Unmanned aerial vehicle deception signal determination method and device, equipment and storage medium

Abstract

The invention discloses an unmanned aerial vehicle deception signal determination method and device, equipment and a storage medium. The method comprises the following steps: acquiring motion track information and state information of a to-be-spoofed unmanned aerial vehicle; generating a cheating track according to the current position of the cheating equipment and the motion track information; determining first estimated state information and second estimated state information of the unmanned aerial vehicle according to the state information and the deception trajectory; determining a deception signal value at the current moment based on the first estimation state information and the second estimation state information; generating a deception signal according to the deception signal value; wherein the first estimation state information is an estimation state based on an unmanned aerial vehicle navigation system, and the second estimation state information is an estimation state based on an unmanned aerial vehicle inertial navigation system. According to the method, the deception signal value is determined after the state of the unmanned aerial vehicle is estimated, and the deception signal is generated according to the deception signal value, so that the deception task of unmanned aerial vehicle navigation can be completed according to the deception signal.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of navigation deception technology, and in particular to a method, apparatus, device, and storage medium for determining drone deception signals. Background Art

[0002] Drones are autonomous or radio-controlled aircraft with significant advantages, including ease of operation, low cost, high flexibility, and small size. Due to their cost advantage, drones are increasingly being used in a variety of fields, including power inspections, pollution monitoring, aerial photography, and disaster prevention and mitigation. However, with the rapid expansion of drone usage, the number of safety incidents caused by illegal drone operations is also increasing. Therefore, how to combat illegal drone operations, eliminate the various safety incidents caused by illegal drone operations, and safeguard public safety remains an unresolved issue.

[0003] Among existing methods, Global Positioning System (GPS) spoofing has been widely used in the fight against illegal drones. It uses a spoofing device to transmit a spoofing signal with erroneous location information that is consistent with the structure of the real GPS signal, causing the target drone's receiving terminal to generate erroneous positioning information based on the received spoofing signal, thereby locating itself in the wrong position. Ideally, the drone is unaware that it has been interfered with and is ultimately induced to complete the task set by the fraudster. However, in reality, drones that use a combination of global navigation satellite systems and inertial navigation systems for positioning and navigation have been widely used. When the erroneous position in the set spoofing signal deviates significantly from the position information received by the drone at the previous moment, the drone will usually detect its deviation from its flight path through its own inertial navigation system to identify navigation spoofing.

[0004] Therefore, in this case, how to more effectively deceive drone navigation is an urgent problem to be solved. Summary of the Invention

[0005] The present invention provides a method, device, equipment and storage medium for determining a drone spoofing signal, so as to solve the problem that the prior art cannot effectively complete the deception of drone navigation.

[0006] According to one aspect of the present invention, a method for determining a drone spoofing signal is provided, the method comprising:

[0007] Obtain the motion trajectory and status information of the drone to be deceived;

[0008] generating a spoofing trajectory according to the current position of the spoofing device and the motion trajectory information;

[0009] determining first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory;

[0010] determining a spoofing signal value at a current moment based on the first estimated state information and the second estimated state information;

[0011] generating a spoofing signal according to the spoofing signal value;

[0012] The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV inertial navigation system.

[0013] According to another aspect of the present invention, a device for determining a drone spoofing signal is provided, the device comprising:

[0014] An acquisition module is used to obtain the motion trajectory information and status information of the drone to be deceived;

[0015] A trajectory generation module, configured to generate a deception trajectory according to the current position of the deception device and the motion trajectory information;

[0016] a first determining module, configured to determine first estimated state information and second estimated state information of the drone based on the state information and the deception trajectory;

[0017] a second determining module, configured to determine a spoofing signal value at a current moment based on the first estimated state information and the second estimated state information;

[0018] a signal generating module, configured to generate a spoofing signal according to the spoofing signal value;

[0019] The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV inertial navigation system.

[0020] According to another aspect of the present invention, there is provided an electronic device, comprising: at least one processor; and

[0021] a memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the drone spoofing signal determination method described in any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the drone spoofing signal determination method described in any embodiment of the present invention when executed.

[0024] Embodiments of the present invention provide a method, apparatus, device, and storage medium for determining a drone spoofing signal. The method comprises: obtaining motion trajectory information and state information of a drone to be spoofed; generating a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information; determining first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory; determining a spoofing signal value at the current moment based on the first estimated state information and the second estimated state information; and generating a spoofing signal based on the spoofing signal value. The first estimated state information is an estimated state based on the drone's navigation system, and the second estimated state information is an estimated state based on the drone's inertial navigation system. This method determines the spoofing signal value after estimating the drone's state, and generates a spoofing signal based on the spoofing signal value. This method can accomplish the task of spoofing the drone's navigation based on the spoofing signal, resolving the problem of the prior art in effectively accomplishing spoofing the drone's navigation.

[0025] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 A schematic diagram of a flow chart of a method for determining a drone spoofing signal provided in the first embodiment of the present invention;

[0028] Figure 2 A schematic diagram of determining an acceleration control amount provided by an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of determining the coordinates of a deceptive location point provided by an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of another method for determining the coordinates of a deceptive location point provided by an embodiment of the present invention;

[0031] Figure 5This is a schematic diagram of the structure of a device for determining a drone spoofing signal provided in the second embodiment of the present invention;

[0032] Figure 6 Schematic diagram of the structure of an electronic device for determining a drone spoofing signal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only embodiments of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention. It should be understood that the various steps described in the method implementation mode of the present invention can be performed in different orders and / or in parallel. In addition, the method implementation mode may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0034] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to." The term "based on" means "based, at least in part, on." The term "one embodiment" means "at least one embodiment," the term "another embodiment" means "at least one additional embodiment," and the term "some embodiments" means "at least some embodiments." Other terms are defined in the following description.

[0035] It should be noted that the terms "first," "second," and the like in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, any variations of the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatus.

[0036] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0037] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0038] Example 1

[0039] Figure 1 This is a flow chart of a method for determining a drone spoofing signal provided in Example 1 of the present invention. This method is applicable to situations where a spoofing signal for drone navigation is generated based on information about the drone and information about the spoofing device. The method can be performed by a drone spoofing signal determination device, where the device can be implemented by software and / or hardware and is generally integrated into an electronic device. In this embodiment, the electronic device includes but is not limited to: a spoofing device or other computer equipment.

[0040] like Figure 1 As shown, a method for determining a drone spoofing signal provided by the first embodiment of the present invention includes the following steps:

[0041] S110: Obtain motion trajectory information and status information of the drone to be deceived.

[0042] The motion trajectory information may include the drone's position information, speed information, and target position, where the target position may be the desired location of the drone. The state information may be used to indicate the drone's motion state, and may include the drone's position information and speed information.

[0043] In this embodiment, the motion trajectory information and status information of the drone to be deceived can be obtained.

[0044] S120: Generate a spoofing trajectory according to the current position of the spoofing device and the motion trajectory information.

[0045] A spoofing device can be used to disrupt or mislead the normal operation of other devices or systems by transmitting false signals or information. A spoofing device can capture the target drone's navigation signal frequency band, identify its satellite navigation system type, and then simulate the signal from a navigation satellite, overwhelming the drone's receiving antenna with a stronger power source to replace the real navigation signal. By transmitting falsified location information, the drone mistakenly believes it is in a different location, causing it to deviate from its route, hover, or automatically return. A spoofed trajectory can be a false movement trajectory that can be used to mislead drones.

[0046] In this embodiment, a spoofing trajectory that can mislead a drone can be generated based on the current location and motion trajectory information of the spoofing device. For example, the coordinates of multiple spoofing points can be determined based on the current location of the spoofing device and the motion trajectory information of the drone, and the coordinates of the multiple spoofing points can be used as the spoofing trajectory.

[0047] For example, the position information A of the deceptive device and the motion trajectory information of the current illegal drone are obtained. The motion trajectory information includes the position information P, the speed information v and the target position B. Based on the position information A and the motion state information of the deceptive device, the coordinates of multiple deceptive position points P are obtained. t (x pt ,y pt ), so that it satisfies (x pt ,y pt ) is the coordinate position of the UAV at time t, (x pt-1 ,y pt-1 ) is the coordinate point position of the drone at time t-1. The preset deception trajectory can be obtained based on the coordinates of multiple deception positions in, is the trajectory coordinate position of the UAV preset at time t, are the horizontal and vertical coordinates of the trajectory coordinate position of the UAV preset at time t, The speed corresponding to the preset trajectory coordinate position at time t, The horizontal and vertical components of the velocity corresponding to the preset trajectory coordinate position at time t, is the acceleration corresponding to the preset trajectory coordinate position at time t, The horizontal and vertical components of the acceleration corresponding to the preset trajectory coordinate position at time t, where t = 0, T, 2T, 3T, ..., nT.

[0048] S130 . Determine first estimated state information and second estimated state information of the drone according to the state information and the deception trajectory.

[0049] The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV's inertial navigation system. The UAV navigation system may include multiple subsystems such as satellite navigation, inertial navigation, visual navigation, or radio navigation. The UAV inertial navigation system may refer to a navigation system primarily composed of an inertial measurement unit.

[0050] In this embodiment, the first estimated state information and the second estimated state information of the drone may be determined according to the state information and the deception trajectory of the drone.

[0051] In one embodiment, determining the first estimated state information and the second estimated state information of the drone based on the state information and the deception trajectory includes: determining the acceleration control amount at the current moment based on the state information at the current moment, the deception trajectory and the acceleration information of the drone at the current moment; determining the first estimated state information of the drone at the current moment based on the acceleration control amount, the deception trajectory and the first formula; determining the second estimated state information of the drone at the current moment based on the acceleration control amount estimated at the previous moment, the second estimated state information corrected at the previous moment and the second formula.

[0052] The acceleration control value may be a value expected by the deceptive device and can be used to estimate the state of the drone.

[0053] In this embodiment, the acceleration control amount at the current moment can be determined based on the current state information, the deception trajectory, and the acceleration information of the drone at the current moment. The first estimated state information of the drone at the current moment can be determined by the acceleration control amount, the deception trajectory, and the first formula. The second estimated state information of the drone at the current moment can be determined based on the acceleration control amount at the previous moment, the second estimated state information corrected at the previous moment, and the second formula. The second estimated state information corrected at the previous moment can be corrected based on the first estimated state information calculated at the previous moment. For example, the first estimated state information calculated at time t can be corrected based on the first estimated state information calculated at the previous moment. As the second estimated state information corrected at the last moment Thus, the corrected inertial navigation system value is obtained.

[0054] For example, in this embodiment, the status information of the illegal drone at time t can be obtained through period T. And acceleration information a t , where status information Including the location information of the illegal drone at time t and speed information is the trajectory coordinate position of the UAV at time t, are the horizontal and vertical coordinates of the trajectory coordinate position of the UAV at time t, is the velocity corresponding to the trajectory coordinate position of the UAV at time t, The horizontal and vertical components of the velocity corresponding to the trajectory coordinate position of the UAV at time t are updated. and the second estimated state information of the inertial navigation system in is the estimated position of the UAV at time t, is the estimated speed of the UAV at time t.

[0055] In one embodiment, determining the acceleration control amount at the current moment based on the current state information, the spoofing trajectory, and the acceleration information of the drone at the current moment includes:

[0056] Using the current state information as the first estimated state information of the drone that has not been updated at the current moment;

[0057] Based on the unupdated first estimated state information, the deception trajectory and the acceleration information of the drone at the current moment, the acceleration control amount a at the current moment is determined in combination with the proportional differential algorithm. * :

[0058]

[0059] Among them, a t is the acceleration of the UAV at time t, K p is the proportional gain of the proportional differential algorithm, is the first estimated state information at time t, is the deception trajectory at time t.

[0060] Among them, the proportional differential algorithm can refer to a control algorithm that determines the control quantity by calculating the current error of the system and the rate of change of the error, so as to achieve the purpose of quickly and accurately controlling the controlled object.

[0061] In this embodiment, the current state information can be used as the first estimated state information of the drone that has not been updated at the current moment. For example, Afterwards, the acceleration control amount at the current moment can be determined by combining the first estimated state information that has not been updated, the deception trajectory, and the acceleration information of the drone at the current moment with the proportional differential algorithm. For example, Figure 2 This is a schematic diagram of determining the acceleration control amount provided by an embodiment of the present invention. The key to navigation deception is to send false signals to make the drone generate the same The same acceleration. Figure 2 As shown in Figure 2, the spoofing signal causes the state of the UAV, which uses a combined navigation system of the global navigation satellite system and the inertial navigation system, to change from the real state to the estimated state. The UAV control produces incorrect acceleration. The drone is then controlled to approach the deceptive target state. The drone regards the estimated state as its true state and thinks it is moving from the estimated state to the original target state. In fact, the drone will move from its true state position to the deceptive state position.

[0062] In one embodiment, the first formula is:

[0063]

[0064] in, is the first estimated state information estimated at time t, is the position of the first estimated state information, is the speed of the first estimated state information; is the trajectory coordinate position of the deception trajectory at time t, a * is the acceleration control quantity, K p is the proportional gain of the proportional differential algorithm, is the velocity corresponding to the trajectory coordinate position of the deceptive trajectory at time t;

[0065] The second formula is:

[0066]

[0067] in, is the second estimated state information estimated at time t, T is the period for obtaining UAV status information, I 2*2 is the second-order identity matrix, 0 2*2 is a two-order zero matrix, is the output of the second estimated state information after correction of the inertial navigation system estimated at time t-1, is the estimated value of the acceleration of the UAV at time t-1.

[0068] In this embodiment, the first estimated state information and the second estimated state information of the drone can be updated in various ways. In this embodiment, the estimated value of the drone's acceleration can be obtained by processing the drone's relevant state data obtained by the spoofing device through radar or other detection devices. The specific determination method is not limited in this embodiment. For example, based on its own "judgment" of the drone's motion state or a preset interference strategy, the device can use a built-in accelerometer to simulate a corresponding acceleration signal, or parse the signal to determine the drone's current attitude angle, throttle control amount, and other parameters. Based on these parameters and some kinematic models, the possible acceleration of the drone can be estimated. Alternatively, the currently monitored drone flight environment, attitude, and other characteristics can be input into a trained model, and the model can output a corresponding acceleration estimate.

[0069] S140: Determine a spoofing signal value at a current moment based on the first estimated state information and the second estimated state information.

[0070] The spoofing signal value may refer to the parameter value of a false signal generated by a spoofing device and sent to the drone. For example, the spoofing signal value may include false latitude and longitude coordinates, speed, acceleration and other parameters.

[0071] In this embodiment, the spoofing signal value at the current moment may be calculated based on the first estimated state information and the second estimated state information.

[0072] In one embodiment, determining the spoofing signal value at the current moment based on the first estimated state information and the second estimated state information includes:

[0073] The deception signal value at the current moment is calculated by the following formula

[0074]

[0075] in, is the second estimated state information estimated at time t, is the first estimated state information estimated at time t, K p is the proportional gain of the proportional derivative algorithm.

[0076] In this embodiment, the spoofing signal value may be calculated using a preset formula.

[0077] S150: Generate a spoofing signal according to the spoofing signal value.

[0078] In this embodiment, the deception signal can be generated by the deception signal value at the current moment. The specific generation method can be set according to the actual situation and is not limited in this example. For example, the deception signal value at time t can be A spoofing signal is generated based on a known GPS structure signal to transmit a spoofing signal to an illegal drone. The known GPS structure signal may refer to the structure of the composition, format, encoding method, frequency characteristics, etc. of the global positioning system signal.

[0079] A first embodiment of the present invention provides a method for determining a drone spoofing signal, comprising: obtaining motion trajectory information and state information of a drone to be spoofed; generating a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information; determining first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory; determining a spoofing signal value at the current moment based on the first estimated state information and the second estimated state information; and generating a spoofing signal based on the spoofing signal value; wherein the first estimated state information is an estimated state based on the drone's navigation system, and the second estimated state information is an estimated state based on the drone's inertial navigation system. This method estimates the drone's state, determines the spoofing signal value, and generates a spoofing signal based on the spoofing signal value, thereby enabling the deception of drone navigation based on the spoofing signal, thereby resolving the problem of the prior art in effectively deceiving drone navigation.

[0080] Based on the above embodiment, a modified embodiment of the above embodiment is proposed. It should be noted that, in order to simplify the description, only the differences from the above embodiment are described in the modified embodiment.

[0081] In one embodiment, the motion trajectory information includes the current position and current speed of the drone. Accordingly, generating a deception trajectory based on the current position of the deception device and the motion trajectory information includes: determining a coordinate interval based on the current speed; taking the coordinate interval as the interval between coordinate points, selecting multiple coordinates from the line between the current position of the deception device and the current position of the drone to obtain multiple deception position point coordinates; and generating a deception trajectory based on the multiple deception position point coordinates.

[0082] In this embodiment, the motion trajectory information may include the current position and current speed of the drone. After obtaining the motion trajectory information of the drone, the interval between the coordinate points to be selected can be determined based on the current speed of the drone. For example, the speed value can be directly used as the coordinate interval, or the value corresponding to the speed multiple can be used as the coordinate interval. After determining the coordinate interval, multiple coordinates can be selected from the line connecting the current position of the deceptive device and the current position of the drone. For example, coordinate points can be selected on either side of the current position of the drone on the line, and a deceptive trajectory can be generated based on the coordinates of multiple deceptive position points. For example, the spoofed location coordinates can be used as the trajectory coordinates Track coordinate position Corresponding speed and acceleration The value can be set based on actual conditions, and this embodiment does not limit this. For example, the acceleration required to lure the drone to the target trajectory point can be calculated using a navigation deception algorithm. In this embodiment, the altitude of the drone can remain unchanged during flight.

[0083] This embodiment obtains the motion state of the illegal drone, sets multiple deceptive positions with speed value intervals to form a deceptive trajectory, calculates the acceleration required to lure the drone to the target trajectory point through a navigation deception algorithm, generates a corresponding deceptive signal, and induces the drone navigation controller to output the corresponding acceleration. This avoids the situation where the erroneous position in the set deceptive signal deviates greatly from the position information received by the drone at the previous moment, which may cause the drone to identify the navigation deception, thereby improving the success rate of navigation deception.

[0084] For example, Figure 3 A schematic diagram of determining the coordinates of a deceptive location point provided by an embodiment of the present invention is shown as follows: Figure 3 As shown, the location information A of the spoofing device, the location information P of the current illegal flying drone, and the speed information v of the drone are obtained to obtain the AP direction vector Along direction vector direction, in On the extension line (can also be from Select coordinate points in the opposite direction of the speed v), and obtain multiple deceptive position coordinate points P1, P2, P3, ..., P with the speed v size |v| as the interval. t Since the deviation between two adjacent coordinate points is small, it can effectively avoid the error position in the set deception signal from being greatly deviated from the position information received by the drone at the previous moment and being identified as navigation deception by the drone, thereby improving the success rate of navigation deception.

[0085] In one embodiment, the motion trajectory information includes the current position, current speed and target position of the drone. Accordingly, generating a deception trajectory based on the current position of the deception device and the motion trajectory information includes: determining the radius of a circle based on the current speed, and obtaining a circle corresponding to the drone at the current position with the current position of the drone as the center of the circle; determining the deception position point coordinates at the next moment based on the current position of the deception device and the tangent point coordinates corresponding to the straight line passing through the target position and tangent to the circle; using the deception position point coordinates at the next moment as the center of the circle, and regenerating the circle corresponding to the drone at the next position based on the radius; re-determining new deception position point coordinates based on the circle and the target position, until a preset number of deception position point coordinates are obtained, and generating a deception trajectory based on the preset number of deception position point coordinates.

[0086] In this embodiment, the motion trajectory information includes the drone's current position, current speed, and target position. The current speed can be used as the radius of a circle, or a multiple of the current speed can be used as the radius of the circle. With the drone's current position as the center, a circle is generated at the drone's current position. A tangent line to the circle passing through the target position is determined. This tangent line has two tangent point coordinates on the circle. One of these tangent point coordinates can be selected based on the spoofing device's current position. For example, if the drone is expected to approach the spoofing device, the tangent point coordinate farther from the spoofing device's current position is selected. If the drone is expected to move away from the spoofing device, the tangent point coordinate closer to the spoofing device's current position is selected. The selected tangent point coordinate is used as the spoofing location coordinate at the next moment, and the spoofing location coordinate at the next moment is used as the center of the circle. Based on the radius, a new circle corresponding to the drone's next position is generated. The step of determining new spoofing location coordinates based on the circle and the target position is repeated until a predetermined number of spoofing location coordinates are obtained. A spoofing trajectory is generated based on these predetermined number of spoofing location coordinates.

[0087] In this embodiment, the altitude of the drone during flight may remain unchanged.

[0088] For example, Figure 4 A schematic diagram of another method for determining the coordinates of a deceptive location point provided by an embodiment of the present invention is shown as follows: Figure 4 As shown, the position information A of the deceptive device, the position information P0 of the current illegal drone, the speed information v and the target position information B are obtained, and a circle with P0 as the center and v as the radius is used as the circle of the drone's initial actual position. A straight line passing through the target position B and tangent to the circle is obtained, and the tangent point coordinates P1 are used as the deceptive position point coordinates at the next moment. A circle with the deceptive position point P1 as the center and v as the radius is established. Repeat the above steps to obtain multiple deceptive position point coordinates P1, P2, P3, ..., P t In this method, P0 represents the true position of the drone, and B is the destination of the drone. Without navigation deception, the drone moves in the direction of P0B. When performing navigation deception interference, the purpose of the spoofer is to make the drone's movement direction deviate from P0B. When the deceptive coordinate P1 is obtained, the drone's positioning result is deceived into P1. Because B is the drone's target position, the drone adjusts its direction to move along P1B. However, in reality, the drone's true position is P0, so the drone will move in the direction of P0C, where P0C is parallel to P1B. When P0P1 is tangent to the ray starting from point B at the tangent point P1, the angle ∠BP1C of the drone's motion deviation is maximized, which can effectively prevent the navigation deception from being recognized by the drone and maximize the deviation of the drone from the target position.

[0089] This embodiment maximizes the angle of the drone's motion deviation by establishing a circle tangent point with the deceptive position point as the center and the size of the circle v as the radius as the deceptive position point. This can effectively prevent the navigation deception from being recognized by the drone and maximize the deviation of the drone from the target position.

[0090] Example 2

[0091] Figure 5 This is a schematic diagram of the structure of a drone spoofing signal determination device provided in Example 2 of the present invention. The device can be used to generate spoofing signals for drone navigation based on drone information and spoofing device information. The device can be implemented by software and / or hardware and is generally integrated into an electronic device.

[0092] like Figure 5 As shown, the device includes:

[0093] An acquisition module 210 is used to obtain the motion trajectory information and status information of the drone to be deceived;

[0094] A trajectory generation module 220 is configured to generate a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information;

[0095] A first determining module 230 is configured to determine first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory;

[0096] A second determining module 240 is configured to determine a current spoofing signal value based on the first estimated state information and the second estimated state information;

[0097] a signal generating module 250, configured to generate a spoofing signal according to the spoofing signal value;

[0098] The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV inertial navigation system.

[0099] This embodiment provides a drone spoofing signal determination device, comprising: an acquisition module for acquiring motion trajectory information and state information of a drone to be spoofed; a trajectory generation module for generating a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information; a first determination module for determining first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory; a second determination module for determining a spoofing signal value at the current moment based on the first estimated state information and the second estimated state information; and a signal generation module for generating a spoofing signal based on the spoofing signal value. The first estimated state information is an estimated state based on the drone's navigation system, and the second estimated state information is an estimated state based on the drone's inertial navigation system. By estimating the drone's state and determining the spoofing signal value, and generating a spoofing signal based on the spoofing signal value, the device can accomplish the task of spoofing the drone's navigation using the spoofing signal, thereby resolving the problem of the prior art in effectively accomplishing spoofing the drone's navigation.

[0100] Furthermore, the first determining module 230 includes:

[0101] Determining an acceleration control amount at a current moment based on the current state information, the spoofing trajectory, and the current acceleration information of the drone;

[0102] Determining first estimated state information of the drone at a current moment based on the acceleration control amount, the spoofing trajectory, and a first formula;

[0103] The second estimated state information of the UAV at the current moment is determined based on the acceleration control amount estimated at the previous moment, the second estimated state information corrected at the previous moment, and the second formula.

[0104] Furthermore, determining the acceleration control amount at the current moment based on the current state information, the deception trajectory, and the acceleration information of the drone at the current moment includes:

[0105] Using the current state information as the first estimated state information of the drone that has not been updated at the current moment;

[0106] Based on the unupdated first estimated state information, the deception trajectory and the acceleration information of the drone at the current moment, the acceleration control amount a at the current moment is determined in combination with the proportional differential algorithm. * :

[0107]

[0108] Among them, a t is the acceleration of the UAV at time t, K p is the proportional gain of the proportional differential algorithm, is the first estimated state information at time t, is the deception trajectory at time t.

[0109] Furthermore, the first formula is:

[0110]

[0111] in, is the first estimated state information estimated at time t, is the position of the first estimated state information, is the speed of the first estimated state information; is the trajectory coordinate position of the deception trajectory at time t, a * is the acceleration control quantity, K p is the proportional gain of the proportional-differential algorithm, is the velocity corresponding to the trajectory coordinate position of the deceptive trajectory at time t;

[0112] The second formula is:

[0113]

[0114] in, is the second estimated state information estimated at time t, T is the period for obtaining UAV status information, I 2*2 is the second-order identity matrix, 0 2*2 is a two-order zero matrix, is the output of the second estimated state information after correction of the inertial navigation system estimated at time t-1, is the estimated value of the acceleration of the UAV at time t-1.

[0115] Furthermore, the second determining module 240 includes:

[0116] The deception signal value at the current moment is calculated by the following formula

[0117]

[0118] in, is the second estimated state information estimated at time t, is the first estimated state information estimated at time t, K p is the proportional gain of the proportional derivative algorithm.

[0119] Furthermore, the motion trajectory information includes the current position and current speed of the UAV. Accordingly, the trajectory generation module 220 includes:

[0120] determining a coordinate interval based on the current velocity;

[0121] Taking the coordinate interval as the interval between coordinate points, select multiple coordinates from the line connecting the current position of the spoofing device and the current position of the drone to obtain multiple spoofing position point coordinates;

[0122] A deception trajectory is generated according to the coordinates of the multiple deception position points.

[0123] Furthermore, the motion trajectory information includes the current position, current speed, and target position of the UAV. Accordingly, the trajectory generation module 220 includes:

[0124] Determine the radius of the circle based on the current speed, and obtain the circle corresponding to the current position of the drone with the current position of the drone as the center of the circle;

[0125] Determining the coordinates of the spoofing location point at the next moment based on the current location of the spoofing device and the coordinates of the tangent point corresponding to the straight line passing through the target location and tangent to the circle;

[0126] Using the coordinates of the spoofed position at the next moment as the center of the circle, regenerate the circle corresponding to the drone's next position based on the radius;

[0127] New deceptive position point coordinates are re-determined based on the circle and the target position until a preset number of deceptive position point coordinates are obtained, and a deceptive trajectory is generated according to the preset number of deceptive position point coordinates.

[0128] The above-mentioned drone deception signal determination device can execute the drone deception signal determination method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0129] Example 3

[0130] Figure 6 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0131] like Figure 6As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0132] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0133] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as the method for determining a drone spoofing signal.

[0134] In some embodiments, the drone spoofing signal determination method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the drone spoofing signal determination method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the drone spoofing signal determination method in any other suitable manner (e.g., via firmware).

[0135] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0136] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0137] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0138] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0139] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0140] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0141] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0142] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for determining a drone spoofing signal, characterized in that: The method comprises: Obtain the motion trajectory and status information of the drone to be deceived; generating a spoofing trajectory according to the current position of the spoofing device and the motion trajectory information; determining first estimated state information and second estimated state information of the drone based on the state information and the spoofing trajectory; determining a spoofing signal value at a current moment based on the first estimated state information and the second estimated state information; generating a spoofing signal according to the spoofing signal value; The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV inertial navigation system.

2. The method according to claim 1, characterized in that Determining first estimated state information and second estimated state information of the drone based on the state information and the deception trajectory includes: Determining an acceleration control amount at a current moment based on the current state information, the spoofing trajectory, and the current acceleration information of the drone; Determining first estimated state information of the drone at a current moment based on the acceleration control amount, the spoofing trajectory, and a first formula; The second estimated state information of the UAV at the current moment is determined based on the acceleration control amount estimated at the previous moment, the second estimated state information corrected at the previous moment, and the second formula.

3. The method according to claim 2, characterized in that The determining of the acceleration control amount at the current moment based on the current state information, the deception trajectory, and the acceleration information of the drone at the current moment includes: Using the current state information as the first estimated state information of the drone that has not been updated at the current moment; Based on the unupdated first estimated state information, the deception trajectory and the acceleration information of the drone at the current moment, the acceleration control amount a at the current moment is determined in combination with the proportional differential algorithm. * : Among them, a t is the acceleration of the UAV at time t, K p is the proportional gain of the proportional-differential algorithm, is the first estimated state information at time t, is the deception trajectory at time t.

4. The method according to claim 2, characterized in that The first formula is: in, is the first estimated state information estimated at time t, is the position of the first estimated state information, is the speed of the first estimated state information; is the trajectory coordinate position of the deception trajectory at time t, a * is the acceleration control quantity, K p is the proportional gain of the proportional differential algorithm, is the velocity corresponding to the trajectory coordinate position of the deceptive trajectory at time t; The second formula is: in, is the second estimated state information estimated at time t, T is the period for obtaining UAV status information, I 2*2 is a two-order identity matrix, O 2*2 is a two-order zero matrix, is the output of the second estimated state information after correction of the inertial navigation system estimated at time t-1, is the estimated value of the acceleration of the UAV at time t-1.

5. The method according to claim 1, wherein The determining the spoofing signal value at a current moment based on the first estimated state information and the second estimated state information includes: The deception signal value at the current moment is calculated by the following formula in, is the second estimated state information estimated at time t, is the first estimated state information estimated at time t, K p is the proportional gain of the proportional derivative algorithm.

6. The method according to claim 1, characterized in that The motion trajectory information includes the current position and current speed of the drone. Accordingly, generating a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information includes: determining a coordinate interval based on the current velocity; Taking the coordinate interval as the interval between coordinate points, select multiple coordinates from the line connecting the current position of the spoofing device and the current position of the drone to obtain multiple spoofing position point coordinates; A deception trajectory is generated according to the coordinates of the multiple deception position points.

7. The method according to claim 1, characterized in that The motion trajectory information includes the current position, current speed, and target position of the UAV. Accordingly, generating a spoofing trajectory based on the current position of the spoofing device and the motion trajectory information includes: Determine the radius of the circle based on the current speed, and obtain the circle corresponding to the current position of the drone with the current position of the drone as the center of the circle; Determining the coordinates of the spoofing location point at the next moment based on the current location of the spoofing device and the coordinates of the tangent point corresponding to the straight line passing through the target location and tangent to the circle; Using the coordinates of the spoofed position at the next moment as the center of the circle, regenerate the circle corresponding to the drone's next position based on the radius; New deceptive position point coordinates are re-determined based on the circle and the target position until a preset number of deceptive position point coordinates are obtained, and a deceptive trajectory is generated according to the preset number of deceptive position point coordinates.

8. A device for determining a drone spoofing signal, characterized in that: The device comprises: An acquisition module is used to obtain the motion trajectory information and status information of the drone to be deceived; A trajectory generation module, configured to generate a deception trajectory according to the current position of the deception device and the motion trajectory information; a first determining module, configured to determine first estimated state information and second estimated state information of the drone based on the state information and the deception trajectory; a second determining module, configured to determine a spoofing signal value at a current moment based on the first estimated state information and the second estimated state information; a signal generating module, configured to generate a spoofing signal according to the spoofing signal value; The first estimated state information is an estimated state based on the UAV navigation system, and the second estimated state information is an estimated state based on the UAV inertial navigation system.

9. An electronic device, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the drone spoofing signal determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the drone spoofing signal determination method according to any one of claims 1 to 7 when executed.

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