CN113824528B - Unmanned aerial vehicle cluster cooperative spoofing interference method, device, equipment and medium - Google Patents
Unmanned aerial vehicle cluster cooperative spoofing interference method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a medium for unmanned aerial vehicle cluster cooperative spoofing interference, wherein the method comprises the following steps: modeling a firefly synchronous flickering process to obtain a first model; modeling an unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model; judging the current state of the unmanned aerial vehicle according to the second model, and determining a reconnaissance information value of the unmanned aerial vehicle; determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value; and controlling the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain. The application can improve the interference effect and can be widely applied to the technical field of unmanned aerial vehicle control.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle cluster cooperative spoofing interference method, device, equipment and medium.
Background
In the electronic countermeasure technology, the monopulse radar angle tracking system has better single-point interference source resistance. The angle tracking and clutter source tracking technology of the monopulse radar can be effectively resisted by utilizing a mode of multi-interference source interference. Compared with the traditional two-point source interference mode, the method of the multi-point source interference can increase the error of the angle measurement of the monopulse radar.
Because modern radars adopt a coherent processing technology, a certain gain can be obtained by an interference device based on a digital radio frequency memory (Digital Radio Frequency Memory, DRFM), and the interference device becomes a current common interference method. The distance deception false target interference is that a DRFM-based jammer is utilized to sample radar echo signals at high speed, and processes such as repeated delay, superposition and modulation are carried out, so that a large number of false targets are formed before and after a real target, and space-domain dense false target interference is formed for the radar.
Meanwhile, in order to shield the target burst prevention, a scene of unmanned aerial vehicle cluster synchronization spoofing interference is analyzed. When all the jammers reach synchronization, a plurality of false targets can be formed on the same distance ring of the anti-collision targets, and angle deception interference is caused to the radar.
However, the prior art still has a large improvement space on the angle deception jamming effect of the radar, and the existing jamming effect cannot safely shield the target from sudden prevention.
Disclosure of Invention
In view of the above, the embodiments of the present application provide a method, apparatus, device, and medium for unmanned aerial vehicle cluster cooperative spoofing interference, so as to improve interference effects.
One aspect of the present application provides a method for unmanned aerial vehicle cluster cooperative spoofing interference, including:
modeling a firefly synchronous flickering process to obtain a first model;
modeling an unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
judging the current state of the unmanned aerial vehicle according to the second model, and determining a reconnaissance information value of the unmanned aerial vehicle;
determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value;
and controlling the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain.
Optionally, modeling the firefly synchronous flashing process to obtain a first model includes:
simulating vibrator energy fluctuation existing in a firefly group through a trigonometric function;
establishing a differential equation model of firefly state quantity and time;
the expression of the differential equation model is as follows:
wherein,differentiation of the state (phase) representing point j; omega j Representing the initial luminescence frequency of fireflies; n represents the number of fireflies; s is(s) j Representing the collaboration of the jth firefly; a, a lj Representing whether two fireflies are in the field of view of each other, 1 or 0; θ i Representing the status of the ith firefly; θ j Representing the status of the jth firefly; Σ represents the sum of all the effects of point-to-point j over a range.
Optionally, in the differential equation model,
when the state of the ith firefly is greater than the state of the jth firefly, the state of the jth firefly will be added a positive number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is less than the state of the jth firefly, the state of the jth firefly will be added a negative number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is equal to the state of the jth firefly, the state of the jth firefly will remain unchanged.
Optionally, modeling the unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model, including:
determining that any unmanned aerial vehicle receives the information of the radiation source of the unmanned aerial vehicle in the interference state and the received information of the total radiation source;
when the unmanned aerial vehicle is converted from an undisturbed state to an interfered state, gain of radiation source information is given to the neighbor unmanned aerial vehicle of the unmanned aerial vehicle, so that the reconnaissance time is shortened.
Optionally, the determining, according to the second model, the current state of the unmanned aerial vehicle, and determining the reconnaissance information value of the unmanned aerial vehicle includes:
acquiring a current reconnaissance information value of the unmanned aerial vehicle;
and updating the scout information value of the unmanned aerial vehicle when the scout information value is smaller than a preset scout threshold value until the scout information value is larger than or equal to the preset scout threshold value.
Optionally, the determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value includes:
judging whether the unmanned aerial vehicle is in an interference state, if so, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle; if not, after the unmanned aerial vehicle is converted into an interference state, a fixed gain is added to each unmanned aerial vehicle around the unmanned aerial vehicle.
Optionally, the performing continuous reconnaissance according to the fixed gain control unmanned aerial vehicle includes:
acquiring a motion equation of the sudden prevention target;
determining the motion equation of the shielding target under the polar coordinates through coordinate transformation according to the motion equation of the burst protection target;
determining the distance delay and time delay of a shielding target so that the shielding target and a sudden prevention target are positioned on the same distance ring;
and carrying out weighted summation on the angles of the sudden prevention target and the shielding target which is positioned in the same distance ring with the sudden prevention target, and determining polar coordinate values deviating from the flight path.
Another aspect of the embodiment of the present application provides an unmanned aerial vehicle cluster cooperative spoofing interference device, including:
the first module is used for modeling a firefly synchronous flickering process to obtain a first model;
the second module is used for modeling the unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
the third module is used for judging the current state of the unmanned aerial vehicle according to the second model and determining a reconnaissance information value of the unmanned aerial vehicle;
a fourth module, configured to determine a fixed gain of the unmanned aerial vehicle in an interference state according to the reconnaissance information value;
and a fifth module, configured to control the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain.
Another aspect of an embodiment of the present application provides an electronic device, including a processor and a memory;
the memory is used for storing programs;
the processor executes the program to implement the method as described above.
Another aspect of the embodiments of the present application provides a computer-readable storage medium storing a program that is executed by a processor to implement a method as described above.
Embodiments of the present application also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, to cause the computer device to perform the foregoing method.
The embodiment of the application models a firefly synchronous flickering process to obtain a first model; modeling an unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model; judging the current state of the unmanned aerial vehicle according to the second model, and determining a reconnaissance information value of the unmanned aerial vehicle; determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value; and controlling the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain. The application improves the interference effect.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of the overall steps provided by an embodiment of the present application;
FIG. 2 is an energy wave diagram of a firefly population;
FIG. 3 is a graph of the number of glow fireflies versus time;
fig. 4 is a flow chart of drone cluster interference synchronization;
fig. 5 is a schematic diagram of a scenario of unmanned aerial vehicle cluster synchronization spoofing interference provided by an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
First, at night in summer, people tend to see groups of fireflies in the clumps together, which blink to illuminate at the same frequency. This is a wonderful phenomenon in nature, where initially there is no synchronized firefly, but agreement is achieved by autonomous regulation. Studies have shown that the process of glowing firefly populations constitutes a system with interactions by which parts of fireflies can act synchronously under specific conditions.
Therefore, aiming at the problems in the prior art, the application provides an unmanned aerial vehicle cluster cooperative spoofing interference method which is inspired by a firefly synchronous flickering mechanism. When the multiple unmanned aerial vehicles carrying the interference load achieve interference synchronization, multiple false targets can be generated on the same distance ring of the outburst prevention targets, angle deception interference effects are caused on the radar, and the outburst prevention of the targets is shielded.
Specifically, as shown in fig. 1, the application provides a method for unmanned aerial vehicle cluster cooperative spoofing interference, which comprises the following steps:
modeling a firefly synchronous flickering process to obtain a first model;
modeling an unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
judging the current state of the unmanned aerial vehicle according to the second model, and determining a reconnaissance information value of the unmanned aerial vehicle;
determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value;
and controlling the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain.
Optionally, modeling the firefly synchronous flashing process to obtain a first model includes:
simulating vibrator energy fluctuation existing in a firefly group through a trigonometric function;
establishing a differential equation model of firefly state quantity and time;
the expression of the differential equation model is as follows:
wherein,differentiation of the state (phase) representing point j; omega j Representing the initial luminescence frequency of fireflies; n represents the number of fireflies; s is(s) j Representing the collaboration of the jth firefly; a, a lj Representing whether two fireflies are in the field of view of each other, 1 or 0; θ i Representing the status of the ith firefly; θ j Representing the status of the jth firefly; Σ represents the sum of all the effects of point-to-point j over a range.
Optionally, in the differential equation model,
when the state of the ith firefly is greater than the state of the jth firefly, the state of the jth firefly will be added a positive number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is less than the state of the jth firefly, the state of the jth firefly will be added a negative number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is equal to the state of the jth firefly, the state of the jth firefly will remain unchanged.
Optionally, modeling the unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model, including:
determining that any unmanned aerial vehicle receives the information of the radiation source of the unmanned aerial vehicle in the interference state and the received information of the total radiation source;
when the unmanned aerial vehicle is converted from an undisturbed state to an interfered state, gain of radiation source information is given to the neighbor unmanned aerial vehicle of the unmanned aerial vehicle, so that the reconnaissance time is shortened.
Optionally, the determining, according to the second model, the current state of the unmanned aerial vehicle, and determining the reconnaissance information value of the unmanned aerial vehicle includes:
acquiring a current reconnaissance information value of the unmanned aerial vehicle;
and updating the scout information value of the unmanned aerial vehicle when the scout information value is smaller than a preset scout threshold value until the scout information value is larger than or equal to the preset scout threshold value.
Optionally, the determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value includes:
judging whether the unmanned aerial vehicle is in an interference state, if so, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle; if not, after the unmanned aerial vehicle is converted into an interference state, a fixed gain is added to each unmanned aerial vehicle around the unmanned aerial vehicle.
Optionally, the performing continuous reconnaissance according to the fixed gain control unmanned aerial vehicle includes:
acquiring a motion equation of the sudden prevention target;
determining the motion equation of the shielding target under the polar coordinates through coordinate transformation according to the motion equation of the burst protection target;
determining the distance delay and time delay of a shielding target so that the shielding target and a sudden prevention target are positioned on the same distance ring;
and carrying out weighted summation on the angles of the sudden prevention target and the shielding target which is positioned in the same distance ring with the sudden prevention target, and determining polar coordinate values deviating from the flight path.
Another aspect of the embodiment of the present application provides an unmanned aerial vehicle cluster cooperative spoofing interference device, including:
the first module is used for modeling a firefly synchronous flickering process to obtain a first model;
the second module is used for modeling the unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
the third module is used for judging the current state of the unmanned aerial vehicle according to the second model and determining a reconnaissance information value of the unmanned aerial vehicle;
a fourth module, configured to determine a fixed gain of the unmanned aerial vehicle in an interference state according to the reconnaissance information value;
and a fifth module, configured to control the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain.
Another aspect of an embodiment of the present application provides an electronic device, including a processor and a memory;
the memory is used for storing programs;
the processor executes the program to implement the method as described above.
Another aspect of the embodiments of the present application provides a computer-readable storage medium storing a program that is executed by a processor to implement a method as described above.
Embodiments of the present application also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, to cause the computer device to perform the foregoing method.
The specific implementation principle of the application is described in detail below with reference to the drawings of the specification:
1. firefly synchronous flickering model
Assume a graph with N points. Each point represents a firefly, and the energy fluctuation of vibrators existing in the group can be simulated by using a trigonometric function, and the initial luminous frequency w j To describe. To describe the mechanism of synchronous flicker of fireflies, a differential equation model of firefly state quantities θ and t can be established based on literature as follows:
initially, each point is trying to operate alone at its own frequency, while the coupling tends to synchronize it with the other points. Each point can be mutually influenced, and the state variable theta i Representing the status of the ith insect, θ j Representing the status of the j-th insect, the difference value of the status and the status can continuously adjust the status of the j-th insect.
The equation within the summation symbol represents the effect of point i on point j, and the whole Σ represents the sum of the effects of all points j over a range.
The interaction mechanism between the spots is further elucidated below. Assume that the phase difference between points i and j is between-pi and pi:
1) When theta i -θ j >0, i.e. point j is behind point i, sin (θ i -θ j )>0, since the variation of the next time point j is equal to the natural frequency plus a positive number, the next time point j will "accelerate catch up" point l.
2) When theta i -θ j <0, i.e. point j leads point i, sin (θ i -θ j )<0, since the variation of the next time point j is equal to the natural frequency plus a negative number, the next time point j will be the "slow down waiting" point l.
3) When theta i -θ j When =0, i.e. point j lags point i, sin (θ i -θ j ) =0, since the variation of the next time point j is zeroThen a stable phenomenon is maintained.
Based on the model, simulation analysis is performed on a firefly synchronization mechanism, as shown in fig. 2, and fig. 2 is an energy wave diagram of firefly population.
As can be seen from fig. 2 and 3, the energy fluctuation of fireflies is initially disturbed, because of the phase regulation with each other, but it can be found that the energy fluctuation of fireflies tends to be uniform after t=0.02 s, and the whole system exhibits a synchronism. In the model processing, the application regards the light source as a single energy fluctuation source, which is not affected by any other firefly, the properties of the fluctuation source satisfy:
E o ＝sin(ωt)
the number of the glowing fireflies is counted in the time domain, so that the model is further verified to achieve the synchronization effect of the system.
2. Unmanned aerial vehicle cluster synchronous deception jamming model
Model hypothesis and description: 1) Each unmanned aerial vehicle is assumed to have the capability of autonomous reconnaissance; 2) Assuming that each unmanned aerial vehicle has the same interference capability and interference pattern; 3) The position of the unmanned aerial vehicle in the area is assumed to be unchanged and distributed randomly; 4) Each unmanned aerial vehicle is assumed to have the same interference frequency under the condition of not being interfered by the outside; 5) Assuming that each unmanned plane has the same reconnaissance range, other unmanned planes within its communication range share reconnaissance radiation source information with it;
the modeling process of the unmanned plane cluster synchronous deception jamming model is as follows:
the interference duration of each unmanned aerial vehicle is a constant, and the radiation source information obtained by each unmanned aerial vehicle during interference is consistent. For the unmanned aerial vehicle group body which does not detect the radiation source, any unmanned aerial vehicle is taken, and the received radiation source information and the received total radiation source information of the unmanned aerial vehicle with the ith frame in an interference state are respectively as follows:
wherein d is i And (5) representing the distance between the ith unmanned aerial vehicle and other unmanned aerial vehicles.
In order to enable the cluster interference periods of the unmanned aerial vehicles to be consistent, when the jth unmanned aerial vehicle is converted into an interference state, a gain is given to the neighbor unmanned aerial vehicle receiving radiation source information of the unmanned aerial vehicle, and the gain is recorded as beta. Therefore, the reconnaissance time can be effectively shortened, and the passive synchronization of the unmanned aerial vehicle cluster interference is realized.
When the intensity of the scout radiation source information exceeds the scout threshold, it will be converted into an interference state, i.e.:
wherein t is 0 For the reconnaissance time of the unmanned aerial vehicle, E represents the reconnaissance threshold value of the unmanned aerial vehicle, S 0 And S is 1 Representing a scout state and an interference state, respectively.
As shown in FIG. 4, the flow chart of unmanned aerial vehicle cluster interference synchronization is that firstly, the current state of the unmanned aerial vehicle is judged, if the scout information value of the unmanned aerial vehicle is smaller than the scout threshold value, the scout task is continuously executed, namely, the scout information value is updated; if the scout information value is greater than the threshold value, judging whether the current unmanned aerial vehicle is in an interference state, adding a fixed gain beta to a neighborhood unmanned aerial vehicle of the unmanned aerial vehicle in the interference state, and finally updating the duration t of interference j And continuing the reconnaissance.
The foregoing describes the implementation of interference synchronization, and the following describes specific embodiments of interference. Because modern radars adopt a coherent processing technology, a certain gain can be obtained by an interference device based on a digital radio frequency memory (Digital Radio Frequency Memory, DRFM), and the interference device becomes a current common interference method. The distance deception false target interference is that a DRFM-based jammer is utilized to sample radar echo signals at high speed, and processes such as repeated delay, superposition and modulation are carried out, so that a large number of false targets are formed before and after a real target, and space-domain dense false target interference is formed for the radar.
Meanwhile, in order to shield the target burst prevention, a scene of unmanned aerial vehicle cluster synchronization spoofing interference is analyzed. As shown in fig. 5, when each jammer achieves synchronization, a plurality of decoys can be formed on the same distance ring of the outburst prevention target, which causes angle spoofing interference to the radar.
Assuming that the sudden-prevention target does uniform linear motion, under the condition of only considering two-dimensional conditions, setting all points to be positioned in a first quadrant and a fourth quadrant of a rectangular coordinate system with a radar as an origin, and obtaining a motion equation of the sudden-prevention target as follows:
in the method, in the process of the application,for the initial coordinate value of the movement of the sudden prevention object, +.>To highlight the projected value of the target speed in the xy direction, T is the radar scan period.
The motion equation of the shielding target under the polar coordinates can be obtained through coordinate transformation:
let the polar coordinate value of the ith unmanned aerial vehicle be (R i ,A i ) The polar coordinates of the decoy formed are (R f ,A f ) In order to enable the generated false target and the burst prevention target to be located on the same distance ring, the corresponding distance delay and time delay at the moment k can be obtained as follows:
ΔR if (k)＝R i (k)-R f (k)
Δτ if (k)＝Δ2R if (k)/c
wherein Deltaτ if For the time delay, when taking a negative value, the characteristic information of the radar signal needs to be detected in advance, and c is the light speed.
Traversing each unmanned aerial vehicle, calculating the time delay delta tau of each unmanned aerial vehicle, enabling the generated false target to be located on the distance ring where the anti-burst target is located, carrying out weighted summation on the anti-burst target and the angles of the anti-burst target located on the same distance ring from the false target point trace, and obtaining polar coordinate values deviating from the flight path:
wherein w is 1 The weight value of the burst prevention target angle is that n is the number of unmanned aerial vehicles, w 1+i The false target angle weighting weight is a parameter to be input.
The same applies to the measurement of off-track points:
wherein, delta' N A T (k) Is a random variable related to the signal noise N.
In summary, in order to cause angle deception jamming to the monopulse radar and shield target burst prevention, the application models and analyzes the process of synchronous flickering of fireflies, and inspires the process, and applies the process to an unmanned aerial vehicle cluster cooperative deception jamming scene, thereby realizing angle deception jamming to the monopulse radar, and compared with the prior art, the application has the following outstanding characteristics:
(a) Modeling the synchronous flickering process of fireflies
Modeling and analyzing a mechanism of synchronous flicker of fireflies, exploring conditions and influencing factors for achieving synchronization, and providing theoretical support for application of radar to countermeasure scenes;
(b) Unmanned aerial vehicle cluster cooperative spoofing interference method
The method comprises the steps of firstly carrying out theoretical analysis on a mechanism of forming distance deception jamming by a DRFM technology, then applying the mechanism to a deception jamming scene of an unmanned aerial vehicle cluster system based on a firefly synchronous flashing mechanism, and forming a plurality of false targets on the same distance ring of the sudden-prevention targets when the unmanned aerial vehicle cluster realizes jamming synchronization, so that angle deception jamming is caused to a monopulse radar, and the flight path of the sudden-prevention targets cannot be tracked normally.
In some alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present application are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed, and in which sub-operations described as part of a larger operation are performed independently.
Furthermore, while the application is described in the context of functional modules, it should be appreciated that, unless otherwise indicated, one or more of the described functions and/or features may be integrated in a single physical device and/or software module or one or more functions and/or features may be implemented in separate physical devices or software modules. It will also be appreciated that a 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 various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Accordingly, one of ordinary skill in the art can implement the application as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative and are not intended to be limiting upon the scope of the application, which is to be defined in the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, 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 description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the application, the scope of which is defined by the claims and their equivalents.
While the preferred embodiment of the present application has been described in detail, the present application is not limited to the embodiments described above, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present application, and these equivalent modifications or substitutions are included in the scope of the present application as defined in the appended claims.
Claims (7)
1. The unmanned aerial vehicle cluster cooperative spoofing jamming method is characterized by comprising the following steps of:
modeling a firefly synchronous flickering process to obtain a first model;
modeling an unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
judging the current state of the unmanned aerial vehicle according to the second model, and determining a reconnaissance information value of the unmanned aerial vehicle;
determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value;
controlling the unmanned aerial vehicle to perform continuous reconnaissance according to the fixed gain;
modeling the firefly synchronous flickering process to obtain a first model, wherein the modeling comprises the following steps:
simulating vibrator energy fluctuation existing in a firefly group through a trigonometric function;
establishing a differential equation model of firefly state quantity and time;
the expression of the differential equation model is as follows:
wherein,differentiation of the phase state representing point j; omega j Representing the initial luminescence frequency of fireflies; n represents the number of fireflies; s is(s) j Representing the collaboration of the jth firefly; a, a lj Representing whether two fireflies are in the field of view of each other, 1 or 0; θ i Representing the status of the ith firefly; θ j Representing the status of the jth firefly; Σ represents the sum of all the effects of point-to-point j over a range;
the determining the fixed gain of the unmanned aerial vehicle in the interference state according to the reconnaissance information value comprises the following steps:
judging whether the unmanned aerial vehicle is in an interference state, if so, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle; if not, after the unmanned aerial vehicle is converted into an interference state, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle;
the continuous reconnaissance performed by the unmanned aerial vehicle according to the fixed gain control comprises:
acquiring a motion equation of the sudden prevention target;
determining the motion equation of the shielding target under the polar coordinates through coordinate transformation according to the motion equation of the burst protection target;
determining the distance delay and time delay of a shielding target so that the shielding target and a sudden prevention target are positioned on the same distance ring;
and carrying out weighted summation on the angles of the sudden prevention target and the shielding target which is positioned in the same distance ring with the sudden prevention target, and determining polar coordinate values deviating from the flight path.
2. The method of claim 1, wherein in the differential equation model,
when the state of the ith firefly is greater than the state of the jth firefly, the state of the jth firefly will be added a positive number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is less than the state of the jth firefly, the state of the jth firefly will be added a negative number from the natural frequency such that the state of the jth firefly is equal to the state of the ith firefly;
when the state of the ith firefly is equal to the state of the jth firefly, the state of the jth firefly will remain unchanged.
3. The method for unmanned aerial vehicle cluster co-spoofing jamming according to claim 1, wherein modeling the unmanned aerial vehicle cluster co-spoofing jamming process according to the first model to obtain a second model comprises:
determining that any unmanned aerial vehicle receives the information of the radiation source of the unmanned aerial vehicle in the interference state and the received information of the total radiation source;
when the unmanned aerial vehicle is converted from an undisturbed state to an interfered state, gain of radiation source information is given to the neighbor unmanned aerial vehicle of the unmanned aerial vehicle, so that the reconnaissance time is shortened.
4. The method of claim 1, wherein the determining, according to the second model, the current state of the unmanned aerial vehicle, and determining the reconnaissance information value of the unmanned aerial vehicle, includes:
acquiring a current reconnaissance information value of the unmanned aerial vehicle;
and updating the scout information value of the unmanned aerial vehicle when the scout information value is smaller than a preset scout threshold value until the scout information value is larger than or equal to the preset scout threshold value.
5. An unmanned aerial vehicle cluster cooperative spoofing jamming device, comprising:
the first module is used for modeling a firefly synchronous flickering process to obtain a first model;
the second module is used for modeling the unmanned aerial vehicle cluster cooperative spoofing interference process according to the first model to obtain a second model;
the third module is used for judging the current state of the unmanned aerial vehicle according to the second model and determining a reconnaissance information value of the unmanned aerial vehicle;
a fourth module, configured to determine a fixed gain of the unmanned aerial vehicle in an interference state according to the reconnaissance information value;
a fifth module, configured to control, according to the fixed gain, the unmanned aerial vehicle to perform continuous reconnaissance;
the first module is specifically configured to:
simulating vibrator energy fluctuation existing in a firefly group through a trigonometric function;
establishing a differential equation model of firefly state quantity and time;
the expression of the differential equation model is as follows:
wherein,differentiation of the phase state representing point j; omega j Representing the initial luminescence frequency of fireflies; n represents the number of fireflies; s is(s) j Representing the collaboration of the jth firefly; a, a lj Representing whether two fireflies are in the field of view of each other, 1 or 0; θ i Representing the status of the ith firefly; θ j Representing the status of the jth firefly; Σ represents the sum of all the effects of point-to-point j over a range;
the fourth module is specifically configured to:
judging whether the unmanned aerial vehicle is in an interference state, if so, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle; if not, after the unmanned aerial vehicle is converted into an interference state, adding a fixed gain to each unmanned aerial vehicle around the unmanned aerial vehicle;
the fifth module is specifically configured to:
acquiring a motion equation of the sudden prevention target;
determining the motion equation of the shielding target under the polar coordinates through coordinate transformation according to the motion equation of the burst protection target;
determining the distance delay and time delay of a shielding target so that the shielding target and a sudden prevention target are positioned on the same distance ring;
and carrying out weighted summation on the angles of the sudden prevention target and the shielding target which is positioned in the same distance ring with the sudden prevention target, and determining polar coordinate values deviating from the flight path.
6. An electronic device comprising a processor and a memory;
the memory is used for storing programs;
the processor executing the program to implement the method of any one of claims 1-4.
7. A computer readable storage medium, characterized in that the storage medium stores a program, which is executed by a processor to implement the method of any one of claims 1-4.
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| CN108496135A (en) * | 2017-07-31 | 2018-09-04 | 深圳市大疆创新科技有限公司 | A kind of control method, equipment and the interference system of interference unmanned plane |
| CN109617645A (en) * | 2018-12-21 | 2019-04-12 | 杰创智能科技股份有限公司 | A kind of unmanned plane supervision management-control method and system based on towed cheating interference |
| CN112733251A (en) * | 2020-12-24 | 2021-04-30 | 中国人民解放军空军工程大学 | Multi-unmanned aerial vehicle collaborative track planning method |
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| US20170171729A1 (en) * | 2015-12-11 | 2017-06-15 | Eukuma Technologies Inc. | Systems and methods of announcing device communication availability |
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| CN108496135A (en) * | 2017-07-31 | 2018-09-04 | 深圳市大疆创新科技有限公司 | A kind of control method, equipment and the interference system of interference unmanned plane |
| CN109617645A (en) * | 2018-12-21 | 2019-04-12 | 杰创智能科技股份有限公司 | A kind of unmanned plane supervision management-control method and system based on towed cheating interference |
| CN112733251A (en) * | 2020-12-24 | 2021-04-30 | 中国人民解放军空军工程大学 | Multi-unmanned aerial vehicle collaborative track planning method |
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