host, the radar closest to the host is taken as the main radar, and the other drones are taken as auxiliary drones. The position parameters of the first deception point are calculated based on the coordinates of the main radar, the coordinates of the host, the azimuth angle between the host and the main radar, the heading angle of the host, and the deception jamming forwarding delay of the host. The target point corresponding to the auxiliary aircraft is determined based on the location parameters of the first deception point. The auxiliary aircraft is controlled to move to the corresponding target point. The location parameters of the second deception point are calculated based on the coordinates of the auxiliary radar closest to the auxiliary aircraft, the coordinates of the auxiliary aircraft, the azimuth angle between the auxiliary aircraft and the auxiliary radar, the heading angle of the auxiliary aircraft, and the deception jamming forwarding delay of the auxiliary aircraft. Among them, the location parameters of the first and second deception points are used to interfere with the radar network.

2. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 1, characterized in that, The process of calculating the deception point location parameters for each drone includes: Determine the actual distance between the drone and the radar based on the drone's coordinates and the radar's coordinates; The deception distance is determined based on the deception interference forwarding delay of the drone and the actual distance; the deception speed is determined based on the deception interference forwarding delay of the drone. The distance vector between the deception point and the radar is determined based on the deception speed, the azimuth angle between the deception point and the radar, and the heading angle of the deception point. The angle vector between the deception point and the radar's azimuth is determined based on the deception distance, deception speed, azimuth angle between the deception point and the radar, and heading angle of the deception point. Among them, the azimuth angle between the deception point and the radar is the same as the azimuth angle between the UAV and the radar; the heading angle of the deception point is the same as the heading angle of the UAV.

3. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 1, characterized in that, The step of determining the target point corresponding to the auxiliary machine based on the first deception point position parameter and controlling the auxiliary machine to move to the corresponding target point includes: The auxiliary machine is controlled to move to the line segment formed by the radar that matches the first deception point and the auxiliary machine, and the foot of the perpendicular between the auxiliary machine and the line segment is taken as the target point. If the perpendicular is outside the line segment, then the point on the line segment where the auxiliary machine forwarding delay is determined is taken as the target point.

4. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 1, characterized in that, Also includes: If the number of radars in the radar network changes, the number of deception points is recalculated, and the drone's trajectory is planned based on the recalculated number of deception points so that the drone moves to a new designated location to interfere with the radar network.

5. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 4, characterized in that, If the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV's flight path is planned based on the recalculated number of deception points, including: If the number of radars in a radar network increases while the number of deception points remains unchanged, the drone's flight path will remain the same.

6. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 4, characterized in that, If the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV's flight path is planned based on the recalculated number of deception points, including: If the number of radars in a radar network increases and the number of deception points that can be formed decreases, then the first difference between the recalculated number of deception points and the number of deception points that can be formed is determined. The n1 old deception points generated before the latest generation are retained. Based on the first difference, the corresponding number of UAVs that are not matched with the radar are controlled to participate in the generation of new deception points, so that the sum of the old deception points and the new deception points is equal to the number of recalculated deception points. The number of deception points that can be formed after the number of radars in the n1 radar network increases.

7. The adaptive multi-UAV cooperative jamming method for radar networking according to claim 4, characterized in that, If the number of radars in the radar network changes, the number of deception points is recalculated, and the UAV's flight path is planned based on the recalculated number of deception points, including: If the number of radars in a radar network decreases, the deception points that are still effective will be retained. Recalculate the number of deception points and determine a second difference between the recalculated number of deception points and the number of deception points that are still in effect; The second difference controls the corresponding number of drones that are not matched with the radar to participate in the generation of new deception points, so that the sum of the still effective deception points and the new deception points is equal to the number of recalculated deception points.

8. An adaptive multi-UAV cooperative jamming device for radar networking, characterized in that, include: The deception point number determination unit is used to determine the number of deception points that can be formed by the jammer carried on the drone based on the number of drones and the number of radars in the radar network; wherein, the number of radars and drones are both multiple, and each drone carries one jammer. The drone matching unit is used to match a drone with a radar individually based on the number of deception points, so as to minimize the total distance between the drone and the radar, and control the drones that are not matched with the radar to maintain their original motion state. The first deception parameter calculation unit is used to take the UAV closest to the radar as the host, the radar closest to the host as the main radar, and the other UAVs as auxiliary UAVs. Based on the coordinates of the main radar, the coordinates of the host, the azimuth angle between the host and the main radar, the heading angle of the host, and the deception interference forwarding delay of the host, the first deception point position parameters are calculated. The second deception parameter calculation unit is used to determine the target point corresponding to the auxiliary aircraft based on the first deception point position parameters, control the auxiliary aircraft to move to the corresponding target point, and calculate the second deception point position parameters based on the coordinates of the auxiliary radar closest to the auxiliary aircraft, the coordinates of the auxiliary aircraft, the azimuth angle between the auxiliary aircraft and the auxiliary radar, the heading angle of the auxiliary aircraft, and the deception interference forwarding delay of the auxiliary aircraft. Among them, the location parameters of the first and second deception points are used to interfere with the radar network.

9. An electronic device, characterized in that, Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program that is executed by a processor to implement the method as described in any one of claims 1 to 7.

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