Control method and device for fixed-point decoy of unmanned aerial vehicle

Abstract

The invention relates to the field of unmanned aerial vehicle prevention and control, in particular to a control method and device for fixed-point decoy of an unmanned aerial vehicle. The method mainly comprises the following steps: acquiring the actual position of a target at each current moment, and performing incremental progressive calculation according to the actual position to obtain an expected angle deviation and an expected distance deviation at the next moment; and according to the expected angle deviation and the expected distance deviation, a false coordinate at the next moment is calculated, and the target is decoy to the false coordinate until the target reaches a decoy expected position. According to the method, a good fixed-point decoy effect can be achieved on the unmanned aerial vehicle using satellite navigation, and the safety of a special area is ensured.

Description

Technical Field

[0001] The present invention relates to the field of drone prevention and control, and in particular to a control method and device for drone fixed-point deception. Background Art

[0002] In recent years, the number of drones has been increasing, and unknown drone activities often occur in regulatory areas, which are prone to safety accidents. Drone-related safety precautions are becoming increasingly prominent. Therefore, it is necessary to control drones that illegally invade the airspace of regulatory areas.

[0003] From the current research reports on UAV deception, the focus is mainly on specific decoy equipment, and navigation decoy signal generation and decoy trajectory planning are proposed for various types of UAVs. However, there are few applied studies on real-time decoy control strategies for UAVs. The decoy trajectory control problem of UAVs is discussed from the perspective of control theory, especially for fixed-point deception. There are very few control methods proposed, which cannot achieve the target fixed-point deception well.

[0004] In view of this, how to overcome the defects of the existing technology and solve the problem of being unable to effectively carry out fixed-point deception of drones is a problem to be solved in this technical field. Summary of the invention

[0005] In view of the above defects or improvement needs of the prior art, the present invention solves the problem that it is impossible to effectively perform fixed-point deception on drones.

[0006] The embodiment of the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a control method for fixed-point deception of unmanned aerial vehicles, specifically: at each current moment, the actual position of the target is obtained, and incremental progressive calculation is performed based on the actual position to obtain the expected angle deviation and expected distance deviation at the next moment; wherein the current moment is the last moment of three consecutive moments; based on the expected angle deviation and the expected distance deviation, the false coordinates of the next moment are calculated, and the target is lured to the false coordinates until the target reaches the expected decoyed position.

[0008] Preferably, the incremental progressive calculation is performed according to the actual position to obtain the expected angle deviation and expected distance deviation at the next moment, specifically including: calculating the actual angle deviation between the actual position at three moments and the decoyed expected position, obtaining a first parameter group for angle control in the incremental progressive calculation, and calculating the expected angle deviation at the next moment according to the actual angle deviation and the first parameter group; obtaining a second parameter group for distance control in the incremental progressive calculation, calculating the actual distance deviation between the actual position at three moments and the decoyed expected position, and calculating the expected distance deviation at the next moment according to the actual distance deviation and the second parameter group.

[0009] Preferably, the calculation of the actual angular deviation between the actual position at three moments and the decoyed expected position specifically includes: for two adjacent moments, obtaining the position change vector between the actual position at the previous moment and the actual position at the next moment, and taking the direction of the position change vector as the actual heading at the next moment; obtaining the expected vector between the actual position at the next moment and the decoyed expected position, taking the direction of the expected vector as the expected heading at the next moment, and taking the angle between the actual heading and the expected heading as the actual angular deviation at the next moment.

[0010] Preferably, the first parameter group includes a first proportional coefficient, a first integral time constant and a first differential time constant, and the calculation of the expected angle deviation at the next moment according to the actual angle deviation and the first parameter group specifically includes:

[0011]

[0012] Among them, θ (k) is the expected angle deviation, T θ is the calculation period of the angle, is the first proportionality coefficient, is the first integration time constant, is the first differential time constant, and eA represents the actual angular deviation at the corresponding moment.

[0013] Preferably, the calculation of the actual distance deviation between the actual position at three moments and the decoyed expected position specifically includes: for two adjacent moments, calculating the position change vector between the actual position at the previous moment and the actual position at the next moment, obtaining the expected vector between the actual position at the next moment and the decoyed expected position, and taking the component of the position change vector in the direction of the expected vector as the actual distance deviation at the next moment.

[0014] Preferably, the second parameter group includes a second proportional coefficient, a second integral time constant and a second differential time constant, and the calculation of the expected distance deviation at the next moment according to the actual distance deviation and the second parameter group specifically includes: the expected distance deviation is calculated as follows:

[0015]

[0016] Among them, L (k) is the expected distance deviation, T L is the distance calculation period, is the second proportionality coefficient, is the second integration time constant, is the second differential time constant, and eS represents the actual distance deviation at the corresponding moment.

[0017] Preferably, the method of calculating the false coordinates at the next moment based on the expected angle deviation and the expected distance deviation specifically includes: taking the sum of the actual heading at the current moment and the expected angle deviation as the expected heading angle at the next moment, and taking the sum of the actual position at the current moment and the expected distance deviation as the expected distance at the next moment; and calculating the false coordinates at the next moment through polar coordinates based on the expected heading angle and the expected distance.

[0018] Preferably, the luring the target to the false coordinates specifically includes: generating a corresponding decoy signal according to the false coordinates, and causing the target to passively receive the decoy signal by means of high-intensity signal coverage, so that the target reaches the false coordinates according to the decoy signal.

[0019] In a second aspect, the present invention provides a control device for fixed-point spoofing of unmanned aerial vehicles, specifically: comprising at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions that can be executed by the at least one processor, and after the instructions are executed by the processor, they are used to complete the control method for fixed-point spoofing of unmanned aerial vehicles in the first aspect.

[0020] In a third aspect, the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors to complete the method provided in the first aspect.

[0021] In a fourth aspect, a chip is provided, comprising: a processor and an interface, for calling and running a computer program stored in the memory from a memory, and executing the method provided in the first aspect.

[0022] According to a fifth aspect, a computer program product comprising instructions is provided. When the instructions are executed on a computer or a processor, the computer or the processor executes the method provided in the first aspect.

[0023] Compared with the prior art, the beneficial effect of the present invention lies in: the method provided by the present invention starts from the desired decoy position and real-time position of the target UAV, proposes a dual-loop control strategy with distance and angle as loop control variables respectively, obtains the next false coordinate of real-time control until the target reaches the desired decoy position, and can have a better fixed-point decoy effect on UAVs using satellite navigation, ensuring the safety of special areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic diagram of a decoy computing model used in the method provided in an embodiment of the present invention;

[0026] Figure 2 A flow chart of a control method for fixed-point deception of unmanned aerial vehicles provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of a false coordinate calculation process used in the method provided in an embodiment of the present invention;

[0028] Figure 4 A flow chart of another control method for fixed-point deception of unmanned aerial vehicles provided by an embodiment of the present invention;

[0029] Figure 5 A schematic diagram of a control model used in the method provided in an embodiment of the present invention;

[0030] Figure 6 A schematic diagram of the structure of a control device for fixed-point deception of unmanned aerial vehicles provided by an embodiment of the present invention;

[0031] The reference numerals are as follows:

[0032] 11: processor; 12: memory. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0034] The present invention is an architecture of a specific functional system, so the specific embodiments mainly illustrate the functional logical relationship between the various structural modules, and do not limit the specific software and hardware implementation methods.

[0035] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0036] For drones that use the Global Positioning System (GPS) for navigation, since the structure of the GPS navigation signal is public, it is possible to "forge" the navigation signal to lure the drone away from areas that are not allowed to enter or to reach a designated landing location.

[0037] As one of the important means of countering unidentified drone activities in special areas, drone deception is divided into two types of deception: forwarding and generation. Both deception methods use unidentified drones as deception targets. Forwarding deception delays and amplifies the received real satellite signal, and uses the power advantage to make the target receiver capture false location information. Generative deception interference achieves signal regeneration through its own GPS signal generator, generating a deception signal with the same structure as the real signal, but the location information is false.

[0038] There are two main drone decoy strategies: directional expulsion and fixed-point decoy. Directional expulsion means luring the drone to a specified direction and controlling the drone to fly in the specified direction. Fixed-point decoy is more difficult and requires luring the drone to a specified location. Compared with directional expulsion, fixed-point decoy is more effective in actual scenarios because it can lure the target to a specified location, which can be a safe area where the drone will not have any impact. It is also a key and difficult problem of drone decoy that needs to be solved urgently in the current engineering field.

[0039] At present, there is a lot of theoretical research on drone deception, but it mainly focuses on specific decoy equipment. Through the hardware of the decoy equipment, navigation decoy signal generation and decoy trajectory planning are proposed for various types of drones. However, there are few engineering application studies on real-time decoy control strategies for drones, especially for fixed-point deception of drones. Few control methods have been proposed, and it is impossible to achieve fixed-point deception of the target well.

[0040] Embodiment 1:

[0041] The method provided in this embodiment is aimed at unmanned aerial vehicles using GPS satellite navigation technology, and proposes a real-time control strategy for the process of luring the target to the desired deception position when using a fixed-point deception method.

[0042] In order to facilitate calculation, this implementation is guided by the theory of complex control systems, starting from the target decoy position and real-time position information of the UAV, and based on the fixed-point decoy method and generative deception strategy, a UAV decoy calculation model with dual control variables of distance and angle is constructed.

[0043] In actual implementation, the use of GPS navigation information in satellite navigation cannot interfere with the altitude of the drone. In this embodiment, the altitude change of the target is not considered during the movement, and the height of the target in the decoy state is regarded as a fixed value. Only the movement state of the target on the fixed altitude plane needs to be considered. Therefore, the coordinate system for calculation in this embodiment is a Cartesian rectangular two-dimensional coordinate system, and the movement of the drone at adjacent moments is regarded as a linear motion on the plane.

[0044] At the current time k, the actual position of the target drone at the current time is (RX k, R.Y. k ), the actual position at the last moment is (RX k-1 , R.Y. k-1 ), the target decoy position is (X Goal , Y Goal ). The reference direction for angle calculation is A0, and the north direction is generally selected. The next false coordinates that need to be sent to the target at each moment are (DX k , DY k ).like Figure 1 As shown, the actual position of the drone at the current moment (RX k , R.Y. k ), the heading angle relative to the reference direction A0 is RA k , the desired heading angle at the current moment is DA k , the actual distance deviation from the decoy expected position is RS k .

[0045] In practical applications, the flight path of the drone to be lured is unknown. In the method provided in this embodiment, the actual distance and the actual heading angle between the actual position of the target drone and the desired decoy position are used as loop control variables, respectively, to construct a dual-loop control strategy, and the false coordinates of the decoy device at each moment are calculated based on the dual-loop control strategy, so that the target drone flies along the direction set by us and reaches the set desired decoy position.

[0046] like Figure 2 As shown, the specific steps of the control method for fixed-point deception of drones provided by the embodiment of the present invention are as follows:

[0047] Step 101: At each current moment, the actual position of the target is obtained, and incremental progressive calculation is performed based on the actual position to obtain the expected angle deviation and expected distance deviation at the next moment.

[0048] like Figure 3 In the spoofing process shown, the current moment is moment 1, and the false coordinates (DX2, DY2) at moment 2 need to be calculated. First, the expected angle deviation and expected distance deviation at moment 2 are calculated based on the actual positions at moments 0, 1, and 2.

[0049] Assume that at time 0, the actual position of the target is (RX0, RY0), the actual distance from the target to the desired position is S0, and the deception begins at time 0. After 1 moment, the target flies to the actual position at time 1 (RX1, RY1), and the actual distance from the desired position is S1. At this time, the actual position at time 1 (RX1, RY1) to the target decoy position (X Goal , Y Goal) is used as the expected heading angle, the expected angle deviation between the expected heading angle and the actual heading angle is eA1, and the expected distance deviation is eS1.

[0050] In the decoy track, the heading angle of the target at the expected position (DX1, DY1) at the first moment is θ1, and the heading angle of the target at the expected position (DX2, DY2) at the second moment is θ2. The expected angle deviation Δθ1 between the first moment and the second moment can be expressed as: Δθ1 = θ2-θ1. The position change vector of the false coordinates from the 0th moment to the 1st moment is L1, and the position change vector of the false coordinates from the 1st moment to the 2nd moment is L2. The expected distance deviation ΔL1 between the 1st moment and the 2nd moment can be expressed as: ΔL1 = L2-L1.

[0051] In actual implementation, the expected angle deviation Δθ1 can be calculated based on the difference eA1 between the actual target heading angle θ1 and the expected heading angle at the first moment; the expected distance deviation ΔL1 can be calculated based on the direction vector between the actual position of the target at the first moment and the decoy expected position.

[0052] Step 102: Calculate the false coordinates at the next moment according to the expected angle deviation and the expected distance deviation, and lure the target to the false coordinates until the target reaches the desired decoy position.

[0053] After obtaining the expected angle deviation, the sum of the actual heading θ1 at the current moment and the expected angle deviation Δθ1 can be used as the expected heading angle θ2 at the next moment; after obtaining the expected distance deviation ΔL1, the sum of the actual position L1 at the current moment and the expected distance deviation ΔL1 can be used as the expected distance L2 at the next moment.

[0054] By analogy, if we bring the second moment into the kth moment, we can calculate the θ at the k+1th moment based on the relevant parameters at the kth moment. k and L k :θ k+1 =θ k +Δθ k ; L k+1 =L k +ΔL k .

[0055] In getting θ k and L k After that, the false coordinates (DX) at the next moment can be calculated by polar coordinates according to the expected heading angle θ2 and the expected distance L2. k+1 , DY k+1 ).

[0056] Then according to the false coordinates (DX k+1 , DY k+1) generates a corresponding decoy signal, and uses high-intensity signal coverage to make the target passively receive the decoy signal, so that the target reaches the false coordinates according to the decoy signal.

[0057] After step 101 and step 102 provided in this embodiment, the target UAV can be lured, so that the target UAV reaches the designated desired lured position, thereby preventing the unauthorized flight of the UAV from causing a safety accident.

[0058] Furthermore, when decoying, if there is an obstacle between the actual position of the target UAV and the desired decoy position at time 0 or an important area needs to be passed through, multiple decoy intermediate positions can be set through various path planning methods to allow the target to bypass the obstacle or important area to reach the desired decoy position, thereby preventing the target UAV from colliding with the obstacle or passing through the important area.

[0059] In actual implementation, the system control quantity is adjusted by the state difference between the previous moment and the next moment to achieve closed-loop control, which is more conducive to maintaining system stability. In general scenarios, the control variable expression used for control is:

[0060]

[0061] Among them, u(k) is the control variable, K p is the proportional coefficient, e(k) is the state value at time k, e(k-1) is the state value at time k-1, T I is the integration time constant, T D is the differential time constant, and T is the calculation period. I , T D and T are adjustable control parameters

[0062] In this embodiment, two state variables, angle and distance, are used for control, so the angle and distance control variables need to be calculated respectively. In actual implementation, the angle control variable can be used as the expected angle deviation, and the distance control variable can be used as the expected distance deviation.

[0063] like Figure 4 As shown, the following method can be used to perform incremental progressive calculation according to the actual position to obtain the expected angle deviation and the expected distance deviation at the next moment.

[0064] Step 201: Calculate the actual angle deviations between the actual position at three moments and the decoyed expected position, obtain the first parameter group for angle control in the incremental progressive calculation, and calculate the expected angle deviation at the next moment based on the actual angle deviation and the first parameter group.

[0065] The expected angle deviation is calculated as follows:

[0066] uθ (k) = u θ (k-1)+du θ (k);

[0067]

[0068] Among them, u θ (k) is the expected angle at the current moment, u θ (k-1) is the expected angle at the previous moment, and the expected angle deviation Δθ k =du θ (k), T θ is the calculation period of the angle, is the first proportionality coefficient, is the first integration time constant, is the first differential time constant, and eA represents the actual angular deviation at the corresponding moment.

[0069] Step 202: Obtain a second parameter group for distance control in incremental progressive calculation, calculate the actual distance deviations between the actual position and the decoyed expected position at three moments, and calculate the expected distance deviation at the next moment based on the actual distance deviation and the second parameter group.

[0070] The expected distance deviation is calculated as follows:

[0071] u L (k) = u L (k-1)+du L (k);

[0072]

[0073] Among them, u L (k) is the expected distance at the current moment, u L (k-1) is the expected distance at the previous moment, and the expected distance deviation ΔL k =du L (k), T L is the distance calculation period, is the second proportionality coefficient, is the second integration time constant, is the second differential time constant, and eS represents the actual distance deviation at the corresponding moment.

[0074] After step 201 and step 202 provided in this embodiment, the desired angle deviation and the desired distance deviation required for control can be obtained.

[0075] In actual implementation, the expected heading angle, actual heading angle, expected distance, and actual distance of the UAV at the kth moment can be used as input to first calculate the heading angle θ of the UAV at the kth moment.k and the position change vector is L k , and obtain the corresponding control variable du θ (k) and du L (k), and iterate backward to calculate the deviation, and finally calculate the expected angle deviation Δθ according to the formula k The deviation from the expected distance is ΔL k , and finally get the false coordinates at time k+1.

[0076] (1) Expected angle deviation Δθ k .

[0077] For two adjacent moments, obtain the position change vector between the actual position at the previous moment and the actual position at the next moment, and use the direction of the position change vector as the actual heading at the next moment; obtain the expected vector between the actual position at the next moment and the decoyed expected position, use the direction of the expected vector as the expected heading at the next moment, and use the angle between the actual heading and the expected heading as the actual angle deviation at the next moment.

[0078] In a certain actual scenario, the target expected heading angle DA at the kth moment is k , the actual heading angle RA of the UAV at the kth moment k , proportionality coefficient Integration time constant Differential time constant Sampling period T θ .

[0079] The start time of deception is taken as the current time k when the first calculation is performed. At this time, the actual angle deviation at the kth time is: eA(k) = DA k -RA k ; The actual angle deviation at the k-1th moment is: eA(k-1)=0; the actual angle deviation at the k-2th moment is: eA(k-2)=0.

[0080] According to the first proportional coefficient, the actual angle deviation at the current moment and the actual angle deviation at the previous moment, the angle proportional deviation is calculated as:

[0081] According to the first proportional coefficient, the first integral time constant, the time interval between two adjacent moments and the actual angle deviation at the current moment, the angle integral deviation is calculated as:

[0082] According to the first proportional coefficient, the first differential time constant, the time interval between two adjacent moments, the angle deviation at the current moment, the actual angle deviation at the previous moment, and the actual angle deviation at the previous moment, the angle differential deviation is calculated as:

[0083] The sum of the angle proportional deviation, angle integral deviation and angle differential deviation is taken as the expected angle deviation: Δθ k =du θ (k) = AnglePropResult + AngleIntegResult + AngleDerivResult, thereby obtaining the expected angle deviation Δθ at the kth moment k .

[0084] When the expected angle deviation Δθ at the kth moment is completed k After calculation, the current kth moment can be used as the k-1th moment of the next moment, and eA(k-2)=eA(k-1), eA(k-1)=eA(k), and the above process can be used again to calculate the expected angle deviation Δθ of the next moment. k , until the target reaches the desired decoy position.

[0085] (2) Expected distance deviation ΔL k .

[0086] For two adjacent moments, calculate the position change vector between the actual position at the previous moment and the actual position at the next moment, obtain the expected vector between the actual position at the next moment and the decoyed expected position, and use the component of the position change vector in the direction of the expected vector as the actual distance deviation at the next moment.

[0087] In a specific scenario, the expected distance of the drone at the kth moment is 0, and the actual distance deviation of the drone at the kth moment is RS k , proportionality coefficient Integration time constant Differential time constant Sampling period T L .

[0088] The deception start time is taken as the current time k when the first calculation is performed. At this time, the actual distance deviation at the kth time is: eL(k) = DL k -RL k ; The actual distance deviation at the k-1th moment is: eL(k-1)=0; The actual distance deviation at the k-1th moment is: eL(k-2)=0.

[0089] According to the second proportional coefficient, the actual distance deviation at the current moment and the actual distance deviation at the previous moment, the distance proportional deviation is calculated as:

[0090] According to the second proportional coefficient, the second integral time constant, the time interval between two adjacent moments and the actual distance deviation at the current moment, the distance integral deviation is calculated as: LengthIntegResult =

[0091]

[0092] According to the second proportional coefficient, the second differential time constant, the time interval between two adjacent moments, the angle deviation at the current moment, the actual distance deviation at the previous moment, and the actual distance deviation at the previous moment, the distance differential deviation is calculated as:

[0093] The sum of the distance proportional deviation, distance integral deviation and distance differential deviation is taken as the expected distance deviation: ΔL k =du θ (k) = LengthPropResult + LengthIntegResult + LengthDerivResult, thereby obtaining the expected distance deviation ΔL at the kth moment k .

[0094] When the expected distance deviation ΔL at the kth moment is completed k After calculation, the current kth moment can be used as the k-1th moment of the next moment, and eA(k-2)=eA(k-1), eA(k-1)=eA(k) can be used again to calculate the expected distance deviation ΔL at the next moment. k , until the target reaches the desired decoy position.

[0095] The method provided in this embodiment can be used in actual implementation as follows Figure 5 The control model shown is implemented. The desired decoy position is input into the model, and the desired angle, actual angle, expected distance and actual distance are obtained according to the distance and angle calculation unit respectively, and the error value eA between the actual heading angle and the desired heading angle, and the deviation eS between the expected distance and the actual distance of the target at the current position are obtained. The decoy position calculation unit calculates the false coordinates of the next moment by adjusting the control amount angle and distance, and then outputs the calculated false coordinates of the decoy position calculation unit to the decoy device, which generates the corresponding decoy signal according to the false coordinates, and makes the target UAV passively receive the navigation decoy signal and respond through high-intensity signal coverage. Finally, the detection device feeds back the detected target real motion information to the system as the negative feedback variable of the closed-loop control model, thereby completing the target deception.

[0096] The control method for fixed-point deception of unmanned aerial vehicles provided in this embodiment constructs a model for the control process of fixed-point deception of unmanned aerial vehicles, utilizes the position difference between the deception destination position and the real-time position, and parameter information such as the real-time speed and direction of the target, takes the distance difference and angle difference from the desired deception position as control variables, determines the direction of the false coordinates by angle, and determines the position of the false coordinates by distance, that is, controls the flight direction of the target by flight angle, and determines the specific position of the target by combining the distance variable, constructs a dual-loop control strategy with two control variables of distance and angle, and forms a drone deception control method based on dual-loop control.

[0097] Embodiment 2:

[0098] Based on the control method for fixed-point deception of unmanned aerial vehicles provided in the above embodiment 1, the present invention also provides a control device for fixed-point deception of unmanned aerial vehicles that can be used to implement the above method, such as Figure 6 , which is a schematic diagram of the device architecture of an embodiment of the present invention. The control device for fixed-point deception of drones in this embodiment includes one or more processors 11 and a memory 12. Figure 6 A processor 11 is taken as an example.

[0099] The processor 11 and the memory 12 may be connected via a bus or other means. Figure 6 The example of connecting through bus is taken in the following.

[0100] The memory 12 is a non-volatile computer-readable storage medium for the control method for fixed-point deception of unmanned aerial vehicles, and can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as the control method for fixed-point deception of unmanned aerial vehicles in Example 1. The processor 11 executes various functional applications and data processing of the control device for fixed-point deception of unmanned aerial vehicles by running the non-volatile software programs, instructions and modules stored in the memory 12, that is, the control method for fixed-point deception of unmanned aerial vehicles in Example 1 is realized.

[0101] The memory 12 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 12 may optionally include a memory remotely arranged relative to the processor 11, and these remote memories may be connected to the processor 11 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0102] The program instructions / modules are stored in the memory 12, and when executed by one or more processors 11, the control method for fixed-point deception of drones in the above-mentioned embodiment 1 is executed, for example, the above-described Figure 2 and Figure 4 The steps shown.

[0103] An embodiment of the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors, such as Figure 6 A processor 11 in the embodiment may enable the one or more processors to execute the control method for fixed-point deception of a drone in embodiment 1, for example, to execute the above-described Figure 2 , Figure 4 The steps shown can also be implemented Figure 5 The various modules and units described.

[0104] It is worth noting that the information interaction, execution process, etc. between the modules and units within the above-mentioned devices and systems are based on the same concept as the processing method embodiment of the present invention. The specific contents can be found in the description of the method embodiment of the present invention and will not be repeated here.

[0105] A person skilled in the art may understand that all or part of the steps in the various methods of the embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0106] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A control method for fixed-point deception of unmanned aerial vehicles, characterized in that: include: At each current moment, the actual position of the target is obtained, and incremental progressive calculation is performed based on the actual position to obtain the expected angle deviation and expected distance deviation at the next moment; wherein the current moment is the last moment of three consecutive moments; According to the expected angle deviation and the expected distance deviation, the false coordinates at the next moment are calculated, and the target is lured to the false coordinates until the target reaches the expected decoy position.

2. The control method for fixed-point deception of unmanned aerial vehicles according to claim 1, characterized in that: The incremental progressive calculation is performed according to the actual position to obtain the expected angle deviation and the expected distance deviation at the next moment, specifically including: Calculate the actual angle deviations between the actual position and the decoyed expected position at three moments, obtain the first parameter group for angle control in the incremental progressive calculation, and calculate the expected angle deviation at the next moment according to the actual angle deviation and the first parameter group; The second parameter group used for distance control in the incremental progressive calculation is obtained, the actual distance deviations between the actual position and the decoyed expected position at three moments are calculated, and the expected distance deviation at the next moment is calculated according to the actual distance deviation and the second parameter group.

3. The control method for fixed-point deception of unmanned aerial vehicles according to claim 2, characterized in that: The calculation of the actual angle deviation between the actual position at three moments and the decoyed expected position specifically includes: For two adjacent moments, obtain the position change vector between the actual position at the previous moment and the actual position at the next moment, and use the direction of the position change vector as the actual heading at the next moment; The expected vector between the actual position at the next moment and the decoyed expected position is obtained, the direction of the expected vector is used as the expected heading at the next moment, and the angle between the actual heading and the expected heading is used as the actual angle deviation at the next moment.

4. The control method for fixed-point deception of unmanned aerial vehicles according to claim 3 is characterized in that: The first parameter group includes a first proportional coefficient, a first integral time constant and a first differential time constant, and the step of calculating the expected angle deviation at the next moment according to the actual angle deviation and the first parameter group specifically includes: Among them, θ (k) is the expected angle deviation, T θ is the calculation period of the angle, is the first proportionality coefficient, is the first integration time constant, is the first differential time constant, and eA represents the actual angular deviation at the corresponding moment.

5. The control method for fixed-point deception of unmanned aerial vehicles according to claim 2, characterized in that: The calculation of the actual distance deviation between the actual position at three moments and the decoyed expected position specifically includes: For two adjacent moments, calculate the position change vector between the actual position at the previous moment and the actual position at the next moment, obtain the expected vector between the actual position at the next moment and the decoyed expected position, and use the component of the position change vector in the direction of the expected vector as the actual distance deviation at the next moment.

6. The control method for fixed-point deception of unmanned aerial vehicles according to claim 5, characterized in that: The second parameter group includes a second proportional coefficient, a second integral time constant and a second differential time constant, and the calculation of the expected distance deviation at the next moment according to the actual distance deviation and the second parameter group specifically includes: The expected distance deviation is calculated as follows: Among them, L (k) is the expected distance deviation, T L is the distance calculation period, is the second proportionality coefficient, is the second integration time constant, is the second differential time constant, and eS represents the actual distance deviation at the corresponding moment.

7. The control method for fixed-point deception of unmanned aerial vehicles according to claim 1, characterized in that: The step of calculating the false coordinates at the next moment according to the expected angle deviation and the expected distance deviation specifically includes: The sum of the deviations between the actual heading at the current moment and the expected angle is taken as the expected heading angle at the next moment, and the sum of the deviations between the actual position at the current moment and the expected distance is taken as the expected distance at the next moment; According to the expected heading angle and expected distance, the false coordinates at the next moment are calculated by polar coordinates.

8. The control method for fixed-point deception of unmanned aerial vehicles according to claim 1, characterized in that: The method of deceiving the target to the false coordinates specifically includes: A corresponding decoy signal is generated based on the false coordinates, and the target is made to passively receive the decoy signal through high-intensity signal coverage, so that the target reaches the false coordinates according to the decoy signal.

9. A control device for fixed-point deception of unmanned aerial vehicles, characterized in that: It includes at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions that can be executed by the at least one processor, and after the instructions are executed by the processor, they are used to complete the control method for fixed-point deception of unmanned aerial vehicles described in any one of claims 1-8.

10. A non-volatile computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, which are executed by one or more processors to complete the control method for drone fixed-point spoofing as described in any one of claims 1-8.

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