Intelligent bird repelling method and device based on sound-light synergistic effect

Abstract

The invention provides an intelligent bird repelling method and device based on a sound-light synergistic effect, and the method comprises the steps: generating bird flock flight state data through radar detection, evaluating a threat level to match an optimal repelling strategy, and finally controlling an acousto-optic device to generate and directionally send a collaborative repelling signal. According to the method and the device, the bird flock dynamic information detected by the radar is converted into the bird flock flight path data and the threat level, so that the driving strategy which is most matched with the current threat degree can be intelligently matched and executed from the strategy library. Therefore, high-intensity and high-energy-consumption sound-light collaborative driving signals can be accurately used for bird flocks really forming high-risk threats, and corresponding mild strategies are adopted for low-threat targets. Therefore, the pertinence and the final efficiency of repelling are greatly improved, the adaptability of the birds is effectively overcome, waste of repelling resources is fundamentally avoided, and unification of the bird repelling effect and energy consumption optimization is achieved.

Description

Technical Field

[0001] This application relates to the field of intelligent bird deterrence technology, and in particular to an intelligent bird deterrence method and device based on the synergistic effect of sound and light. Background Technology

[0002] In today's civil aviation field, bird strike risk around airports is one of the core hidden dangers that continuously threaten flight safety. Traditional bird control methods, such as gas cannons and recording predator calls, are limited by their singular, fixed, and predictable modes of action, leading to rapid adaptation by birds and a sharp decline in their effectiveness. This problem is particularly prominent in terminal areas with frequent flight takeoffs and landings. Bird activity in this airspace is characterized by its instantaneous, highly dynamic, and highly uncertain nature, while existing technologies lack the ability to accurately perceive and intelligently decide on bird intrusion behavior, resulting in low efficiency and high energy consumption in bird control. Summary of the Invention

[0003] This application provides an intelligent bird-repelling method and device based on the synergistic effect of sound and light, which solves the problem of low efficiency of single and fixed bird-repelling methods in related technologies.

[0004] The first aspect of this application provides an intelligent bird-repelling method based on the synergistic effect of sound and light, the intelligent bird-repelling method based on the synergistic effect of sound and light includes: By using radar to detect the monitored airspace to obtain echo signals, and processing the echo signals, bird flock flight trajectory data is generated. Threat assessment and analysis are performed on the flight trajectory data of the bird flock to determine the threat level of the target bird flock; The threat level is matched with a preset knowledge base of expulsion strategies to determine the target expulsion strategy corresponding to the threat level. Generate corresponding coordinated driving signals based on the configuration parameters of the target driving strategy; Based on the spatial location information provided by the bird flock flight trajectory data, the coordinated driving signal is sent to the airspace where the target bird flock is located.

[0005] Optionally, in a first implementation of the first aspect of this application, the step of obtaining echo signals by radar detection of the monitored airspace and processing the echo signals to generate bird flock flight trajectory data includes: The monitored airspace is scanned by frequency-modulated continuous wave radar to obtain echo signals, and the echo signals are subjected to fast Fourier transform to obtain the corresponding spectral data. By clustering the spectral data, reflection points whose three-dimensional Euclidean distance between any two reflection points is less than a preset first distance threshold are grouped into the same cluster, and the trajectory association of multiple consecutive frames of reflection points in the same cluster is performed to generate independent motion trajectories. The flight trajectory data of the flock of birds is determined by calculating the three-dimensional coordinates of the centroid of the trajectory of the independent movement trajectory, the confidence level of the average moving velocity vector and the moving direction.

[0006] Optionally, in the second implementation of the first aspect of this application, before the step of matching the threat level of the target bird flock assessed based on the bird flock flight trajectory data with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level, the method further includes: The warning distance is determined based on the relative positional relationship between the three-dimensional coordinates of the trajectory centroid and the core protection area; The magnitude of the component pointing towards the core protected area is determined based on the average moving speed vector in the bird flock flight trajectory data, and the directional threat index of the bird flock flying towards the core protected area is determined based on the product of the component magnitude and the confidence level of the moving direction. The target size index is determined by comparing the trajectory dispersion value in the bird flock flight trajectory data with a preset size threshold. Different weighting coefficients are assigned to the warning distance, the directional threat index, and the target size index to obtain the threat value of the target flock of birds; The threat value is input into a preset threat level mapping table to determine the threat level of the target flock of birds.

[0007] Optionally, in the third implementation of the first aspect of this application, the step of matching the threat level of the target bird flock assessed based on the bird flock flight trajectory data with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level includes: The threat level is matched with a pre-defined knowledge base of expulsion strategies to determine a set of expulsion strategies corresponding to the threat level. The trajectory dispersion value is compared with a preset density threshold. If the trajectory dispersion value is less than the preset density threshold, a first subset of strategies suitable for dense formations is selected from the set of driving strategies. If the trajectory dispersion value is greater than or equal to the preset density threshold, then a second subset of strategies suitable for dispersed formations is selected from the set of driving strategies; By comparing the average moving speed vector with a preset speed threshold, a second matching is performed on the first strategy subset or the second strategy subset to obtain the target driving strategy.

[0008] Optionally, in the fourth implementation of the first aspect of this application, the preset speed threshold includes a first speed threshold and a second speed threshold, and the step of comparing the average moving speed vector with the preset speed threshold to perform secondary matching on the first policy subset or the second policy subset to obtain the target driving strategy includes: The magnitude of the average moving speed vector is compared with the first speed threshold and a second speed threshold that is higher than the first speed threshold; If the magnitude of the average moving speed vector is less than or equal to the first speed threshold, the target flock of birds is determined to be in a low-speed moving state, and a strategy combining intermittent working mode and standard intensity parameter is selected from the first strategy subset or the second strategy subset as the target driving strategy. If the magnitude of the average moving speed vector is greater than the first speed threshold and less than or equal to the second speed threshold, the target flock of birds is determined to be in a medium-speed moving state, and a strategy combining a periodic working mode and a medium-intensity parameter is selected from the first strategy subset or the second strategy subset as the target driving strategy. If the magnitude of the average moving speed vector is greater than the second speed threshold, the target flock of birds is determined to be in a high-speed moving state, and a strategy with a combination of continuous strong output mode and high-intensity parameters is selected from the first strategy subset or the second strategy subset as the target driving strategy.

[0009] Optionally, in the fifth implementation of the first aspect of this application, the step of generating the corresponding cooperative driving signal according to the configuration parameters of the target driving strategy includes: According to the acoustic mode identifier of the target driving strategy, the corresponding reference audio waveform is called from the acoustic waveform library, and the reference audio waveform is processed according to the intensity parameter combination of the target driving strategy to generate the target acoustic driving signal. Based on the optical mode identifier of the target driving strategy, a corresponding optical control sequence is generated, and the pulse width and pulse interval of the optical control sequence are modulated according to the intensity parameter combination to generate a target optical driving signal. The target acoustic driving signal and the target optical driving signal are time-aligned to generate a cooperative driving signal.

[0010] Optionally, in a sixth implementation of the first aspect of this application, the method further includes: During the first driving-away period, the acoustic generation unit is controlled to output a mid-to-low frequency acoustic signal that mimics the calls of bird predators, and the optical generation unit is controlled to alternately emit red and blue beams at a first preset frequency. During the second driving period immediately following the first driving period, the mid-to-low frequency acoustic signal is switched to a sweeping ultrasonic signal that covers the bird's auditory sensitive area, and the optical generation unit is simultaneously controlled to switch to emitting a laser beam that performs random path scanning. During the third driving-away period immediately following the second driving-away period, the acoustic generating unit is controlled to simultaneously output the mid-to-low frequency acoustic signal and the swept-frequency ultrasonic signal, and the optical generating unit is controlled to alternately output the red and blue light beam and the laser beam.

[0011] A second aspect of this application provides an intelligent bird-repelling device based on sound-optical synergy, wherein the intelligent bird-repelling device based on sound-optical synergy is used to implement an intelligent bird-repelling method based on sound-optical synergy. The intelligent bird-repelling device based on sound-optical synergy includes: The acquisition module is used to obtain echo signals by radar detection of the monitored airspace, and to process the echo signals to generate bird flock flight trajectory data. The matching module is used to match the threat level of the target bird flock, which is evaluated based on the bird flock flight trajectory data, with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level. The generation module is used to generate corresponding coordinated driving signals according to the configuration parameters of the target driving strategy; The sending module is used to send the coordinated driving signal to the airspace where the target flock of birds is located based on the spatial location information provided by the bird flock flight trajectory data.

[0012] A third aspect of this application provides an electronic device, including a memory and a processor, wherein the processor is configured to execute a computer program stored in the memory, and when the processor executes the computer program, it implements the steps of the intelligent bird-repelling method based on sound-light synergy provided in the first aspect of this application.

[0013] The fourth aspect of this application provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the intelligent bird-repelling method based on sound-light synergy provided in the first aspect of this application.

[0014] In summary, the intelligent bird deterrence method and device based on sound-optical synergy provided in this application generates bird flock flight status data through radar detection, then assesses the threat level to match the optimal deterrence strategy, and finally controls the sound-optical equipment to generate and directionally transmit synergistic deterrence signals. This application transforms the dynamic information of bird flocks detected by radar into bird flock flight trajectory data and threat levels, and can intelligently match and execute the deterrence strategy best suited to the current threat level from a strategy library. This allows high-intensity, high-energy-consuming sound-optical synergistic deterrence signals to be precisely used for bird flocks that truly pose a high threat, while employing correspondingly gentler strategies for low-threat targets. This not only greatly improves the targeting and final efficiency of deterrence and effectively overcomes the adaptability of birds, but also fundamentally avoids the waste of deterrence resources, achieving a balance between bird deterrence effectiveness and energy consumption optimization. Attached Figure Description

[0015] Figure 1 A flowchart illustrating the intelligent bird-repelling method based on sound-light synergy provided in this application embodiment; Figure 2 A schematic diagram of the program modules of the intelligent bird deterrent device based on the synergistic effect of sound and light provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0016] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] To address the low efficiency of single, fixed bird-repelling methods in related technologies, this application provides an intelligent bird-repelling method based on the synergistic effect of sound and light, such as... Figure 1 This is a flowchart illustrating the intelligent bird-repelling method based on sound-light synergy provided in this embodiment. The intelligent bird-repelling method based on sound-light synergy includes the following steps: Step 110: Obtain echo signals by radar detection of the monitored airspace, and process the echo signals to generate bird flock flight trajectory data.

[0018] Specifically, radar detection of monitored airspace relies on the round-trip propagation of electromagnetic waves. By continuously transmitting modulated signals into the airspace and receiving reflected echoes, the presence and dynamic state of targets in space are reflected by the changes in the time, frequency, and amplitude of the echoes. Since reflected signals from different distances have different return times, and targets at different speeds cause frequency shifts, the original echoes can be unfolded along the time and frequency axes to form a set of physical quantities that characterize spatial distribution and motion trends. Subsequently, by processing the amplitude envelope, frequency shift components, and phase changes of the echoes, the scattered data points are integrated into target trajectories with continuous motion characteristics in the airspace. Furthermore, bird flock flight trajectory data containing basic information such as position, altitude, speed, and direction of movement is extracted.

[0019] Step 130: Match the threat level of the target bird flock, which is assessed based on the bird flock flight trajectory data, with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level.

[0020] Specifically, when assessing the threat level of the aforementioned situation, influencing factors are constructed based on the geometric distance between the target group and the sensitive area, the approach trend, and the spatial aggregation degree of the target cluster. The approach intensity is evaluated by calculating the change in distance from the target's center point to the boundary of the sensitive area. This is further combined with factors such as whether the speed direction points towards the protected area, whether the speed magnitude shows a trend towards proximity, and whether the target group exhibits a high-density aggregation state. A comprehensive evaluation metric reflecting the degree of approach, size, and potential risk is then formed. This evaluation metric corresponds to a preset level range, allowing the target group to present a quantifiable risk level within the overall situation. The determined risk level is then linked to a pre-constructed deflection strategy system. By searching for strategy entries corresponding to the risk level, the basic strategy range is determined. Further filtering of the basic strategy range is then performed based on the spatial aggregation degree, movement speed, and whether the target group exhibits a rapid intrusion trend, ensuring that the deflection strategy is not only related to the risk level but also consistent with the instantaneous dynamic characteristics of the target. The screening process combines different intensity ranges, different working rhythms, and different energy output ranges, and rearranges the sound and light stimulation methods with clear applicable ranges so that they can correspond to the target's movement speed characteristics, approach speed characteristics, and group morphology characteristics, thereby selecting the most suitable repulsion scheme.

[0021] Step 140: Generate a corresponding coordinated driving signal according to the configuration parameters of the target driving strategy.

[0022] Specifically, the output formats of sound and light are determined based on the selected target-driving strategy. Corresponding configuration parameters are used to set the frequency band, amplitude, pulse rhythm, and continuity of the sound signal, ensuring that the audio stimulus creates a significantly disruptive effect within the target group's perceptual range. The emission rhythm, beam color, beam trajectory, and beam pulse density of the light signal are organized to create a rapidly changing, strong visual disturbance in the target group's spatial domain. To ensure that sound and light act simultaneously in time, the trigger times of the sound and light signals are aligned at the output end, allowing them to act on the target area with a coordinated rhythm, thus forming a composite stimulus output and significantly enhancing the driving effect.

[0023] Step 150: Based on the spatial location information provided by the bird flock flight trajectory data, send a coordinated drive-away signal to the airspace where the target bird flock is located.

[0024] Specifically, based on the target location range contained in the situational awareness data, the generated composite stimuli are applied to the airspace where the target is located. By controlling the coverage direction of the sound source and the scanning angle of the beam, the stimuli can accurately cover the target area. Furthermore, the pointing angle is continuously adjusted according to real-time position changes, ensuring that the stimuli are always aimed at the actual location of the target group, keeping them in a state of continuous disturbance. In this way, through spatial coverage and directional adjustment, the comprehensive interference output maintains an effective area of ​​action, thereby achieving an intelligent deterrence process based on the synergistic effect of sound and light.

[0025] In one optional implementation of this embodiment, the steps of obtaining echo signals by radar detection of the monitored airspace and processing the echo signals to generate bird flock flight trajectory data include: scanning the monitored airspace with frequency-modulated continuous wave radar to obtain echo signals, and performing fast Fourier transform on the echo signals to obtain corresponding spectral data; clustering the spectral data to group reflection points whose three-dimensional Euclidean distance between any two reflection points is less than a preset first distance threshold into the same cluster, and associating the trajectories of multiple consecutive frames of reflection points in the same cluster to generate independent motion trajectories; and determining the bird flock flight trajectory data by calculating the three-dimensional coordinates of the trajectory centroid, the confidence level of the average moving velocity vector and the moving direction of the independent motion trajectory.

[0026] In this embodiment, when scanning the monitored airspace using a frequency-modulated continuous wave radar, the radar continuously emits electromagnetic waves whose frequency varies linearly with time. These waveforms, when reflected back to the receiver, can generate distance-related phase shifts and velocity-related frequency shifts due to collisions with targets. The phase shift represents the time difference accumulated during the round trip, while the frequency shift represents the target's velocity along the radar direction. Upon receiving the reflected signal, the received waveform is organized chronologically and frequency-domain unfolded within a fixed time window. Frequency-domain unfolding transforms the time-varying electromagnetic wave into a sequence reflecting the intensity of different frequency components, thus forming spectral data. To eliminate interference and extract the true target, reflection points that are spatially close in the spectral data need to be grouped. The merging process determines which reflection points are close based on three-dimensional distance relationships. For example, if several points are closely adjacent in horizontal distance, altitude, and radial distance from the radar, they can be considered spatial targets from the same source. Therefore, a first distance threshold can be set. When the three-dimensional Euclidean distance between any two reflection points is less than the preset first distance threshold, these two reflection points can be grouped into the same cluster. After obtaining the merging results, reflection points of the same type that repeatedly appear in different time slices are connected. The connection process relies on the continuity of the position and the consistency of the displacement trend of the reflection points in adjacent time slices. For example, if a reflection point appears at a certain position in the first moment and is at an adjacent position in the next moment and moves in the same direction, the two can be identified as continuous trajectories of the same moving object. As time progresses, the connected trajectories will form a path that records the target's motion history. Then, by weighted averaging the spatial coordinates in the trajectory, the trajectory centroid can be obtained, which represents the overall position of the target group. By statistically analyzing the differences in the centroid positions in adjacent time slices, the average velocity vector can be obtained, which describes the target's movement direction and speed. At the same time, by comparing the stability of the velocity vector over multiple frames, the confidence level of the movement direction can be obtained. For example, when the velocity direction remains close to the same direction in multiple time slices, the confidence level will be higher. By combining the three-dimensional coordinates of the centroid, the average velocity vector, and the direction confidence, we can obtain information that reflects the overall position, overall movement trend, and approach risk of the target flock in the airspace, thereby constructing a complete description of the true dynamics of the bird flock in the airspace.

[0027] In an optional implementation of this embodiment, before the step of matching the threat level of the target bird flock assessed based on the bird flock flight trajectory data with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level, the method further includes: determining the warning distance based on the relative positional relationship between the three-dimensional coordinates of the trajectory centroid and the core protected area; determining the magnitude of the component pointing towards the core protected area based on the average moving speed vector in the bird flock flight trajectory data, and determining the directional threat index based on the product of the component magnitude and the confidence level of the moving direction; determining the target size index by comparing the trajectory dispersion value in the bird flock flight trajectory data with a preset size threshold; assigning different weighting coefficients to the warning distance, directional threat index, and target size index respectively to obtain the threat value of the target bird flock; and inputting the threat value into a preset threat level mapping table to determine the threat level of the target bird flock.

[0028] In this embodiment, the spatial intrusion intensity is assessed by comparing the three-dimensional coordinates of the trajectory centroid with the geometric boundary of the core protected area. The three-dimensional coordinates are interpreted as positions in the lateral, longitudinal, and height directions, allowing the measurement of the straight-line distance from the centroid to the nearest point in the protected area. When this distance decreases and crosses the warning buffer zone, the intrusion index increases, and vice versa. For example, if the centroid has entered the buffer zone and is close to the inner circle, the intrusion index will be in a high-value zone. Secondly, regarding the determination of movement intent, the approach force is represented by the magnitude of the component of the average movement velocity vector pointing towards the protected area. This component is multiplied by the confidence level of the movement direction to reflect the true intention. The confidence level refers to the consistency of the direction across multiple consecutive frames. For example, when the velocity direction is almost consistent across multiple frames and always points towards the core protected area, the confidence level will be significantly high, thus significantly amplifying the directional threat index. Conversely, if the direction fluctuates greatly, the index will be suppressed. To characterize the impact of group size, the spatial occupancy of the group is measured by calculating the geometric dispersion of trajectory points. This dispersion is then compared to a pre-defined size threshold. When the dispersion exceeds the threshold, the size index indicates a high-size state, and vice versa. For example, if most trajectory points are clustered in a small area, the dispersion is low, indicating a high-density formation; conversely, if the points are widely distributed, it indicates a dispersed formation. Different weighting coefficients are assigned to the warning distance, directional threat index, and size index to reflect the varying degrees of influence of each factor on the risk. A comprehensive threat value is obtained by summing the weights. The weights can be adjusted based on the importance of the protected object and historical experience. For instance, the intrusion weight can be increased when protecting densely populated areas, while the size weight can be increased when protecting aircraft runways. The obtained threat values ​​are mapped to a predefined threat level table to determine the final level. The mapping table reflects the threshold of the response strategy through segmented thresholds. When the threat value crosses a certain segment, the corresponding level of action is triggered. For example, if the overall threat value exceeds the high-risk threshold, it is judged as the highest level and a strong expulsion measure is required immediately. If it is in the middle range, a medium response is adopted.

[0029] In one optional implementation of this embodiment, the step of matching the threat level of the target bird flock, assessed based on the bird flock flight trajectory data, with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level includes: matching the threat level in the preset deterrence strategy knowledge base to determine a set of deterrence strategies corresponding to the threat level; comparing the trajectory dispersion value with a preset density threshold; if the trajectory dispersion value is less than the preset density threshold, selecting a first subset of strategies suitable for dense formations from the set of deterrence strategies; if the trajectory dispersion value is greater than or equal to the preset density threshold, selecting a second subset of strategies suitable for dispersed formations from the set of deterrence strategies; and performing a secondary matching of the first or second subset of strategies by comparing the average moving speed vector with a preset speed threshold to obtain the target deterrence strategy.

[0030] In this embodiment, in a pre-set knowledge base of expulsion strategies, several candidate strategy entries are first searched using threat level as the search key. Each entry includes acoustic output form, optical output form, intensity parameters, working rhythm, and applicable formation identifier. Therefore, the results obtained from the threat level search constitute a set of expulsion strategies. It can be understood that the threat level is composed of multiple weighted indices, so the same threat level may be composed of indices, and the corresponding targeted expulsion strategies are not entirely the same. Subsequently, the geometric characteristics of the target group are refined to achieve more accurate matching. The spatial occupancy range of the group is measured by giving a clear meaning to the trajectory dispersion value. The trajectory dispersion value represents the average deviation of the trajectory point from the center of the group or the area of ​​the region enclosed by the trajectory point, thereby distinguishing between highly clustered and dispersed distributions. This value is compared with a pre-set density threshold. If the dispersion is less than the threshold, the group is considered to have a dense formation. At this time, strategies marked as suitable for dense formations are selected from the initial strategy set to form a first strategy subset. Conversely, if the dispersion is greater than or equal to the threshold, it is considered to be a dispersed formation, and strategies suitable for dispersed formations are selected from the initial strategy set to form a second strategy subset. The speed attribute is then further analyzed by comparing the magnitude of the average moving speed vector with a preset speed threshold range to distinguish between low-speed, medium-speed, and high-speed motion states. The stability of the speed direction is used as an auxiliary criterion for further judgment, and a secondary screening is performed on the selected subset: for low-speed states, strategies with intermittent output, low to medium intensity, and short-range sweeping within a region are prioritized; for medium-speed states, strategies with periodic output, medium intensity, and expanded coverage are prioritized; and for high-speed states, strategies with continuous output, high intensity, and long-range directional coverage are prioritized. This secondary screening process essentially involves matching and rearranging the parameterized configurations in the strategy entries, ensuring that the remaining strategies respond to both the threat level and the group's morphology and dynamic characteristics. Furthermore, priority rules can be introduced during the screening process, such as increasing the weight of response intensity for groups near critical assets, or assigning higher priority to strategies that have been effective against a certain group in the past, to facilitate rapid decision-making. It should be noted that adjustable parameter templates are used in the strategy entries, and applicable conditions are identified with text or numerical labels, so that a repulsion configuration that can be issued can be directly generated after matching is completed. For example, when the threat level is medium to high and the dispersion is small, and the speed is between medium and high speed, the final target repulsion strategy may consist of a combination of medium to high intensity predator call output, rapid random laser scanning and alternating red and blue strobe, with clear pulse interval and duration settings, so as to realize a closed-loop mapping from generalized threat to specific repulsion execution.

[0031] In one optional embodiment of this example, the preset speed threshold includes a first speed threshold and a second speed threshold. The step of obtaining a target driving strategy by comparing the average moving speed vector with the preset speed threshold and performing secondary matching on the first strategy subset or the second strategy subset includes: comparing the magnitude of the average moving speed vector with the first speed threshold and the second speed threshold which is higher than the first speed threshold; if the magnitude of the average moving speed vector is less than or equal to the first speed threshold, the target flock of birds is determined to be in a low-speed moving state, and a strategy combining intermittent working mode and standard intensity parameters is selected from the first strategy subset or the second strategy subset as the target driving strategy; if the magnitude of the average moving speed vector is greater than the first speed threshold and less than or equal to the second speed threshold, the target flock of birds is determined to be in a medium-speed moving state, and a strategy combining periodic working mode and medium intensity parameters is selected from the first strategy subset or the second strategy subset as the target driving strategy; if the magnitude of the average moving speed vector is greater than the second speed threshold, the target flock of birds is determined to be in a high-speed moving state, and a strategy combining continuous strong output mode and high intensity parameters is selected from the first strategy subset or the second strategy subset as the target driving strategy.

[0032] In this embodiment, the magnitude of the average moving velocity vector is understood as the overall velocity of the group along the direction of movement per unit time. Therefore, by comparing this velocity magnitude with two pre-set velocity thresholds, the group's movement state can be divided into three levels: low speed, medium speed, and high speed. During the comparison process, the sum of the squares of the velocity vector components in the three directions is first calculated, and then the square root is taken to obtain a scalar velocity value. This scalar value is then compared with the first and second thresholds to determine the classification interval, thus serving as the basis for grading the intensity of the dispersal strategy. Next, for the low-speed situation, when the movement state is determined to be low-speed, an intermittent working mode combined with standard intensity parameters should be preferentially selected. The intermittent working mode refers to the sound and light output operating at a low duty cycle, i.e., generating interference signals that can be detected by birds within a certain working time before entering a dormant period to reduce energy consumption and minimize continuous disturbance to the environment. Meanwhile, the standard intensity parameter combination limits the nominal values ​​of physical quantities such as sound pressure level, frequency band, beam brightness, and pulse width to ensure that the stimulus intensity is sufficient to guide dense or dispersed formations to slowly withdraw without causing excessive panic. Furthermore, in the medium-speed scenario, if the speed is between the two thresholds, it is classified as a medium-speed movement state. In this case, the preferred combination is a periodic operating mode and a medium-intensity parameter combination. The periodic operating mode means that the acoustic and optical outputs repeat at regular time intervals, and the signal duration and interval length within each cycle have a clear ratio, thereby achieving a balance between coverage and stimulation frequency. This allows the moving flock of birds to change course after receiving continuous but predictable warnings. Subsequently, if the speed exceeds the second threshold and is judged as a high-speed movement state, a continuous strong output mode and a high-intensity parameter combination should be selected from the corresponding strategy subset. The continuous strong output mode means that the acoustic and optical outputs apply interference in a high duty cycle or a near-continuous manner, while the high-intensity parameter combination increases the sound pressure level, expands the effective frequency band, and increases the beam movement speed and flashing frequency to maximize the suppression effect on rapidly approaching targets. Meanwhile, the selection process also requires matching subset attributes. First, it's necessary to determine whether the subset is suitable for dense or dispersed formations. Then, within that subset, the selection rules for the aforementioned modes and intensities are applied according to the speed level. This ensures the strategy responds to both the group's form and its dynamic characteristics. Furthermore, to avoid single configuration failures, adjustable parameter templates can be retained within the selected strategy to allow for adjustments to the duty cycle, pulse interval, and sound level based on real-time feedback during implementation. For example, when the first speed threshold is set to two meters per second and the second threshold to six meters per second, if the group speed is one meter per second, an intermittent output of ten seconds of activation and twenty seconds of silence will be selected, maintaining moderate sound pressure and moderate light intensity. If the speed is three meters per second, a periodic output of five seconds of activation and five seconds of silence will be selected, increasing the coverage angle. If the speed is eight meters per second, a near-continuous high sound pressure and rapid random beam scanning will be selected to achieve powerful dispersal. This directly links speed determination with strategy intensity and transforms it into specific, deployable parameter configurations.

[0033] In an optional implementation of this embodiment, the step of generating a corresponding cooperative driving signal based on the configuration parameters of the target driving strategy includes: calling a corresponding reference audio waveform from an acoustic waveform library based on the acoustic mode identifier of the target driving strategy, and processing the reference audio waveform according to the intensity parameter combination of the target driving strategy to generate a target acoustic driving signal; generating a corresponding optical control sequence based on the optical mode identifier of the target driving strategy, and modulating the pulse width and pulse interval of the optical control sequence according to the intensity parameter combination to generate a target optical driving signal; and aligning the target acoustic driving signal and the target optical driving signal in time to generate a cooperative driving signal.

[0034] In this embodiment, based on the acoustic pattern identifier in the target driving strategy, the corresponding reference audio waveform is retrieved from the acoustic waveform library. This waveform is interpreted as a sound sample with a specific frequency band, time domain envelope, and initial amplitude. The waveform library is a collection of pre-recorded or synthesized sounds, and each entry contains a spectral range description and a perceived intensity label. After the reference audio is retrieved, it is processed according to the combination of intensity parameters. The combination of intensity parameters is a set of adjustable physical quantities, such as sound pressure level (i.e., the amplitude of the sound wave), upper and lower limits of the frequency band, pulse duty cycle, and envelope rise and fall time. The acoustic stimulation effect is changed by adjusting the amplitude amplification or attenuation, limiting or broadening the spectrum, and introducing pulsed or continuous output in the time domain, thereby generating a target acoustic driving signal. In addition, short-time frequency sweeps or randomized phase perturbations can be added to the waveform to avoid animal habituation. Simultaneously, an optical control sequence is generated based on the optical mode identifier. The optical control sequence is a timing table consisting of a series of beam pointing, color switching, and scanning trajectories. Each entry includes attributes such as emission direction, beam duration, and spot size. Then, the pulse width and pulse interval of the sequence are modulated according to the combination of intensity parameters. The pulse width refers to the duration of a single beam emission, and the pulse interval refers to the idle time between adjacent emission. Increasing the pulse width can improve the instantaneous light energy output, while shortening the pulse interval can improve the overall duty cycle, thereby achieving an optical change from gentle cues to strong stimuli. Furthermore, random path and velocity variations can be introduced into the control sequence to enhance the unpredictability of disturbances. Subsequently, to form a coordinated driving signal, the target acoustic driving signal and the target optical driving signal need to be time-aligned. This time alignment includes correcting the trigger times of the acoustic and optical signals based on a unified clock reference, compensating for their respective transmission and startup delays, and synchronizing pulse boundaries. This ensures that the key acoustic energy peak and beam flicker coincide within the desired time window, enhancing the perceived impact. Simultaneously, system jitter needs to be monitored, and microsecond-level delays need to be inserted as necessary to ensure time stability for multiple repetitions. For example, when the startup delay of the acoustic amplifier is significantly higher than that of the optical transmitter, the acoustic signal can be triggered earlier to achieve [the desired effect]. Since the peak values ​​overlap, the final output of the coordinated driving signal is a predefined time-series stream, which includes amplitude and frequency modification of the acoustic waveform and control of the width and interval of the optical pulses. For example, in a medium-intensity scenario, the predator sound can be set to trigger in the first 200 milliseconds and repeat in the form of periodic pulses in the following second, while the optical control sequence emits a red and blue alternating beam of light lasting for 500 milliseconds at the midpoint of each acoustic pulse. By adjusting the sound and light together, the synergistic effect of time and perception can be achieved, thereby improving the driving effect and facilitating subsequent fine-tuning of parameters based on actual measurement feedback.

[0035] In one optional embodiment of this example, during the first driving-away period, the acoustic generating unit is controlled to output a mid-to-low frequency acoustic signal that mimics the calls of bird predators, and the optical generating unit is controlled to alternately emit red and blue beams at a first preset frequency; during the second driving-away period immediately following the first driving-away period, the mid-to-low frequency acoustic signal is switched to a sweeping ultrasonic signal whose frequency band covers the hearing-sensitive area of ​​birds, and the optical generating unit is simultaneously controlled to switch to emitting a laser beam that performs random path scanning; during the third driving-away period immediately following the second driving-away period, the acoustic generating unit is controlled to simultaneously output the mid-to-low frequency acoustic signal and the sweeping ultrasonic signal, and the optical generating unit is controlled to alternately output red and blue beams and laser beams.

[0036] In this embodiment, during the first deterrence period, the acoustic output primarily consists of low-to-mid-frequency signals mimicking the calls of bird predators. This low-to-mid-frequency range typically covers hundreds to thousands of hertz, allowing birds to perceive it clearly without causing high-frequency discomfort. Furthermore, this frequency range experiences minimal propagation loss in the air and has a wide coverage area, thus providing an initial warning to the flock. During this period, the acoustic output adjusts its amplitude and pulse rhythm to alternating the duration and interval of each call, creating a recognizable bioacoustic signature that alerts the flock. Simultaneously, the optical output presents alternating red and blue light beams, switching at a first preset frequency. This preset frequency refers to the switching cycle between red and blue light flashes. By controlling the flashing interval and duration, the light stimulation creates a significant visual disturbance in the airspace, causing birds to visually perceive environmental anomalies and forming a synchronized multimodal stimulus with the acoustic signal, thus enhancing the effectiveness of the initial deterrence. During the subsequent second driving-off period, the acoustic signal is converted into a frequency-sweeping ultrasonic signal covering the bird's auditory sensitive area. Frequency-sweeping ultrasonic signals, typically above 20 kHz, are signals with frequencies higher than the mid-to-low frequency band that cover the bird's highly sensitive auditory area. By continuously or rapidly changing the frequency within this range, a frequency scanning effect is created, enhancing the birds' perceived discomfort. At this time, the optical output switches to laser beam scanning. The laser beam moves along a random path in the airspace. This random path means that the beam's direction, speed, and scanning trajectory are not fixed. By randomly changing the scanning direction and angle, the birds find it difficult to predict the light source's location, thus increasing stress and uncertainty. The acoustic and optical outputs are highly synchronized during this stage. While the acoustic signal covers the entire frequency band, the beam moves randomly in the airspace, causing the birds to experience strong auditory and visual interference, thus prompting the flock to accelerate away from the core area. Then, in the third driving-off period, the acoustic unit simultaneously outputs a mid-to-low frequency signal mimicking predator calls and a frequency-sweeping ultrasonic signal. This creates a superposition effect of low-frequency biological warnings and high-frequency discomfort stimuli within the same time period, enhancing the overall deterrent effect on the birds. The optical generator alternately outputs red and blue light beams and a laser beam. The red and blue beams continue to provide flashing visual warnings, while the laser beam scans the bird flock's location with a random path. The alternation of these two types of light signals in time creates a visual stimulus that is both regular and contains unpredictable disturbances, increasing the target flock's attention and discomfort. Throughout the process, the timing of the audio-visual outputs is precisely aligned; that is, the triggering times of the low-frequency and high-frequency audio signals, red and blue light, and laser beams are all synchronized to ensure maximum synergistic effect of the multimodal signals in perception. For example, when the low-frequency predator sound is triggered in the first 100 milliseconds, the red and blue light flashes at the midpoint of the audio signal, while the swept-frequency ultrasonic signal and laser scan are superimposed in the next 100 milliseconds, thus forming a continuous and multi-layered stimulus that the flock cannot adapt to or form a habit with, effectively achieving continuous control from mild warnings to strong deterrence.

[0037] This application provides an intelligent bird deterrence method based on sound-optical synergy. It generates bird flock flight status data through radar detection, assesses threat levels to match the optimal deterrence strategy, and finally controls sound-optical devices to generate and directionally transmit synergistic deterrence signals. This application converts the dynamic information of bird flocks detected by radar into bird flight trajectory data and threat levels, intelligently matching and executing the deterrence strategy best suited to the current threat level from a strategy library. This allows high-intensity, high-energy-consuming sound-optical synergistic deterrence signals to be precisely used against bird flocks that truly pose a high threat, while employing correspondingly gentler strategies against low-threat targets. This not only greatly improves the targeting and final efficiency of deterrence and effectively overcomes bird adaptability, but also fundamentally avoids the waste of deterrence resources, achieving a balance between bird deterrence effectiveness and energy consumption optimization.

[0038] Figure 2 This application provides an intelligent bird-repelling device based on sound-light synergy, which can be used to implement the intelligent bird-repelling method based on sound-light synergy described in the foregoing embodiments. Figure 2 As shown, this intelligent bird-repelling device based on the synergistic effect of sound and light mainly includes: The acquisition module is used to obtain echo signals by radar detection of the monitored airspace, and to process the echo signals to generate bird flock flight trajectory data. The matching module is used to match the threat level of the target bird flock, which is evaluated based on the bird flock flight trajectory data, with a preset deterrence strategy knowledge base to determine the target deterrence strategy corresponding to the threat level. The generation module is used to generate corresponding coordinated driving signals according to the configuration parameters of the target driving strategy; The sending module is used to send the coordinated driving signal to the airspace where the target flock of birds is located based on the spatial location information provided by the bird flock flight trajectory data.

[0039] In one optional implementation of this embodiment, the acquisition module is specifically used to: scan the monitored airspace using a frequency-modulated continuous wave radar to acquire echo signals, and perform a fast Fourier transform on the echo signals to obtain corresponding spectral data; cluster the spectral data to group reflection points whose three-dimensional Euclidean distance between any two reflection points is less than a preset first distance threshold into the same cluster, and associate the trajectories of multiple consecutive frames of reflection points in the same cluster to generate independent motion trajectories; and determine the bird flock flight trajectory data by calculating the three-dimensional coordinates of the trajectory centroid, the confidence level of the average moving velocity vector and the moving direction of the independent motion trajectory.

[0040] In an optional implementation of this embodiment, the matching module is further configured to: determine the warning distance based on the relative positional relationship between the three-dimensional coordinates of the trajectory centroid and the core protected area; determine the magnitude of the component pointing towards the core protected area based on the average moving speed vector in the bird flock flight trajectory data, and determine the directional threat index based on the product of the component magnitude and the confidence level of the moving direction; determine the target size index by comparing the trajectory dispersion value in the bird flock flight trajectory data with a preset size threshold; assign different weighting coefficients to the warning distance, directional threat index, and target size index respectively to obtain the threat value of the target bird flock; and input the threat value into a preset threat level mapping table to determine the threat level of the target bird flock.

[0041] In an optional implementation of this embodiment, the matching module is specifically used for: matching threat levels in a preset drive-away strategy knowledge base to determine a set of drive-away strategies corresponding to the threat level; comparing the trajectory dispersion value with a preset density threshold; if the trajectory dispersion value is less than the preset density threshold, then selecting a first subset of strategies suitable for dense formations from the set of drive-away strategies; if the trajectory dispersion value is greater than or equal to the preset density threshold, then selecting a second subset of strategies suitable for dispersed formations from the set of drive-away strategies; and performing a secondary matching of the first or second subset of strategies by comparing the average moving speed vector with a preset speed threshold to obtain the target drive-away strategy.

[0042] In an optional implementation of this embodiment, the matching module is further specifically used to: compare the magnitude of the average moving speed vector with a first speed threshold and a second speed threshold higher than the first speed threshold; if the magnitude of the average moving speed vector is less than or equal to the first speed threshold, the target flock of birds is determined to be in a low-speed moving state, and a strategy combining an intermittent working mode and a standard intensity parameter is selected from the first strategy subset or the second strategy subset as the target driving strategy; if the magnitude of the average moving speed vector is greater than the first speed threshold and less than or equal to the second speed threshold, the target flock of birds is determined to be in a medium-speed moving state, and a strategy combining a periodic working mode and a medium intensity parameter is selected from the first strategy subset or the second strategy subset as the target driving strategy; if the magnitude of the average moving speed vector is greater than the second speed threshold, the target flock of birds is determined to be in a high-speed moving state, and a strategy combining a continuous high-power output mode and a high-intensity parameter is selected from the first strategy subset or the second strategy subset as the target driving strategy.

[0043] In one optional implementation of this embodiment, the generation module is specifically used to: retrieve the corresponding reference audio waveform from the acoustic waveform library according to the acoustic mode identifier of the target driving strategy, and process the reference audio waveform according to the intensity parameter combination of the target driving strategy to generate a target acoustic driving signal; generate the corresponding optical control sequence according to the optical mode identifier of the target driving strategy, and modulate the pulse width and pulse interval of the optical control sequence according to the intensity parameter combination to generate a target optical driving signal; and perform time alignment between the target acoustic driving signal and the target optical driving signal to generate a cooperative driving signal.

[0044] In an optional embodiment of this example, the transmitting module is further configured to: during the first driving-away time period, control the acoustic generating unit to output a mid-to-low frequency acoustic signal that mimics the calls of bird predators, and control the optical generating unit to alternately emit red and blue beams at a first preset frequency; during the second driving-away time period immediately following the first driving-away time period, switch the mid-to-low frequency acoustic signal to a sweeping ultrasonic signal whose output frequency band covers the auditory sensitive area of ​​birds, and simultaneously control the optical generating unit to switch to emitting a laser beam that performs random path scanning; during the third driving-away time period immediately following the second driving-away time period, control the acoustic generating unit to simultaneously output the mid-to-low frequency acoustic signal and the sweeping ultrasonic signal, and control the optical generating unit to alternately output red and blue beams and laser beams.

[0045] The intelligent bird deterrence device based on sound-optical synergy provided in this application generates bird flock flight status data through radar detection, then assesses the threat level to match the optimal deterrence strategy, and finally controls the sound-optical equipment to generate and directionally transmit synergistic deterrence signals. This application converts the dynamic information of bird flocks detected by radar into bird flock flight trajectory data and threat levels, and can intelligently match and execute the deterrence strategy best suited to the current threat level from a strategy library. This allows high-intensity, high-energy-consuming sound-optical synergistic deterrence signals to be precisely used for bird flocks that truly pose a high threat, while employing correspondingly gentler strategies for low-threat targets. This not only greatly improves the targeting and final efficiency of deterrence and effectively overcomes the adaptability of birds, but also fundamentally avoids the waste of deterrence resources, achieving a balance between bird deterrence effectiveness and energy consumption optimization.

[0046] According to the scheme provided in this application Figure 3 An electronic device is provided as an embodiment of this application. This electronic device can be used to implement the intelligent bird-repelling method based on sound-light synergy in the foregoing embodiments, and mainly includes: The system includes a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and executable on the processor 302. The memory 301 and the processor 302 are connected via communication. When the processor 302 executes the computer program 303, it implements the intelligent bird-repelling method based on sound-light synergy described in the foregoing embodiments. The number of processors can be one or more.

[0047] The memory 301 can be a high-speed random access memory (RAM) or a non-volatile memory, such as a disk storage device. The memory 301 is used to store executable program code, and the processor 302 is coupled to the memory 301.

[0048] Furthermore, embodiments of this application also provide a computer-readable storage medium, which may be disposed in the electronic device described in the above embodiments, and the computer-readable storage medium may be as described above. Figure 3 The memory in the illustrated embodiment.

[0049] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the intelligent bird-repelling method based on sound-light synergy described in the foregoing embodiments. Furthermore, the computer-readable storage medium can also be any medium capable of storing program code, such as a USB flash drive, external hard drive, read-only memory (ROM), RAM, magnetic disk, or optical disk.

[0050] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0051] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An intelligent bird repelling method based on sound-light synergy, characterized in that, The method comprises the following steps: obtaining echo signals by radar detection on a monitoring airspace, and processing the echo signals to generate bird flock flight trajectory data; matching a threat level of the target bird flock evaluated based on the bird flock flight trajectory data with a preset driving strategy knowledge base to determine a target driving strategy corresponding to the threat level; generating a corresponding cooperative driving signal according to configuration parameters of the target driving strategy; sending the cooperative driving signal to the airspace where the target bird flock is located based on spatial position information provided by the bird flock flight trajectory data.

2. The intelligent bird repelling method based on sound-light synergy according to claim 1, characterized in that, The step of obtaining echo signals by radar detection on a monitoring airspace, and processing the echo signals to generate bird flock flight trajectory data comprises the following steps: scanning the monitoring airspace by a frequency-modulated continuous wave radar to obtain echo signals, and performing fast Fourier transform on the echo signals to obtain corresponding spectral data; merging reflection points with a three-dimensional Euclidean distance between any two reflection points less than a preset first distance threshold into the same cluster by clustering the spectral data, and performing trajectory association on continuous multiple frames of reflection points in the same cluster to generate independent motion trajectories; determining bird flock flight trajectory data by calculating three-dimensional coordinates, average moving speed vectors and moving direction confidence of trajectory centroids of the independent motion trajectories.

3. The intelligent bird repelling method based on sound-light synergy according to claim 2, characterized in that, Before the step of matching a threat level of the target bird flock evaluated based on the bird flock flight trajectory data with a preset driving strategy knowledge base to determine a target driving strategy corresponding to the threat level, the method further comprises the following steps: determining a warning distance according to the relative position relationship between the three-dimensional coordinates of the trajectory centroid and a core protection area; determining the component size of the moving direction pointing to the core protection area according to the average moving speed vector in the bird flock flight trajectory data, and determining a directional threat index of the bird flock flying to the core protection area according to the product of the component size and the confidence of the moving direction; determining a target size index by comparing a trajectory dispersion value in the bird flock flight trajectory data with a preset size threshold; weighting the warning distance, the directional threat index and the target size index by different weighting coefficients respectively to obtain a threat value of the target bird flock; inputting the threat value into a preset threat level mapping table to determine the threat level of the target bird flock.

4. The intelligent bird repelling method based on sound-light synergy according to claim 3, characterized in that, The step of matching a threat level of the target bird flock evaluated based on the bird flock flight trajectory data with a preset driving strategy knowledge base to determine a target driving strategy corresponding to the threat level comprises the following steps: matching the threat level in a preset driving strategy knowledge base to determine a driving strategy set corresponding to the threat level; comparing the trajectory dispersion value with a preset density threshold, and if the trajectory dispersion value is less than the preset density threshold, filtering out a first strategy subset suitable for dense formation from the driving strategy set; if the trajectory dispersion value is greater than or equal to the preset density threshold, filtering out a second strategy subset suitable for dispersed formation from the driving strategy set; The average moving speed vector is compared with a preset speed threshold value to perform secondary matching on the first strategy subset or the second strategy subset, so as to obtain a target driving strategy.

5. The intelligent bird repelling method based on sound-light synergy according to claim 4, characterized in that, The preset speed threshold value includes a first speed threshold value and a second speed threshold value, and the step of performing secondary matching on the first strategy subset or the second strategy subset to obtain a target driving strategy by comparing the average moving speed vector with a preset speed threshold value includes: The modulus of the average moving speed vector is compared with the first speed threshold value and the second speed threshold value higher than the first speed threshold value; If the modulus of the average moving speed vector is less than or equal to the first speed threshold value, it is determined that the target bird group is in a low-speed moving state, and a strategy of an intermittent working mode combined with a standard intensity parameter is screened from the first strategy subset or the second strategy subset as the target driving strategy; If the modulus of the average moving speed vector is greater than the first speed threshold value and less than or equal to the second speed threshold value, it is determined that the target bird group is in a medium-speed moving state, and a strategy of a periodic working mode combined with a medium-intensity parameter is screened from the first strategy subset or the second strategy subset as the target driving strategy; If the modulus of the average moving speed vector is greater than the second speed threshold value, it is determined that the target bird group is in a high-speed moving state, and a strategy of a continuous strong output mode combined with a high-intensity parameter is screened from the first strategy subset or the second strategy subset as the target driving strategy.

6. The intelligent bird repelling method based on sound-light synergy according to claim 5, characterized in that, The step of generating a corresponding cooperative driving signal according to the configuration parameters of the target driving strategy includes: According to the acoustic mode identifier of the target driving strategy, a corresponding reference audio waveform is called from an acoustic waveform library, and the target acoustic driving signal is generated by processing the reference audio waveform according to the intensity parameter combination of the target driving strategy; According to the optical mode identifier of the target driving strategy, a corresponding optical control sequence is generated, and the target optical driving signal is generated by modulating the pulse width and pulse interval of the optical control sequence according to the intensity parameter combination; The target acoustic driving signal and the target optical driving signal are time-aligned to generate a cooperative driving signal.

7. The intelligent bird repelling method based on sound-light synergy according to claim 5, characterized in that, The method further includes: In a first driving time period, an acoustic generating unit is controlled to output a middle-low frequency acoustic signal simulating a call of a bird enemy, and an optical generating unit is controlled to alternately switch a red-blue light beam at a first preset frequency; In a second driving time period immediately following the first driving time period, the middle-low frequency acoustic signal is switched to output a sweep frequency ultrasonic wave signal covering a bird hearing sensitive area, and the optical generating unit is synchronously controlled to switch to emit a laser beam performing irregular path scanning; In a third driving time period immediately following the second driving time period, the acoustic generating unit is controlled to simultaneously output the middle-low frequency acoustic signal and the sweep frequency ultrasonic wave signal, and the optical generating unit is controlled to alternately output the red-blue light beam and the laser beam.

8. An intelligent bird repelling device based on sound-light synergy, characterized in that, The intelligent bird repelling device based on sound-light synergy is used for realizing the intelligent bird repelling method based on sound-light synergy in claim 1, and the intelligent bird repelling device based on sound-light synergy comprises: An acquisition module is configured to acquire echo signals by radar detection on a monitored airspace, and process the echo signals to generate bird flock flight trajectory data; A matching module is configured to match a threat level of the target bird flock evaluated based on the bird flock flight trajectory data with a preset repelling strategy knowledge base, and determine a target repelling strategy corresponding to the threat level; A generation module is configured to generate a corresponding cooperative repelling signal according to configuration parameters of the target repelling strategy; A sending module is configured to send the cooperative repelling signal to an airspace where the target bird flock is located based on spatial position information provided by the bird flock flight trajectory data.

9. An electronic device, comprising: A computer program product comprises a memory and a processor, wherein: The processor is configured to execute a computer program stored in the memory; When the processor executes the computer program, steps in the intelligent bird repelling method based on sound-light synergy in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by the processor, steps in the intelligent bird repelling method based on sound-light synergy in any one of claims 1 to 7 are implemented.

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