An unmanned aerial vehicle countermeasure method and system based on acoustic wave nonlinear MEMS resonance

Abstract

The application discloses an unmanned aerial vehicle countermeasure method and system based on acoustic wave nonlinear MEMS resonance, and belongs to the technical field of unmanned aerial vehicle countermeasures. a The application comprises the following steps: sweeping frequency to test the resonance frequency f of the MEMS device of the unmanned aerial vehicle; calculating the 1 / k times frequency frequency value of the resonance frequency, and performing nonlinear resonance test on the unmanned aerial vehicle; determining the k value that makes the output response of the MEMS device maximum according to the frequency response data of the MEMS device in the unmanned aerial vehicle, and recording the k value as k0; the corresponding acoustic wave frequency at this time is the optimal nonlinear resonance excitation frequency; and countermeasuring the unmanned aerial vehicle based on the optimal nonlinear resonance excitation frequency. The application effectively reduces the required transmission frequency by using the 1 / k times frequency acoustic wave to excite the nonlinear resonance of the MEMS sensor, avoids the problem that the action distance is limited due to the serious high-frequency attenuation in the traditional ultrasonic countermeasure technology, significantly improves the countermeasure range, and is more suitable for long-distance black flight unmanned aerial vehicle countermeasures.

Description

Technical Field

[0001] This invention belongs to the field of drone countermeasure technology, and particularly relates to a drone countermeasure method and system based on acoustic nonlinear MEMS resonance. Background Technology

[0002] In recent years, the phenomenon of unauthorized drone flights has become increasingly frequent, posing a serious threat to public safety. Drones that enter airport airspace, near critical infrastructure, or in densely populated areas without permission may cause major accidents such as aircraft collisions, communication interference, and privacy breaches. Therefore, non-contact countermeasures technology based on the principle of acoustic resonance has attracted attention due to its controllability and safety, but its practical application still faces technical bottlenecks.

[0003] Current acoustic countermeasures primarily rely on experiments to determine the acoustic resonance frequencies of key components of the target drone (such as MEMS sensors), typically concentrated in the ultrasonic band above 20kHz. However, ultrasound has significant drawbacks: firstly, high-frequency sound waves attenuate severely in air, with an effective range usually less than 50 meters, and the attenuation worsens beyond 15 meters, making it difficult to counter distant targets; secondly, ultrasound is highly directional, easily affected by obstacles or airflow disturbances; and thirdly, the equipment requires high-precision frequency tracking capabilities, resulting in high hardware costs. Theoretically, if the countermeasure sound wave frequency could be reduced to the audible range (below 20kHz), the longer propagation distance and stronger diffraction ability of low-frequency sound waves could significantly improve the countermeasure coverage. However, experiments show that directly reducing the frequency leads to a significant weakening of the resonance effect, or even complete failure. This contradiction stems from the complex low-frequency vibration modes and low energy transfer efficiency of key drone components, and the ease with which low-frequency sound waves can be superimposed with environmental noise (such as traffic and industrial equipment). Therefore, finding an effective frequency close to the resonant frequency in the sub-ultrasonic frequency band to make it suitable for far-field suppression of drones has become the key to breaking through the existing technological bottleneck.

[0004] Current methods for obtaining resonant frequencies based on laboratory conditions suffer from a disconnect between the experimental and real-world scenarios. In experiments, resonant frequencies are typically measured using precision instruments within a 10cm distance. However, in actual countermeasure scenarios, the distance between the drone and the equipment often exceeds 15 meters. At this distance, sound wave propagation loss, changes in ambient temperature and humidity, and multipath effects significantly alter the frequency response characteristics, rendering the laboratory data invalid. Furthermore, directly scanning the audible frequency band (e.g., 1kHz–15kHz) requires a lengthy scanning process, which not only fails to match the resonant frequency but may also damage the human auditory system.

[0005] The determination of current acoustic resonant frequencies relies heavily on ultrasonic frequency sweep experiments under laboratory conditions. In a controlled environment, researchers can accurately identify the resonant frequencies of key components such as drone MEMS devices by scanning frequencies above 20kHz using sophisticated equipment. Considering the need to find effective frequencies close to the resonant frequency in the lower ultrasonic frequency band, direct frequency sweep testing in this band is not feasible. First, the physical conditions in the laboratory differ significantly from those in real-world scenarios: test results at a distance of 10cm in the laboratory cannot reflect the sound wave propagation characteristics at distances of 15 meters or more, causing the resonant frequency determined in the laboratory to fail in the far field. Second, low-frequency frequency sweeping faces technical bottlenecks: directly attempting low-frequency audible sound band sweeping in real-world scenarios requires extremely high sound pressure levels to overcome environmental noise interference, and the excessively long wavelength leads to severe sound wave energy diffusion. Furthermore, prolonged exposure to high-intensity low-frequency sound waves may cause auditory fatigue or psychological discomfort. Summary of the Invention

[0006] To address the dual challenges of severe high-frequency attenuation and poor low-frequency performance in existing acoustic countermeasures technologies, this invention proposes a UAV countermeasures method and system based on acoustic nonlinear MEMS resonance.

[0007] The technical solution adopted in this invention is as follows:

[0008] In a first aspect, the present invention provides a method for countering unmanned aerial vehicles (UAVs) based on acoustic nonlinear MEMS resonance, characterized by comprising the following steps:

[0009] (1) Frequency sweep test of the resonant frequency f of the UAV MEMS device a ;

[0010] (2) Calculate the 1 / k harmonic frequency of the resonance frequency and perform a nonlinear resonance test on the UAV. Based on the frequency response data of the MEMS devices in the UAV, determine the k value that maximizes the output response of the MEMS devices, denoted as k0. The corresponding acoustic frequency at this time is... This is the optimal nonlinear resonance excitation frequency;

[0011] (3) Countering UAVs based on the optimal nonlinear resonant excitation frequency.

[0012] Furthermore, a database of different UAV models was established to record the resonant frequency f of each UAV model. a And its optimal nonlinear resonant excitation frequency.

[0013] Furthermore, in step (3), the target UAV model is determined based on image recognition technology, and the optimal nonlinear resonant excitation frequency is obtained based on the lookup table method.

[0014] Furthermore, in step (1), the frequency sweep test range is 20kHz to 40kHz, and the distance between the UAV MEMS device and the acoustic signal generator is 5-20cm.

[0015] Furthermore, in step (1), the resonant frequency f a It refers to the acoustic frequency corresponding to the point where the output response amplitude of the drone's MEMS device is at its maximum.

[0016] Furthermore, step (2) includes:

[0017] (2.1) Based on the measured resonant frequency f a Calculate its 1 / k harmonic frequency value, where k = 2 to 5, i.e., f k =

[0018] f a / k;

[0019] (2.2) Use f in sequence k A frequency-sensitive acoustic signal is injected into a MEMS device, and its frequency response is measured. The amplitude of the output signal at each frequency is recorded.

[0020] (2.3) Analyze the frequency response data to determine the k value that maximizes the output response of the MEMS device, denoted as k0, and the corresponding acoustic frequency. This is the optimal nonlinear resonant excitation frequency.

[0021] Furthermore, in step (3), the acoustic wave emitting device is used to counter the UAV based on the optimal nonlinear resonant excitation frequency. The acoustic wave emitting device includes:

[0022] The power module is used to provide stable power to the entire acoustic wave emitting device;

[0023] The signal generation module is used to generate frequency-adjustable sound wave signals;

[0024] The audio amplifier module is used to amplify the sound wave signal output by the signal generation module and increase the sound wave intensity.

[0025] The speaker array module is used to convert the electrical signal output from the audio amplifier module into high-intensity sound waves and transmit them directionally to the target drone.

[0026] Furthermore, the distance between the counter-drone and the acoustic wave transmitter exceeded 10m.

[0027] Secondly, this invention proposes a UAV countermeasure system based on acoustic wave nonlinear MEMS resonance, which is used to implement the aforementioned UAV countermeasure method based on acoustic wave nonlinear MEMS resonance.

[0028] The beneficial effects of this invention are:

[0029] This invention overcomes the technical limitations of traditional linear acoustic frameworks by implementing it in two phases: First, in a laboratory environment, high-frequency ultrasonic frequency sweeping technology (20kHz–100kHz) is used to accurately calculate the inherent resonant frequencies of key components in the target UAV MEMS sensor. Second, based on nonlinear acoustic theory, the subharmonic frequencies (such as 1 / k harmonics) of the resonant frequencies are precisely calculated to select the nonlinear resonant excitation frequency with optimal energy transfer efficiency. This technology induces phase disturbances and harmonic distortion in the output signal of the target MEMS device by exciting its nonlinear vibration modes.

[0030] This invention utilizes 1 / k harmonic sound waves to excite the nonlinear resonance of a MEMS sensor, effectively reducing the required transmission frequency and avoiding the problem of limited effective range caused by severe high-frequency attenuation in traditional ultrasonic countermeasures technology. This significantly improves the countermeasure range and makes it more suitable for countering long-range unauthorized drones. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating a method for countering drones based on acoustic nonlinear MEMS resonance.

[0032] Figure 2 This is a schematic diagram of the structure of a sound wave emitting device;

[0033] Figure 3 This is a flowchart for testing the optimal nonlinear resonant excitation frequency of MEMS devices in a drone;

[0034] Figure 4 This is the Z-axis output result of the gyroscope when testing the ultrasonic resonant frequency of a certain type of UAV in this embodiment;

[0035] Figure 5 yes Figure 4 A magnified view of a portion of the image;

[0036] Figure 6 This is the Z-axis output result of the gyroscope before and after manually adjusting the gyroscope in this embodiment;

[0037] Figure 7 The results are simulations of attenuation at a sound wave frequency of 8.575kHz.

[0038] Figure 8 The results are the attenuation simulation results when the sound wave frequency is 25.725kHz. Detailed Implementation

[0039] The present invention will be further described and illustrated below with reference to specific embodiments. The embodiments described are merely examples of the content of this disclosure and do not limit the scope of the invention. The technical features of each embodiment in the present invention can be combined accordingly, provided that there is no mutual conflict.

[0040] This invention addresses the threat to public safety posed by the irregular flight of low-speed, small unmanned aerial vehicles (UAVs). It proposes a UAV countermeasure method based on acoustic nonlinear MEMS resonance. This method induces nonlinear resonance in the MEMS devices of the target UAV through acoustic excitation, causing severe distortion of its output signal. This leads to incorrect decisions by the flight control system, ultimately resulting in the UAV losing control, making a forced landing, or deviating from its flight path. This method effectively counters the malicious flight behavior of single or swarm UAVs.

[0041] like Figure 1 As shown, the implementation process of this invention mainly includes the following steps:

[0042] S1, frequency sweep test of the resonant frequency f of the drone MEMS device. a ;

[0043] S2, calculate the 1 / k harmonic frequency of the resonance frequency and perform a nonlinear resonance test on the UAV. Based on the frequency response data of the MEMS devices in the UAV, determine the k value that maximizes the output response of the MEMS devices, denoted as k0, at which point the corresponding acoustic frequency is... This is the optimal nonlinear resonance excitation frequency;

[0044] S3, based on the optimal nonlinear resonant excitation frequency to counter drones.

[0045] In one specific embodiment of the present invention, the resonant frequency f of the MEMS device of the UAV is measured by frequency sweep testing. a One possible implementation process is as follows:

[0046] S1.1: Use a signal generator to generate an acoustic wave signal with a frequency range of 20kHz to 40kHz, and transmit the swept-frequency acoustic wave signal to the MEMS devices (such as gyroscopes, accelerometers, etc.) of the target UAV through a speaker.

[0047] S1.2: By detecting the output response of the UAV MEMS devices, recording the amplitude of the output signal at different frequencies, and determining the frequency corresponding to the maximum output amplitude as the resonant frequency f. a That is, the sound wave frequency corresponding to the maximum output response.

[0048] In one specific embodiment of the present invention, an optional process for determining the optimal nonlinear resonant excitation frequency is as follows: Figure 3 As shown, specifically:

[0049] S2.1, based on the measured resonant frequency f a Calculate its 1 / k harmonic frequency value, where k = 2 to 5, i.e., f k =

[0050] f a / k;

[0051] S2.2, use f in sequence k A frequency-sensitive acoustic signal is injected into a MEMS device, and its frequency response is measured. The amplitude of the output signal at each frequency is recorded.

[0052] S2.3, Analyze the frequency response data to determine the k value that maximizes the output response of the MEMS device, denoted as k0, at which point the corresponding acoustic frequency is... This is the optimal nonlinear resonant excitation frequency.

[0053] In one specific embodiment of the present invention, a sound wave emitting device is used to counter unmanned aerial vehicles (UAVs) based on an optimal nonlinear resonant excitation frequency, such as... Figure 2 As shown, the sound wave emitting device includes:

[0054] The power module is used to provide stable power to the entire acoustic wave emitting device;

[0055] The signal generation module is used to generate frequency-adjustable sound wave signals;

[0056] The audio amplifier module is used to amplify the sound wave signal output by the signal generation module and increase the sound wave intensity.

[0057] The speaker array module is used to convert the electrical signal output from the audio amplifier module into high-intensity sound waves and transmit them directionally to the target drone.

[0058] Those skilled in the art can record the resonant frequencies f of various UAV models by constructing a database of different UAV models. a The optimal nonlinear resonant excitation frequency is determined. When countering a target UAV, the target UAV model is determined based on image recognition technology, and the optimal nonlinear resonant excitation frequency is obtained based on a lookup table. For UAV models that are not found in the lookup table, a preset typical MEMS resonant frequency (such as above 20kHz) is used directly, and the UAV database is expanded in a timely manner.

[0059] Aim the acoustic wave transmitter at the target drone, ensuring the sound waves effectively cover its MEMS sensor area. Adjust the signal generation module to the optimal nonlinear resonant excitation frequency of the target drone model, activate the audio amplifier module to enhance the sound wave intensity, and then direct the sound wave towards the target drone through the speaker array module. This causes the MEMS devices to enter a nonlinear resonant state, resulting in severe distortion of their output signal, thereby interfering with the drone's stable control and achieving the countermeasure effect.

[0060] The principle of countering drones based on the optimal nonlinear resonant excitation frequency is as follows:

[0061] Sound waves are a type of mechanical wave that propagate through the vibration of a medium (such as air, water, or solids). They can be described by the wave equation. When the frequency of an external sound wave signal is the same as the natural frequency of the system, the object will resonate; this phenomenon is called the acoustic resonance effect. Acoustic resonance vulnerabilities in MEMS devices refer to the vulnerability of sensors and actuators in MEMS structures to mechanical resonance interference induced by sound waves due to their micromechanical structures, leading to sensing or execution abnormalities. MEMS devices typically contain tiny mechanical structures, such as vibrating beams or pendulums, which are highly sensitive to sound wave vibrations. When the frequency of a sound wave is close to the natural frequency of these structures, it can cause excessive vibration of the internal mechanical structures of the MEMS device, thus affecting the measurement results of the sensor or the execution results of the actuator.

[0062] When acoustic resonance occurs, the MEMS device is introduced with an unexpected response. When the unexpected acoustic signal is strong enough, the resonance of the MEMS device will exhibit nonlinearity, and the received signal will be:

[0063]

[0064] That is, the received signal includes a fundamental frequency of f and a harmonic signal with a frequency of kf. Therefore, when transmitting the optimal nonlinear resonant excitation frequency to the UAV, it serves as the fundamental frequency. The nonlinear resonance of the MEMS sensor is excited based on nonlinear acoustic theory, thereby generating a frequency of The harmonic signal can theoretically achieve an effect similar to the resonant frequency.

[0065] To verify the effectiveness of this invention, a certain model of drone was tested. Its MEMS device was a gyroscope. Frequency sweep testing revealed that the resonant frequency in the ultrasonic band was 25.725 kHz. Figure 4 The image shows the Z-axis output of the gyroscope; the result after magnification is as follows. Figure 5 As shown, the horizontal axis represents time. The output of the gyroscope was compared before and after manual adjustment. Figure 6 As shown, the fluctuation in the gyroscope's output signal at 25.725kHz is not due to human touch, but rather to acoustic resonance. Further calculation of the 1 / k octave frequency and nonlinear resonance testing of the UAV yielded the optimal nonlinear resonance excitation frequency. It is 8.575kHz.

[0066] The relationship between the sound wave attenuation coefficient α and the frequency f under different media and conditions: α∝f nThe exponent n in the equation will vary. In air, sound attenuation is mainly determined by classical absorption (viscosity and thermal conduction) and molecular relaxation absorption (excitation of vibrational energy levels in oxygen and nitrogen). Simulation software tests show that at 50% humidity, 20 degrees Celsius, and 1 standard atmosphere, when the sound frequency is 8.575 kHz, the attenuation is 11.9 dB / 100 m. Figure 7 As shown, when the sound wave frequency is 25.725kHz, its attenuation is 76.2dB / 100m, as... Figure 8 As shown.

[0067] The test results above show that, under the same transmission power, 8.575kHz can cause the gyroscope output amplitude to be about 1, while 25.725kHz can cause the gyroscope output amplitude to be about 3. Therefore, the energy of the 8.575kHz sound wave needs to be increased by 9 times to make its output amplitude comparable to that of 25.725kHz.

[0068] It can be calculated that when the propagation distance is greater than 14.84m, the attenuation of the 25.725kHz sound wave will be more than 9 times that of the 8.575kHz sound wave. Therefore, in long-distance countermeasure scenarios, using the 8.575kHz sound wave can achieve a more effective countermeasure effect.

[0069] Based on the same inventive concept, this embodiment also provides a UAV countermeasure system based on acoustic nonlinear MEMS resonance, the system comprising:

[0070] The resonant frequency test module is used for frequency sweep testing of the resonant frequency f of UAV MEMS devices. a ;

[0071] The optimal nonlinear resonant excitation frequency test module is used to calculate the 1 / k harmonic frequency of the resonant frequency and perform nonlinear resonant tests on the UAV. Based on the frequency response data of the MEMS devices in the UAV, it determines the k value that maximizes the output response of the MEMS devices, denoted as k0, at which point the corresponding acoustic frequency is... This is the optimal nonlinear resonance excitation frequency; the preferred value of k is 2 to 5.

[0072] Acoustic wave emission module, which is used to counter drones based on the optimal nonlinear resonant excitation frequency.

[0073] For the system embodiments, since they basically correspond to the method embodiments, relevant details can be found in the descriptions of the method embodiments; the implementation methods of the remaining modules will not be repeated here. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the present invention according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0074] The system embodiments of the present invention can be applied to any device with data processing capabilities, such as a computer or other similar device. The system embodiments can be implemented in software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of any data processing device loading the corresponding computer program instructions from non-volatile memory into memory for execution.

[0075] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. Those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for countering unmanned aerial vehicles (UAVs) based on acoustic nonlinear MEMS resonance, characterized in that, Includes the following steps: (1) Frequency sweep test of the resonant frequency of the UAV MEMS device Resonance frequency It refers to the acoustic frequency corresponding to the maximum output response amplitude of the drone's MEMS device. (2) Calculate the resonant frequency The frequency of the frequency doubling was determined, and a nonlinear resonance test was performed on the UAV. Based on the frequency response data of the MEMS devices in the UAV, the value that maximizes the output response of the MEMS devices was determined. Value, denoted as The corresponding sound wave frequency at this time This is the optimal nonlinear resonant excitation frequency; Step (2) includes: (2.1) Based on the measured resonance frequency Calculate its The harmonic frequency value, where k = 2~5, i.e. ; (2.2) Use in sequence A frequency-sensitive acoustic signal is injected into a MEMS device, and its frequency response is measured. The amplitude of the output signal at each frequency is recorded. (2.3) Analyze the frequency response data to determine the frequency response that maximizes the output response of the MEMS device. Value, denoted as The corresponding sound wave frequency at this time This is the optimal nonlinear resonant excitation frequency; (3) Countering UAVs based on the optimal nonlinear resonant excitation frequency.

2. The UAV countermeasure method based on acoustic nonlinear MEMS resonance according to claim 1, characterized in that, Establish a database of different drone models and record the resonant frequencies of each model. And its optimal nonlinear resonant excitation frequency.

3. The UAV countermeasure method based on acoustic nonlinear MEMS resonance according to claim 2, characterized in that, In step (3), the target UAV model is determined based on image recognition technology, and the optimal nonlinear resonant excitation frequency is obtained based on the lookup table method.

4. The UAV countermeasure method based on acoustic nonlinear MEMS resonance according to claim 1, characterized in that, In step (1), the frequency sweep test range is 20kHz ~ 40kHz, and the distance between the UAV MEMS device and the acoustic signal generator is 5-20 cm.

5. The UAV countermeasure method based on acoustic nonlinear MEMS resonance according to claim 1, characterized in that, In step (3), the acoustic wave emitting device is used to counter the UAV based on the optimal nonlinear resonant excitation frequency. The acoustic wave emitting device includes: The power module is used to provide stable power to the entire acoustic wave emitting device; The signal generation module is used to generate frequency-adjustable sound wave signals; The audio amplifier module is used to amplify the sound wave signal output by the signal generation module and increase the sound wave intensity. The speaker array module is used to convert the electrical signal output from the audio amplifier module into high-intensity sound waves and transmit them directionally to the target drone.

6. The UAV countermeasure method based on acoustic nonlinear MEMS resonance according to claim 1, characterized in that, The drone to be countered was more than 10 meters away from the acoustic transmitter.

7. A drone countermeasure system based on acoustic wave nonlinear MEMS resonance, used to implement the drone countermeasure method of claim 1, characterized in that, The system includes: The resonant frequency test module is used for frequency sweep testing of the resonant frequencies of MEMS devices in drones. ; The optimal nonlinear resonant excitation frequency test module is used to calculate the resonant frequency. The frequency of the frequency doubling was determined, and a nonlinear resonance test was performed on the UAV. Based on the frequency response data of the MEMS devices in the UAV, the value that maximizes the output response of the MEMS devices was determined. Value, denoted as The corresponding sound wave frequency at this time This is the optimal nonlinear resonant excitation frequency; Acoustic wave emission module, which is used to counter drones based on the optimal nonlinear resonant excitation frequency.

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