Detection and interference method and device for unmanned aerial vehicle target

Abstract

The invention discloses a detection and interference method and device for an unmanned aerial vehicle target, and the method comprises the steps: obtaining a movement track information set of an unmanned aerial vehicle according to the collected radiation signal information of the unmanned aerial vehicle; the unmanned aerial vehicle radiation signal information comprises a radiation signal and signal acquisition time; calculating real-time position information of the unmanned aerial vehicle based on the obtained real-time radiation signal of the unmanned aerial vehicle; performing signal parameter measurement on the real-time radiation signal to obtain a signal parameter information set; the signal parameter information set comprises frequency, amplitude, phase and acquisition time; and generating and transmitting an unmanned aerial vehicle interference signal based on the motion trail information set of the unmanned aerial vehicle, the real-time position information of the unmanned aerial vehicle and the signal parameter information set.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV detection, tracking and interference, and particularly relates to a detection and interference method and device for UAV targets. Background Art

[0002] With the rapid development and wide application of UAV technology, UAVs play an important role in both civilian and military fields. However, the abuse of UAVs has also brought a series of security risks, such as privacy infringement, interference with aviation order, and threat to the safety of critical facilities. Therefore, effective monitoring and defense of UAVs have become urgent problems to be solved.

[0003] Currently, common UAV monitoring means mainly include radar monitoring, optoelectronic monitoring, etc., and the shooting-down methods of UAVs mainly include net capture, laser strike, electromagnetic interference, etc. However, these methods often have their own limitations. For example, single radar monitoring may not be able to accurately identify the type and payload of UAVs, and single electromagnetic interference may not be able to effectively act on UAVs at a long distance. Summary of the Invention

[0004] The present invention mainly solves the problem of how to effectively detect and interfere with UAV targets, and discloses a detection and interference method and device for UAV targets.

[0005] In the first aspect of the embodiments of the present invention, a detection and interference method for UAV targets is disclosed, including:

[0006] S1, obtaining a set of UAV motion trajectory information according to the collected UAV radiation signal information; the UAV radiation signal information includes radiation signals and signal acquisition time;

[0007] S2, calculating the real-time position information of the UAV based on the obtained real-time radiation signal of the UAV;

[0008] S3, measuring the signal parameters of the real-time radiation signal to obtain a set of signal parameter information; the set of signal parameter information includes frequency, amplitude, phase and acquisition time;

[0009] S4, generating and transmitting a UAV interference signal based on the set of UAV motion trajectory information, the real-time position information of the UAV and the set of signal parameter information.

[0010] The obtaining of the set of UAV motion trajectory information according to the collected UAV radiation signal information includes:

[0011] S11. At each signal acquisition time, use each sensor array to perform direction finding calculations on the UAV radiation signal information, and measure the corresponding UAV radiation signal direction; the positions of all sensors in the sensor array form a uniform linear space cross array; based on the uniform linear space cross array, construct a rectangular coordinate system; the reference sensor of the sensor array is located at the coordinate origin of the rectangular coordinate system, and other sensors are evenly distributed on the positive and negative semi-axes of the x-axis, y-axis, and z-axis of the rectangular coordinate system; the distance between adjacent two sensors is L.

[0012] S12. Use the triangulation method to calculate the UAV radiation signal directions measured by all sensor arrays at each signal acquisition time to obtain the position information at the signal acquisition time.

[0013] S13. Use the radiation signals collected by all sensor arrays to calculate the UAV target trajectory vector.

[0014] S14. Based on the UAV target trajectory vector and the position information at all signal acquisition times, construct a set of UAV motion trajectory information; the set of motion trajectory information includes a motion trajectory model and the deviation values at all signal acquisition times.

[0015] The calculation of the UAV target trajectory vector using the radiation signals collected by all sensor arrays includes:

[0016] S131. For each sensor array, measure the arrival time delay of the radiation signal received by each sensor relative to the radiation signal received by the reference sensor.

[0017] S132. Use the arrival time delay to solve for the unit direction vector k to obtain the solution value of the unit direction vector for each sensor. The solution value of the unit direction vector The expression is:

[0018]

[0019] where the arrival time delays of the radiation signals received by the sensors on the x-axis, y-axis, and z-axis relative to the radiation signal received by the reference sensor are τ x 、τ y 、τ z ; the arrival time delay is a physical quantity measured using the radiation signals received by two channels of sensors.

[0020] S133. For each combination of two sensors, solve for the corresponding target trajectory vector; the expression of the target trajectory vector is:

[0021]

[0022] Among them, the solved values of the unit direction vectors of the combination of two sensors are respectively and which are respectively the first component value, the second component value, and the third component value of the target trajectory vector ;

[0023] S134, perform the first fusion calculation on all the solved target trajectory vectors of a sensor array to obtain the first target trajectory vector of the sensor array;

[0024] S135, perform the second fusion calculation on the first target trajectory vectors of all sensor arrays to obtain the UAV target trajectory vector.

[0025] The expression of the first fusion calculation is:

[0026]

[0027] where lc i is the i-th component value of the first target trajectory vector of a sensor array, l ij is the i-th component of the j-th solved target trajectory vector of a sensor array, M is the total number of the solved target trajectory vectors of a sensor array, α i , β i , ρ i are respectively the mean value, variance value, and median value of the i-th components of all the solved target trajectory vectors of a sensor array.

[0028] The expression of the second fusion calculation is:

[0029]

[0030] where dc i is the i-th component value of the UAV target trajectory vector, lc0 i is the mean value of the i-th components of the first target trajectory vectors of all sensor arrays, lc ij is the i-th component value of the first target trajectory vector of the j-th sensor array, N is the number of sensor arrays, and lcf i is the variance value of the i-th components of the first target trajectory vectors of all sensor arrays.

[0031] Based on the UAV target trajectory vector and the position information at all signal acquisition times, construct the motion trajectory information set of the UAV, including:

[0032] S141. Use the position information at the earliest signal acquisition time and the UAV target trajectory vector to construct a motion trajectory model;

[0033] The expression of the motion trajectory model is:

[0034] x(t) = x0 + v·dc1,

[0035] y(t) = y0 + v·dc2,

[0036] z(t) = z0 + v·dc3,

[0037] where, [x(t), y(t), z(t)] is the estimated target position at time t, [x0, y0, z0] is the position information at the earliest signal acquisition time, and v is the estimated speed of the UAV;

[0038] S142. Use the motion trajectory model to calculate for each signal acquisition time respectively to obtain the estimated target position at each signal acquisition time;

[0039] S143. Subtract the position information from the estimated target position at each signal acquisition time to obtain the deviation value at each signal acquisition time.

[0040] Generating and transmitting a UAV interference signal based on the UAV motion trajectory information set, the UAV real-time position information, and the signal parameter information set includes:

[0041] S41. Based on the motion trajectory model, calculate the acquisition time of the signal parameter information set to obtain the estimated position at the acquisition time;

[0042] S42. Calculate the real-time position deviation value between the estimated position at the acquisition time and the UAV real-time position information;

[0043] S43. Perform statistical estimation processing on the deviation values of all signal acquisition times in the motion trajectory information set and the real-time position deviation value to obtain a signal parameter deviation amount set; the signal parameter deviation amount set includes an amplitude deviation amount, a phase deviation amount, and a frequency deviation amount;

[0044] S44. Generate a UAV interference signal based on the signal parameter deviation amount set and the signal parameter information set;

[0045] S45. Transmit the UAV interference signal in the direction of the signal radiated by the UAV.

[0046] The expression of the statistical estimation processing is:

[0047]

[0048]

[0049] Among them, Ap, fp, and θp are the amplitude deviation, frequency deviation, and phase deviation respectively, is the real-time position deviation value, ω0, ω1, ω2 are preset weighting coefficients, NT is the total number of signal acquisition times, p0 is the mean value of the deviation values of all signal acquisition times, cp0 is the standard deviation of the deviation values of all signal acquisition times, p k is the deviation value at the k-th signal acquisition time, p max is the maximum value of the deviation values of all signal acquisition times.

[0050] In the second aspect of the embodiments of the present invention, a detection and interference device for an unmanned aerial vehicle (UAV) target is disclosed. The device includes:

[0051] A memory storing executable program code;

[0052] A processor coupled to the memory;

[0053] The processor calls the executable program code stored in the memory to execute the detection and interference method for the UAV target.

[0054] In the third aspect of the embodiments of the present invention, a computer-readable storage medium is disclosed. The computer-readable storage medium stores computer instructions, which are used to execute the detection and interference method for the UAV target when called by a computer.

[0055] In the fourth aspect of the embodiments of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the detection and interference method for the UAV target.

[0056] The beneficial effects of the present invention are as follows:

[0057] By using the sensor array of a uniform linear space cross array to perform direction finding calculations on the UAV radiation signal and combining the triangulation method, the present invention can accurately obtain the set of UAV motion trajectory information. This method can accurately measure the position information of the UAV at different signal acquisition times and calculate the UAV target trajectory vector, thereby realizing high-precision detection of the UAV motion trajectory and providing reliable target position information for subsequent interference operations.

[0058] The present invention has strong real-time performance. By collecting the radiation signals of drones in real time, the real-time position information of the drones can be quickly calculated. Combining with the signal parameter information set, it can generate and transmit drone interference signals in real time. This method can respond in a timely manner to the dynamic changes of drones, ensuring that the interference signals are always targeted at the current state of the drones, improving the timeliness and effectiveness of interference, and effectively dealing with fast-moving drone targets.

[0059] Through the comprehensive analysis of the motion trajectory information set, the real-time position information of the drones, and the signal parameter information set, the present invention calculates the signal parameter deviation set, and then generates interference signals that highly match the radiation signals of the drones. Such targeted interference signals can more effectively interfere with the normal communication and control signals of the drones, reduce the working efficiency of the drones, and improve the success rate of interfering with the drones. Brief Description of the Drawings

[0060] Figure 1 It is a flowchart of the implementation of the method of the present invention. Detailed Embodiment

[0061] To better understand the content of the present invention, an embodiment is given here.

[0062] Figure 1 It is a flowchart of the implementation of the method of the present invention.

[0063] In the first aspect of the embodiment of the present invention, a method for detecting and interfering with drone targets is disclosed, including:

[0064] S1. According to the collected drone radiation signal information, obtain the motion trajectory information set of the drones; the drone radiation signal information includes radiation signals and signal acquisition times;

[0065] S2. Based on the real-time radiation signals of the obtained drones, calculate the real-time position information of the drones;

[0066] S3. Measure the signal parameters of the real-time radiation signals to obtain the signal parameter information set; the signal parameter information set includes frequency, amplitude, phase, and acquisition time;

[0067] S4. Based on the motion trajectory information set of the drones, the real-time position information of the drones, and the signal parameter information set, generate and transmit drone interference signals.

[0068] The method of the present invention can dynamically adjust the emission direction and parameters of the interference signal according to the real-time position and movement trajectory of the UAV, so that it can adapt to UAV targets with different flight postures and flight paths. At the same time, through the statistical estimation process of the signal parameter deviation set, it can better cope with the changes of UAV signal parameters, enhance the flexibility and adaptability of the interference system, and make it have stronger anti-interference ability in complex environments.

[0069] Based on the collected UAV radiation signal information, obtain the set of UAV movement trajectory information, including:

[0070] S11. At each signal acquisition time, use each sensor array to perform direction finding calculation on the UAV radiation signal information, and measure the corresponding UAV radiation signal direction; the positions of all sensors of the sensor array form a uniform linear space cross array; based on the uniform linear space cross array, construct a rectangular coordinate system; the reference sensor is located at the coordinate origin of the rectangular coordinate system; other sensors are evenly distributed on the positive and negative semi-axes of the x-axis, y-axis, and z-axis of the rectangular coordinate system; the distance between adjacent two sensors is L.

[0071] S12. Use the triangulation method to calculate the UAV radiation signal directions measured by all sensor arrays at each signal acquisition time to obtain the position information at the signal acquisition time.

[0072] S13. Use the radiation signals collected by all sensor arrays to calculate the UAV target trajectory vector.

[0073] S14. Based on the UAV target trajectory vector and the position information at all signal acquisition times, construct the set of UAV movement trajectory information; the set of movement trajectory information includes a movement trajectory model and the deviation values at all signal acquisition times.

[0074] Based on the acquired real-time radiation signal of the UAV, calculate the real-time position information of the UAV, including:

[0075] Use each sensor array to collect the real-time radiation signal of the UAV.

[0076] Use each sensor array to perform direction finding calculation on the real-time radiation signal information of the UAV, and measure the corresponding UAV radiation signal direction. This process can refer to S11.

[0077] Use the triangulation method to calculate the UAV radiation signal directions measured by all sensor arrays to obtain the real-time position information of the UAV.

[0078] For the direction finding calculation, the interferometer direction finding algorithm can be used.

[0079] For the triangulation method, the generalized azimuth method, the maximum likelihood localization algorithm, etc. can be adopted.

[0080] For the measurement of the signal parameters, the signal feature extraction methods in communication reconnaissance can be adopted, including the carrier frequency measurement method, the level measurement method, and the phase measurement method.

[0081] For the radiation signals acquired by using all the sensor arrays, calculating the UAV target trajectory vector includes:

[0082] S131. For each sensor array, measuring the arrival time delay amount of the radiation signal received by each sensor relative to the radiation signal received by the reference sensor;

[0083] S132. Using the arrival time delay amount to solve for the unit direction vector k to obtain the solution value of the unit direction vector of each sensor The solution value of the unit direction vector The expression is:

[0084]

[0085] where the arrival time delay amounts (Time Delay of Arriving, TDOA) of the radiation signals of the sensors on the x-axis, y-axis, and z-axis relative to the radiation signal of the reference sensor are τ x 、τ y 、τ z , and the arrival time delay amount is a physical quantity measured by using the radiation signals of two sensors;

[0086] S133. For each combination of two sensors, solving for the corresponding target trajectory vector; the target trajectory vector The expression is:

[0087]

[0088] where the solution values of the unit direction vectors of the combination of two sensors are respectively and are respectively the first component value, the second component value, and the third component value of the target trajectory vector ;

[0089] S134. Performing a first fusion calculation on all the solved target trajectory vectors of a sensor array to obtain the first target trajectory vector of the sensor array;

[0090] S135. Performing a second fusion calculation on the first target trajectory vectors of all the sensor arrays to obtain the UAV target trajectory vector;

[0091] The expression of the first fusion calculation is as follows:

[0092]

[0093] where lc i is the i-th component value of the first target trajectory vector of a sensor array, l ij is the i-th component of the j-th target trajectory vector obtained by solving for a sensor array, M is the total number of target trajectory vectors obtained by solving for a sensor array, α i , β i , ρ i are the mean, variance, and median values of the i-th components of all target trajectory vectors obtained by solving for a sensor array, respectively.

[0094] The expression of the second fusion calculation is as follows:

[0095]

[0096] where dc i is the i-th component value of the UAV target trajectory vector, lc0 i is the mean of the i-th components of the first target trajectory vectors of all sensor arrays, lc ij is the i-th component value of the first target trajectory vector of the j-th sensor array, N is the number of sensor arrays, lcf i is the variance value of the i-th component values of the first target trajectory vectors of all sensor arrays.

[0097] Based on the UAV target trajectory vector and the position information of all signal acquisition times, a set of UAV motion trajectory information is constructed, including:

[0098] S141, using the position information of the earliest signal acquisition time and the UAV target trajectory vector to construct a motion trajectory model;

[0099] The expression of the motion trajectory model is as follows:

[0100] x(t) = x0 + v·dc1,

[0101] y(t) = y0 + v·dc2,

[0102] z(t) = z0 + v·dc3,

[0103] Among them, [x(t), y(t), z(t)] is the estimated value of the target position at time t, [x0, y0, z0] is the position information at the earliest signal acquisition time, and v is the estimated value of the UAV's speed, which is obtained by taking the difference between the position information of adjacent signal acquisition times to get the moving distance, and then dividing the moving distance by the time interval between adjacent signal acquisition times;

[0104] S142, using the motion trajectory model, calculate for each signal acquisition time respectively to obtain the estimated value of the target position at each signal acquisition time;

[0105] S143, subtract the position information from the estimated value of the target position at each signal acquisition time to obtain the deviation value at each signal acquisition time;

[0106] Generating and transmitting a UAV interference signal based on the UAV's motion trajectory information set, the UAV's real-time position information, and the signal parameter information set includes:

[0107] S41, based on the motion trajectory model, calculate the acquisition time of the signal parameter information set to obtain the estimated value of the position at the acquisition time;

[0108] S42, calculate the real-time position deviation value between the estimated value of the position at the acquisition time and the UAV's real-time position information; the real-time position deviation value is obtained by subtracting the UAV's real-time position information from the estimated value of the position at the acquisition time;

[0109] S43, perform statistical estimation processing on the deviation values and real-time position deviation values of all signal acquisition times in the motion trajectory information set to obtain a signal parameter deviation amount set; the signal parameter deviation amount set includes an amplitude deviation amount, a phase deviation amount, and a frequency deviation amount;

[0110] S44, generate a UAV interference signal based on the signal parameter deviation amount set and the signal parameter information set;

[0111] S45, transmit the UAV interference signal in the direction of the signal radiated by the UAV.

[0112] The expression of the statistical estimation processing is:

[0113]

[0114] Among them, Ap, fp, and θp are the amplitude deviation amount, the frequency deviation amount, and the phase deviation amount respectively, is the real-time position deviation value, ω0, ω1, ω2 are preset weighting coefficients, NT is the total number of signal acquisition times, p0 is the mean value of the deviation values of all signal acquisition times, cp0 is the standard deviation of the deviation values of all signal acquisition times, pk is the deviation value of the k-th signal acquisition time, p max is the maximum value of the deviation values of all signal acquisition times.

[0115] The expression of the UAV interference signal is:

[0116] jam = (A + Ap)sin((f + fp)t + θ + θp),

[0117] where jam is the UAV interference signal, and A, f, and θ are the frequency, amplitude, and phase in the signal parameter information set, respectively.

[0118] In the second aspect of the embodiments of the present invention, a detection and interference device for UAV targets is disclosed. The device includes:

[0119] A memory storing executable program code;

[0120] A processor coupled to the memory;

[0121] The processor calls the executable program code stored in the memory to execute the detection and interference method for UAV targets.

[0122] In the third aspect of the embodiments of the present invention, a computer-readable storage medium is disclosed. The computer-readable storage medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the detection and interference method for UAV targets.

[0123] In the fourth aspect of the embodiments of the present invention, an information data processing terminal is disclosed. The information data processing terminal is used to implement the detection and interference method for UAV targets.

[0124] In the fifth aspect of the embodiments of the present invention, a detection and interference device for UAV targets is disclosed. The device is used to implement the detection and interference method for UAV targets, and includes a signal reception module, a trajectory measurement module, a parameter measurement module, and an interference signal transmission module;

[0125] The signal reception module includes a plurality of sensor arrays for collecting UAV radiation signal information;

[0126] The trajectory measurement module is used to obtain a set of UAV motion trajectory information according to the collected UAV radiation signal information; the UAV radiation signal information includes a radiation signal and a signal acquisition time; based on the acquired real-time radiation signal of the UAV, the real-time position information of the UAV is calculated;

[0127] The parameter measurement module is used to measure the signal parameters of the real-time radiation signal to obtain a set of signal parameter information; the set of signal parameter information includes frequency, amplitude, phase, and acquisition time;

[0128] The interference signal transmitting module is used to generate and transmit an unmanned aerial vehicle (UAV) interference signal based on the set of movement trajectory information of the UAV, the real-time position information of the UAV, and the set of signal parameter information.

[0129] The above are only embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A detection and interference method for UAV targets, characterized in that, Including: S1. Obtain the set of drone movement trajectory information according to the collected drone radiation signal information; The drone radiation signal information includes radiation signals and signal acquisition times; S2. Calculate the real-time position information of the drone based on the obtained real-time radiation signal of the drone; S3. Measure the signal parameters of the real-time radiation signal to obtain a set of signal parameter information; the set of signal parameter information includes frequency, amplitude, phase, and acquisition time; S4. Generate and transmit a drone interference signal based on the set of drone movement trajectory information, the real-time position information of the drone, and the set of signal parameter information.

2. The detection and interference method for UAV targets according to claim 1, characterized in that, The obtaining of the set of drone movement trajectory information according to the collected drone radiation signal information includes: S11. At each signal acquisition time, use each sensor array to perform direction finding calculations on the drone radiation signal information to measure the corresponding direction of the drone radiation signal; the positions of all sensors of the sensor array form a uniform linear space cross array; based on the uniform linear space cross array, a rectangular coordinate system is constructed; the reference sensor of the sensor array is located at the coordinate origin of the rectangular coordinate system, and other sensors are evenly distributed on the positive and negative semi-axes of the x-axis, y-axis, and z-axis of the rectangular coordinate system; the distance between adjacent two sensors is L; S12. Use the triangulation method to calculate the directions of the drone radiation signals measured by all sensor arrays at each signal acquisition time to obtain the position information at the signal acquisition time; S13. Calculate the drone target trajectory vector using the radiation signals collected by all sensor arrays; S14. Based on the drone target trajectory vector and the position information at all signal acquisition times, construct a set of drone movement trajectory information; the set of drone movement trajectory information includes a movement trajectory model and the deviation values at all signal acquisition times.

3. The detection and interference method for UAV targets according to claim 2, characterized in that, The calculating of the drone target trajectory vector using the radiation signals collected by all sensor arrays includes: S131. For each sensor array, measure the arrival time delay of the radiation signal received by each sensor relative to the radiation signal received by the reference sensor; S132, using the arrival time delay amount, solve for the unit direction vector k to obtain the solution value of the unit direction vector for each sensor The solution value of the unit direction vector has the following expression: Among them, the arrival time delay amounts of the radiation signals received by the sensors on the x-axis, y-axis, and z-axis relative to the radiation signal received by the reference sensor are τ x , τ y , τ z , and the arrival time delay amount is a physical quantity measured using the radiation signals received by the two-way sensors; S133. For each combination of two sensors, solve to obtain the corresponding target trajectory vector; the expression of the target trajectory vector is as follows: Among them, the solution values of the unit direction vectors of the combination of the two sensors are respectively and are respectively the first component value, the second component value, and the third component value of the target trajectory vector ; S134. Perform a first fusion calculation on all the obtained target trajectory vectors of one sensor array to obtain the first target trajectory vector of the sensor array; S135. Perform a second fusion calculation on the first target trajectory vectors of all sensor arrays to obtain the drone target trajectory vector.

4. The detection and interference method for UAV targets according to claim 3, characterized in that The expression of the first fusion calculation is: where, lc i is the i-th component value of the first target trajectory vector of a sensor array, l ij is the i-th component of the j-th target trajectory vector obtained by solving a sensor array, M is the total number of target trajectory vectors obtained by solving a sensor array, α i , β i , ρ i are respectively the mean, variance, and median value of the i-th components of all target trajectory vectors obtained by solving a sensor array; The expression of the second fusion calculation is: where, dc i is the i-th component value of the target trajectory vector of the UAV, lc0 i is the mean of the i-th component of the first target trajectory vector of all sensor arrays, lc ij is the i-th component value of the first target trajectory vector of the j-th sensor array, N is the number of sensor arrays, lcf i is the variance value of the i-th component value of the first target trajectory vector of all sensor arrays.

5. The detection and interference method for UAV targets according to claim 2, characterized in that The constructing of the set of drone movement trajectory information based on the drone target trajectory vector and the position information at all signal acquisition times includes: S141. Use the position information at the earliest signal acquisition time and the drone target trajectory vector to construct a movement trajectory model; The expression of the movement trajectory model is: x(t) = x0 + v·dc1, y(t) = y0 + v·dc2, z(t) = z0 + v·dc3, Among them, [x(t), y(t), z(t)] is the estimated value of the target position at time t, [x0, y0, z0] is the position information at the earliest signal acquisition time, and v is the estimated value of the UAV's speed; S142. Using the motion trajectory model, calculate for each signal acquisition time to obtain the estimated value of the target position at each signal acquisition time; S143. Subtract the position information from the estimated value of the target position at each signal acquisition time to obtain the deviation value at each signal acquisition time.

6. The detection and interference method for UAV targets according to claim 1, characterized in that Generating and transmitting a UAV interference signal based on the UAV's motion trajectory information set, the UAV's real-time position information, and the signal parameter information set includes: S41. Based on the motion trajectory model, calculate the acquisition time of the signal parameter information set to obtain the estimated value of the position at the acquisition time; S42. Calculate the real-time position deviation value between the estimated value of the position at the acquisition time and the UAV's real-time position information; S43. Perform statistical estimation processing on the deviation values at all signal acquisition times of the motion trajectory information set and the real-time position deviation value to obtain a signal parameter deviation amount set; the signal parameter deviation amount set includes an amplitude deviation amount, a phase deviation amount, and a frequency deviation amount; S44. Generate a UAV interference signal based on the signal parameter deviation amount set and the signal parameter information set; S45. Transmit the UAV interference signal in the direction of the UAV's radiation signal.

7. The detection and interference method for UAV targets according to claim 6, characterized in that The expression of the statistical estimation processing is: Among them, Ap, fp, and are the amplitude deviation amount, the frequency deviation amount, and the phase deviation amount respectively, is the real-time position deviation value, ω0, ω1, ω2 are preset weighting coefficients, NT is the total number of signal acquisition times, p0 is the mean value of the deviation values of all signal acquisition times, cp0 is the standard deviation of the deviation values of all signal acquisition times, p k is the deviation value at the k-th signal acquisition time, p max is the maximum value of the deviation values of all signal acquisition times.

8. A detection and interference device for UAV targets, characterized in that, The device includes: A memory storing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory and executes the method for detecting and interfering with a UAV target according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, which are used to execute the method for detecting and interfering with a UAV target according to any one of claims 1 to 7 when called by a computer.

10. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the method for detecting and interfering with a UAV target according to any one of claims 1 to 7.

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