A method and system for drone navigation deception

Abstract

The application provides a UAV navigation deception method and system, which comprises the following steps: calibrating the phase of an antenna array and generating an initial point cloud; scanning the surrounding environment in real time to generate a high-precision terrain grid, loading an electromagnetic parameter library, and combining the initial point cloud to establish a three-dimensional electromagnetic map; continuously scanning and detecting a target UAV to output point cloud data, and identifying the model characteristics of the target UAV through micro-Doppler characteristics; synthesizing a deception navigation signal according to a real-time ephemeris file or a stored ephemeris file and a specified coordinate, and calculating a plurality of reflection paths according to the three-dimensional electromagnetic map; predicting the motion trajectory of the target UAV in real time based on the plurality of reflection paths, and emitting the deception navigation signal to the motion trajectory through laser point cloud combined with a preset point cloud template library to guide the target UAV to land or drive away. The application can guide or drive away the UAV in a complex environment, and can improve the universality in application.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) control technology, and in particular to a method and system for deceiving UAV navigation. Background Technology

[0002] Navigation deception and jamming technology has emerged and rapidly developed as an innovative "information domain" countermeasure. The core mechanism of this technology does not rely on high-power energy suppression, but rather on precisely generating a fake navigation signal that is highly consistent with real satellite navigation systems (including GPS, BeiDou, GLONASS, etc.) in terms of signal structure, data format, and modulation method. After precise time-frequency synchronization, this fake signal is injected into the target UAV's navigation receiver. This carefully designed deception signal can induce the UAV's navigation system to produce incorrect satellite signal acquisition, tracking, and processing, ultimately outputting false positioning information that deviates from its actual position. Given that modern UAV flight control systems generally adopt a closed-loop architecture of "positioning-navigation-control," their key flight functions such as trajectory planning, attitude adjustment, and speed control strictly rely on continuous and accurate positioning data input. This "information injection" attack can achieve precise control over the UAV's flight behavior: it can induce it to gradually deviate from the predetermined route, forming accumulated errors, or force it to execute specific pre-set action commands (such as turning to fly to a designated area, performing a forced landing, or entering a hovering state).

[0003] In existing technologies, most drone deception and interference models are designed for specific drone models or preset simple flight trajectories (such as uniform straight flight). When facing non-cooperative targets, drones using unknown navigation algorithms, or drones performing complex adaptive trajectories (such as variable altitude hovering, serpentine maneuvers, etc.), existing methods are clearly insufficient in terms of robustness and universality in behavioral feature recognition and motion trajectory modeling, making it difficult to meet the needs of practical applications. Currently, most deception planning algorithms are still limited to applications in static environments or simple dynamic scenarios. When facing complex urban environments (including building obstructions), dynamic obstacles, real-time obstacle avoidance, and multi-target collaborative deception, existing algorithms have significant shortcomings in terms of real-time decision-making, flight safety, and intelligence level, and there is an urgent need to introduce more advanced intelligent decision-making methods to improve them. Summary of the Invention

[0004] Therefore, the purpose of this invention is to provide a method and system for deceiving drone navigation, in order to overcome the shortcomings of the prior art.

[0005] In a first aspect, the present invention provides a method for deceiving unmanned aerial vehicle (UAV) navigation, the method comprising:

[0006] The antenna array phase is calibrated, an initial point cloud is generated, and a preset point cloud template library is loaded.

[0007] The surrounding environment is scanned in real time to generate a high-precision terrain mesh. An electromagnetic parameter library is loaded into the high-precision terrain mesh, and a three-dimensional electromagnetic map is built by combining it with the initial point cloud. This step specifically includes:

[0008] The surrounding environment is scanned in real time by lidar to generate a high-precision terrain grid, and an electromagnetic parameter library is loaded into the high-precision terrain grid.

[0009] Based on the initial point cloud and the high-precision terrain mesh after loading the electromagnetic parameter library, a reflection model is established after AI calculation, wherein the reflection model is the three-dimensional electromagnetic map;

[0010] The system continuously scans and detects target drones to output point cloud data, and identifies the model characteristics of the target drones through micro-Doppler features.

[0011] Using real-time ephemeris files or stored ephemeris files and synthesizing decoy navigation signals according to specified coordinates, and calculating several reflection paths based on the three-dimensional electromagnetic map;

[0012] The trajectory of the target UAV is predicted in real time based on several reflection paths, and the decoy navigation signal is emitted to the trajectory through laser point cloud combined with the preset point cloud template library to guide the target UAV to land or drive it away.

[0013] Compared with the prior art, the beneficial effects of the present invention are: by loading an electromagnetic parameter library into a high-precision terrain grid and combining it with an initial point cloud to generate a three-dimensional electromagnetic map, by synthesizing a decoy path using ephemeris files or stored ephemeris files and specified coordinates, and by transmitting decoy navigation signals to the target UAV's trajectory using laser point clouds combined with a point cloud template library including environmental conditions, it is possible to guide or drive away UAVs in complex environments, and by predicting the target UAV's trajectory, the versatility of the application is improved.

[0014] Furthermore, the steps of calibrating the antenna array phase, generating an initial point cloud, and loading a preset point cloud template library include:

[0015] The phase of the millimeter-wave radar antenna array is calibrated, the phase scanning information of the millimeter-wave radar antenna array is obtained, and an initial point cloud is generated based on the scanning information;

[0016] Load the preset point cloud template library according to the laser array.

[0017] Furthermore, after the step of establishing a three-dimensional electromagnetic map in conjunction with the initial point cloud, the method further includes:

[0018] The image transmission signal of the target drone is intercepted and analyzed to calculate the target drone's coordinates, altitude, direction of movement, speed, and model characteristics.

[0019] The next position and attitude of the target UAV are estimated using Kalman filtering.

[0020] Furthermore, after the step of transmitting the deceptive navigation signal to the motion trajectory using laser point clouds combined with the preset point cloud template library, the method further includes:

[0021] The deceptive navigation signal is focused onto the target path using a metasurface intelligent reflective array.

[0022] Secondly, the present invention also provides a drone navigation deception system, the system comprising:

[0023] The calibration module is used to calibrate the phase of the antenna array, generate an initial point cloud, and load a preset point cloud template library.

[0024] The scanning module is used to scan the surrounding environment in real time to generate a high-precision terrain grid, load an electromagnetic parameter library into the high-precision terrain grid, and combine it with the initial point cloud to build a three-dimensional electromagnetic map.

[0025] The scanning module includes:

[0026] The scanning unit is used to scan the surrounding environment in real time using a lidar to generate a high-precision terrain grid and load an electromagnetic parameter library into the high-precision terrain grid.

[0027] A unit is established to create a reflection model based on the initial point cloud combined with the high-precision terrain mesh after loading the electromagnetic parameter library, and after AI calculation, wherein the reflection model is the three-dimensional electromagnetic map;

[0028] The identification module is used to continuously scan and detect the target drone to output point cloud data, and to identify the model characteristics of the target drone through micro-Doppler features;

[0029] The synthesis module is used to synthesize decoy navigation signals using real-time ephemeris files or stored ephemeris files and according to specified coordinates, and to calculate several reflection paths based on the three-dimensional electromagnetic map;

[0030] The guidance module is used to predict the trajectory of the target UAV in real time based on several reflection paths, and to send the decoy navigation signal to the trajectory through laser point cloud combined with the preset point cloud template library, so as to guide the target UAV to land or drive it away.

[0031] Furthermore, the calibration module includes:

[0032] The calibration unit is used to calibrate the phase of the millimeter-wave radar antenna array, acquire the phase scanning information of the millimeter-wave radar antenna array, and generate an initial point cloud based on the scanning information.

[0033] The loading unit is used to load a preset point cloud template library based on the laser array.

[0034] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described drone navigation deception method.

[0035] Thirdly, the present invention also provides a storage medium on which a computer program is stored, which, when executed by a processor, implements the above-described drone navigation deception method. Attached Figure Description

[0036] Figure 1 This is a flowchart of the drone navigation deception method in the first embodiment of the present invention;

[0037] Figure 2 This is a structural block diagram of the drone navigation deception system in the third embodiment of the present invention;

[0038] Figure 3 This is a structural block diagram of the electronic device according to the fourth embodiment of the present invention.

[0039] Explanation of key component symbols:

[0040] 10. Calibration module; 20. Scanning module; 30. Identification module; 40. Synthesis module; 50. Guidance module;

[0041] 60. Bus; 61. Processor; 62. Memory; 63. Communication interface.

[0042] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0043] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0044] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0046] Example 1

[0047] Please see Figure 1 The image shows a drone navigation deception method according to the first embodiment of the present invention, the method comprising steps S1 to S5:

[0048] S1, calibrate the antenna array phase, generate an initial point cloud, and load a preset point cloud template library;

[0049] Specifically, step S1 includes steps S11 to S12:

[0050] S11, calibrate the phase of the millimeter-wave radar antenna array, obtain the phase scanning information of the millimeter-wave radar antenna array, and generate an initial point cloud based on the scanning information;

[0051] S12, Load the preset point cloud template library according to the laser array;

[0052] It should be noted that the millimeter-wave radar calibrates the antenna array phase to ensure beam pointing accuracy, then starts scanning to detect objects within 300 meters and generate an initial point cloud; the laser preheats and performs a self-test, checks the galvanometer deflection range, loads a preset point cloud template library (such as building and tree models), and controls the core to load the phase table of the reflection unit, tests the dynamic tuning response (0~360° continuous adjustment), and verifies the GPS L1 / L2 band reflection efficiency (>85%).

[0053] S2, scan the surrounding environment in real time to generate a high-precision terrain grid, load an electromagnetic parameter library into the high-precision terrain grid, and combine it with the initial point cloud to build a three-dimensional electromagnetic map;

[0054] Specifically, step S2 includes steps S21 to S22:

[0055] S21, The surrounding environment is scanned in real time by lidar to generate a high-precision terrain grid, and an electromagnetic parameter library is loaded into the high-precision terrain grid;

[0056] S22, Based on the initial point cloud combined with the high-precision terrain mesh after loading the electromagnetic parameter library, and after AI calculation, a reflection model is established, wherein the reflection model is the three-dimensional electromagnetic map;

[0057] Understandably, lidar scans the surrounding environment, generates a high-precision terrain mesh, and then loads an electromagnetic parameter library (e.g., for glass curtain walls). r=4.2, concrete (r=6.5), combined with the initial point cloud generated by the previous millimeter-wave radar, a 3D reflection model, i.e. a three-dimensional electromagnetic map, is established after AI calculation.

[0058] S3, continuously scan and detect the target drone to output point cloud data, and identify the model characteristics of the target drone through micro-Doppler features;

[0059] It should be noted that real-time prediction of the drone's trajectory involves pre-embedding Doppler frequency shift curves into false signals to avoid sudden speed changes triggering navigation system alarms.

[0060] S4, using real-time ephemeris files or stored ephemeris files and synthesizing decoy navigation signals according to specified coordinates, and calculating several reflection paths based on the three-dimensional electromagnetic map;

[0061] Understandably, real-time or stored ephemeris files are used to synthesize decoy navigation signals at specified coordinates. At the same time, several reflection paths that can converge to the target point are calculated based on a three-dimensional electromagnetic map, and the phase control of the metasurface reflective array unit is adjusted accordingly.

[0062] S5. Based on several reflection paths, predict the movement trajectory of the target UAV in real time, and send the decoy navigation signal to the movement trajectory through laser point cloud combined with the preset point cloud template library to guide the target UAV to land or drive it away.

[0063] Understandably, when the target drone does not move or land in the intended direction, a laser point cloud is immediately projected to generate a virtual obstacle about 20m in front of the drone to force it to turn or land. If the drone attempts to detour, the laser galvanometer can quickly deflect and update the point cloud position and shape to continue blocking the drone's direction of movement to prevent it from detouring.

[0064] It should be noted that a low-power decoy signal is transmitted only to the direction of the UAV receiver. The decoy energy is then focused onto the target path using a metasurface intelligent reflective array, achieving "stealth illumination." Furthermore, the position measurement deviation caused by the decoy signal is mistakenly identified by the onboard trajectory tracking and control system as persistent lateral wind interference. In this situation, the UAV, based on its preset flight control algorithm, autonomously adjusts its heading angle parameters, attempting to counteract this "virtual wind disturbance" effect by deflecting the control surfaces, thereby causing its flight trajectory to converge back to the predetermined reference route. By fully utilizing the UAV's inherent trajectory stabilization control mechanism, the entire decoy process conforms to the aircraft's dynamic characteristics while maintaining a high degree of stealth and naturalness, thus significantly reducing the likelihood of being detected by the target system.

[0065] Specifically, step S5 further includes step S51:

[0066] S51, the deceptive navigation signal is focused onto the target path using a metasurface intelligent reflective array.

[0067] It's worth noting that by starting the transmission to the metasurface reflector array via the primary radiator, the first reflected wave can be converged to the target point through multipath secondary reflections from the surrounding environment, maintaining phase consistency so that the target antenna receives a false navigation signal with sufficient power to mask the real satellite navigation signal. At this point, various methods can be used to deceive the target, such as gradually increasing the transmission power from the noise floor and gradually shifting the false navigation coordinates from the target drone's true coordinates, making it less likely for the target drone to detect the deception. If the target drone activates visual / LiDAR positioning, the system immediately switches to laser point cloud deception mode, using a laser array to transmit false obstacle point clouds.

[0068] In summary, the UAV navigation deception method in the above embodiments of the present invention employs a dynamic adaptive algorithm during the deception signal generation process. This algorithm precisely controls multi-dimensional observation parameters such as pseudorange and pseudorange rate of the deception signal, ensuring that the statistical difference (i.e., the innovation sequence) between these parameters and the predicted output value of the inertial navigation system (INS) remains within the preset confidence interval threshold range of the Kalman filter. Through this refined parameter matching strategy, the system can effectively avoid security alarms triggered by anomaly detection mechanisms, thereby significantly improving the concealment and persistence of the deception signal. The UAV is simplified as a point mass moving in a two-dimensional plane, with its motion characteristics described by only three key state variables: planar position coordinates (x, y), velocity v, and heading angle θ. This simplified modeling method not only retains the core characteristics of UAV motion but also significantly reduces the computational complexity of the model by ignoring complex aerodynamic factors. This simplification makes subsequent UAV trajectory prediction and deception path planning problems easier to solve, providing convenient conditions for real-time computation and decision-making in practical applications. Simultaneously, it also provides a theoretical basis for studying complex problems such as UAV swarm behavior and obstacle avoidance strategies.

[0069] Example 2

[0070] The drone navigation deception method in the second embodiment of the present invention includes steps S1 to S6:

[0071] S1, calibrate the antenna array phase, generate an initial point cloud, and load a preset point cloud template library;

[0072] Specifically, step S1 includes steps S11 to S12:

[0073] S11, calibrate the phase of the millimeter-wave radar antenna array, obtain the phase scanning information of the millimeter-wave radar antenna array, and generate an initial point cloud based on the scanning information;

[0074] S12, Load the preset point cloud template library according to the laser array;

[0075] It should be noted that the millimeter-wave radar calibrates the antenna array phase to ensure beam pointing accuracy, then starts scanning to detect objects within 300 meters and generate an initial point cloud; the laser preheats and performs a self-test, checks the galvanometer deflection range, loads a preset point cloud template library (such as building and tree models), and controls the core to load the phase table of the reflection unit, tests the dynamic tuning response (0~360° continuous adjustment), and verifies the GPS L1 / L2 band reflection efficiency (>85%).

[0076] S2, scan the surrounding environment in real time to generate a high-precision terrain grid, load an electromagnetic parameter library into the high-precision terrain grid, and combine it with the initial point cloud to build a three-dimensional electromagnetic map;

[0077] Specifically, step S2 includes steps S21 to S22:

[0078] S21, The surrounding environment is scanned in real time by lidar to generate a high-precision terrain grid, and an electromagnetic parameter library is loaded into the high-precision terrain grid;

[0079] S22, Based on the initial point cloud combined with the high-precision terrain mesh after loading the electromagnetic parameter library, and after AI calculation, a reflection model is established, wherein the reflection model is the three-dimensional electromagnetic map;

[0080] Understandably, lidar scans the surrounding environment, generates a high-precision terrain mesh, and then loads an electromagnetic parameter library (e.g., for glass curtain walls). r=4.2, concrete (r=6.5), combined with the initial point cloud generated by the previous millimeter-wave radar, a 3D reflection model, i.e. a three-dimensional electromagnetic map, is established after AI calculation.

[0081] S3, intercept the image transmission signal of the target drone and analyze the target drone to calculate the target drone's coordinates, altitude, direction of movement, speed and model characteristics;

[0082] S4, estimate the next moment position and attitude of the target UAV using Kalman filtering;

[0083] It should be noted that if the Doppler signature is not obvious, radio frequency fingerprinting is performed. This involves intercepting the drone's image transmission signal (2.4GHz / 5.8GHz), parsing the manufacturer ID (such as DJI's OcuSync protocol), and finally calculating the drone's coordinates, altitude, direction of movement, speed, and model characteristics. This process is continuous, and Kalman filtering is used to estimate the drone's position and attitude at the next moment so that the subsequent decoy launch device can adjust in advance.

[0084] S5, using real-time ephemeris files or stored ephemeris files and synthesizing decoy navigation signals according to specified coordinates, and calculating several reflection paths based on the three-dimensional electromagnetic map;

[0085] Understandably, real-time or stored ephemeris files are used to synthesize decoy navigation signals at specified coordinates. At the same time, several reflection paths that can converge to the target point are calculated based on a three-dimensional electromagnetic map, and the phase control of the metasurface reflective array unit is adjusted accordingly.

[0086] S6. Based on several reflection paths, predict the trajectory of the target UAV in real time, and send the decoy navigation signal to the trajectory through laser point cloud combined with the preset point cloud template library to guide the target UAV to land or drive it away.

[0087] Understandably, when the target drone does not move or land in the intended direction, a laser point cloud is immediately projected to generate a virtual obstacle about 20m in front of the drone to force it to turn or land. If the drone attempts to detour, the laser galvanometer can quickly deflect and update the point cloud position and shape to continue blocking the drone's direction of movement to prevent it from detouring.

[0088] It should be noted that a low-power decoy signal is transmitted only to the direction of the UAV receiver. The decoy energy is then focused onto the target path using a metasurface intelligent reflective array, achieving "stealth illumination." Furthermore, the position measurement deviation caused by the decoy signal is mistakenly identified by the onboard trajectory tracking and control system as persistent lateral wind interference. In this situation, the UAV, based on its preset flight control algorithm, autonomously adjusts its heading angle parameters, attempting to counteract this "virtual wind disturbance" effect by deflecting the control surfaces, thereby causing its flight trajectory to converge back to the predetermined reference route. By fully utilizing the UAV's inherent trajectory stabilization control mechanism, the entire decoy process conforms to the aircraft's dynamic characteristics while maintaining a high degree of stealth and naturalness, thus significantly reducing the likelihood of being detected by the target system.

[0089] Specifically, step S6 further includes step S61:

[0090] S61, the decoy navigation signal is focused onto the target path using a metasurface intelligent reflective array.

[0091] It's worth noting that by starting the transmission to the metasurface reflector array via the primary radiator, the first reflected wave can be converged to the target point through multipath secondary reflections from the surrounding environment, maintaining phase consistency so that the target antenna receives a false navigation signal with sufficient power to mask the real satellite navigation signal. At this point, various methods can be used to deceive the target, such as gradually increasing the transmission power from the noise floor and gradually shifting the false navigation coordinates from the target drone's true coordinates, making it less likely for the target drone to detect the deception. If the target drone activates visual / LiDAR positioning, the system immediately switches to laser point cloud deception mode, using a laser array to transmit false obstacle point clouds.

[0092] Example 3

[0093] The third embodiment of the present invention also provides a drone navigation deception system; please refer to [link / reference]. Figure 2 The image shows a drone navigation deception system according to a third embodiment of the present invention. The system includes:

[0094] The calibration module 10 is used to calibrate the phase of the antenna array, generate an initial point cloud, and load a preset point cloud template library.

[0095] The scanning module 20 is used to scan the surrounding environment in real time to generate a high-precision terrain grid, load an electromagnetic parameter library into the high-precision terrain grid, and combine it with the initial point cloud to establish a three-dimensional electromagnetic map.

[0096] The identification module 30 is used to continuously scan and detect the target drone to output point cloud data, and to identify the model characteristics of the target drone through micro-Doppler features;

[0097] The synthesis module 40 is used to synthesize a decoy navigation signal using a real-time ephemeris file or a stored ephemeris file and according to specified coordinates, and to calculate several reflection paths based on the three-dimensional electromagnetic map.

[0098] The guidance module 50 is used to predict the trajectory of the target UAV in real time based on several reflection paths, and to send the decoy navigation signal to the trajectory through laser point cloud combined with the preset point cloud template library, so as to guide the target UAV to land or drive it away.

[0099] In some alternative embodiments, the calibration module 10 includes:

[0100] The calibration unit is used to calibrate the phase of the millimeter-wave radar antenna array, acquire the phase scanning information of the millimeter-wave radar antenna array, and generate an initial point cloud based on the scanning information.

[0101] The loading unit is used to load a preset point cloud template library based on the laser array.

[0102] In some alternative embodiments, the scanning module 20 includes:

[0103] The scanning unit is used to scan the surrounding environment in real time using a lidar to generate a high-precision terrain grid and load an electromagnetic parameter library into the high-precision terrain grid.

[0104] A unit is established to create a reflection model based on the initial point cloud combined with the high-precision terrain mesh after loading the electromagnetic parameter library, and after AI calculation, wherein the reflection model is the three-dimensional electromagnetic map.

[0105] In some alternative embodiments, the guiding module 50 includes:

[0106] A focusing unit is used to focus the decoy navigation signal onto the target path via a metasurface smart reflective array.

[0107] In some alternative embodiments, the system further includes:

[0108] The analysis and calculation module is used to intercept the image transmission signal of the target UAV and analyze the target UAV to calculate the target UAV's coordinates, altitude, direction of movement, speed, and model characteristics.

[0109] The estimation module is used to estimate the next position and attitude of the target UAV through Kalman filtering.

[0110] The functions or operation steps implemented by the above modules and units are largely the same as those in the above method embodiments, and will not be repeated here.

[0111] The drone navigation deception system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0112] Example 4

[0113] The fourth embodiment of the present invention also proposes an electronic device, please refer to [link / reference]. Figure 3 The image shows an electronic device according to the fourth embodiment of the present invention.

[0114] The electronic device may include a processor 61 and a memory 62 storing computer program instructions.

[0115] Specifically, the processor 61 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the present application.

[0116] The memory 62 may include a large-capacity storage device for data or instructions. For example, and not limitingly, the memory 62 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 62 may include removable or non-removable (or fixed) media. Where appropriate, the memory 62 may be internal or external to a data processing device. In a particular embodiment, the memory 62 is non-volatile memory. In a particular embodiment, the memory 62 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), Extended Data Out Dynamic Random-Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0117] The memory 62 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 61.

[0118] The processor 61 reads and executes the computer program instructions stored in the memory 62 to implement the drone navigation deception method described in Embodiment 1 above.

[0119] In some embodiments, the electronic device may further include a communication interface 63 and a bus 60. For example, Figure 3 As shown, the processor 61, memory 62, and communication interface 63 are connected through bus 60 and complete communication with each other.

[0120] The communication interface 63 is used to enable communication between the various modules, devices, units, and / or equipment in this application. The communication interface 63 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0121] Bus 60 includes hardware, software, or both, that couples components of a device together. Bus 60 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 60 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 60 may include one or more buses. Although this application describes and illustrates a specific bus, this application considers any suitable bus or interconnection.

[0122] The electronic device can acquire the drone navigation deception system and execute the drone navigation deception method of this embodiment.

[0123] Furthermore, in conjunction with the drone navigation deception method in Embodiment 1 above, this application can provide a storage medium for implementation. This storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement the drone navigation deception method of Embodiment 1 above.

[0124] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0125] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for deceiving drone navigation, characterized in that, The method includes: The antenna array phase is calibrated, an initial point cloud is generated, and a preset point cloud template library is loaded. The surrounding environment is scanned in real time to generate a high-precision terrain mesh. An electromagnetic parameter library is loaded into the high-precision terrain mesh, and a three-dimensional electromagnetic map is built by combining it with the initial point cloud. This step specifically includes: The surrounding environment is scanned in real time by lidar to generate a high-precision terrain grid, and an electromagnetic parameter library is loaded into the high-precision terrain grid. Based on the initial point cloud and the high-precision terrain mesh after loading the electromagnetic parameter library, a reflection model is established after AI calculation, wherein the reflection model is the three-dimensional electromagnetic map; The system continuously scans and detects target drones to output point cloud data, and identifies the model characteristics of the target drones through micro-Doppler features. Using real-time ephemeris files or stored ephemeris files and synthesizing decoy navigation signals according to specified coordinates, and calculating several reflection paths based on the three-dimensional electromagnetic map; The trajectory of the target UAV is predicted in real time based on several reflection paths, and the decoy navigation signal is emitted to the trajectory through laser point cloud combined with the preset point cloud template library to guide the target UAV to land or drive it away.

2. The drone navigation deception method according to claim 1, characterized in that, The steps of calibrating the antenna array phase, generating an initial point cloud, and loading a preset point cloud template library include: The phase of the millimeter-wave radar antenna array is calibrated, the phase scanning information of the millimeter-wave radar antenna array is obtained, an initial point cloud is generated based on the scanning information, and a preset point cloud template library is loaded.

3. The drone navigation deception method according to claim 1, characterized in that, Following the step of establishing a three-dimensional electromagnetic map by combining the initial point cloud, the method further includes: The image transmission signal of the target drone is intercepted and analyzed to calculate the target drone's coordinates, altitude, direction of movement, speed, and model characteristics. The next position and attitude of the target UAV are estimated using Kalman filtering.

4. The drone navigation deception method according to claim 1, characterized in that, After the step of transmitting the deceptive navigation signal to the motion trajectory using laser point cloud combined with the preset point cloud template library, the method further includes: The deceptive navigation signal is focused onto the target path using a metasurface intelligent reflective array.

5. A drone navigation deception system, characterized in that, The system includes: The calibration module is used to calibrate the phase of the antenna array, generate an initial point cloud, and load a preset point cloud template library. The scanning module is used to scan the surrounding environment in real time to generate a high-precision terrain grid, load an electromagnetic parameter library into the high-precision terrain grid, and combine it with the initial point cloud to build a three-dimensional electromagnetic map. The scanning module includes: The scanning unit is used to scan the surrounding environment in real time using a lidar to generate a high-precision terrain grid and load an electromagnetic parameter library into the high-precision terrain grid. A unit is established to create a reflection model based on the initial point cloud combined with the high-precision terrain mesh after loading the electromagnetic parameter library, and after AI calculation, wherein the reflection model is the three-dimensional electromagnetic map; The identification module is used to continuously scan and detect the target drone to output point cloud data, and to identify the model characteristics of the target drone through micro-Doppler features; The synthesis module is used to synthesize decoy navigation signals using real-time ephemeris files or stored ephemeris files and according to specified coordinates, and to calculate several reflection paths based on the three-dimensional electromagnetic map; The guidance module is used to predict the trajectory of the target UAV in real time based on several reflection paths, and to send the decoy navigation signal to the trajectory through laser point cloud combined with the preset point cloud template library, so as to guide the target UAV to land or drive it away.

6. The drone navigation deception system according to claim 5, characterized in that, The calibration module includes: The calibration unit is used to calibrate the phase of the millimeter-wave radar antenna array, acquire the phase scanning information of the millimeter-wave radar antenna array, generate an initial point cloud based on the scanning information, and load a preset point cloud template library.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the drone navigation deception method as described in any one of claims 1 to 4.

8. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the drone navigation deception method as described in any one of claims 1 to 4.

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