A method and device for multi-dimensional monitoring of birds based on biomimetic optics

Abstract

The application relates to a kind of bird multidimensional monitoring method and device based on bionic optics.The method of the application comprises: obtaining the position information, body type category, motion direction and behavior state of bird target;According to the position information, select the target bionic action sequence from the preset multiple bionic action sequences;According to the body type category, determine the laser exit parameter;According to the behavior state, determine the pan-tilt movement amplitude;According to the position information and the motion direction, determine the pan-tilt movement direction;Determine the MEMS galvanometer scanning parameter;According to the above parameters, generate bionic optical command;According to the body type category, determine the type and emission mode of acoustic guidance signal, and determine the frequency band control parameter, generate acoustic auxiliary command;Control the pan-tilt, laser and MEMS galvanometer to execute bionic optical command, control the loudspeaker array to execute acoustic auxiliary command.The application realizes effective driving of birds through bionic optical guidance and acoustic auxiliary cooperation.

Description

Technical Field

[0001] This application relates to the field of intelligent bird deterrence technology, specifically to a multidimensional bird monitoring method and device based on biomimetic optics. Background Technology

[0002] With the improvement of the ecological environment, the number and species of birds are constantly increasing, and the intersection of bird activities with human production and living areas is becoming more and more frequent. Near power grid transmission lines, bird nesting may cause short circuits; in airport areas, bird flight may affect the safety of aircraft take-off and landing; in farmland areas, birds pecking at crops may cause reduced yields.

[0003] Existing methods for repelling birds mainly employ sound, ultrasound, laser, or physical interception, but these methods have the following shortcomings:

[0004] (1) Existing laser deterrence devices usually adopt a fixed frequency scanning mode, and the laser beam only makes simple reciprocating or circular motions. Birds can easily adapt to this, and the deterrence effect will decrease significantly after long-term use. (2) Existing deterrence devices mostly operate in a single mode and lack the ability to dynamically adjust deterrence strategies based on the bird’s behavioral state (such as being still, foraging, or flying), thus failing to achieve differentiated deterrence of birds in different behavioral states. (3) Existing equipment has low laser visibility in high light environments (such as noon on a sunny day), which limits the repelling effect. Summary of the Invention

[0005] This application provides a method and device for multidimensional bird monitoring based on biomimetic optics, aiming to solve the technical problem that the long-term deterrence effect of existing laser deterrence devices is reduced due to the single scanning mode and the ease with which birds adapt.

[0006] According to a first aspect, embodiments of this application provide a multidimensional bird monitoring method based on biomimetic optics, the method comprising the following steps: When a bird target is detected within a preset monitoring area, the location information, size category, and behavioral status of the bird target are acquired; the behavioral status includes stationary, foraging, and flying. Based on the location information and behavioral state of the bird target, a target biomimetic action sequence is selected from a variety of preset biomimetic action sequences; wherein, the target biomimetic action sequence consists of keyframes at consecutive time points, and each keyframe includes the horizontal angle and vertical angle of the gimbal, as well as the on / off state and emission frequency of the laser; the location information is used to determine the type of biomimetic action, and the behavioral state is used to determine the execution style of the biomimetic action under that type; Determine the scanning parameters of the MEMS galvanometer; the scanning parameters are used to control the synchronous deflection of the MEMS galvanometer in the horizontal and vertical directions, so that the laser beam forms an elliptical scanning trajectory at the location of the bird target; Generate biomimetic optical commands based on the target biomimetic action sequence and the scanning parameters of the MEMS galvanometer; The type and transmission method of the acoustic guidance signal are determined based on the bird size category; wherein, if the bird size category is small, the acoustic guidance signal is an ultrasonic signal, and the transmission method is pulse transmission; if the bird size category is medium, the acoustic guidance signal is a predator call signal, and the transmission method is continuous playback, with the volume of the predator call signal determined according to the distance between the bird target and the speaker array; if the bird size category is large, the acoustic guidance signal is a low-frequency warning sound signal, and the transmission method is continuous transmission. Determine the frequency band control parameters of the acoustic guidance signal; wherein, the frequency band control parameters are used to form directional beams in the frequency bands of the acoustic guidance signal that are above a preset frequency threshold, and to transmit the frequency bands that are below the preset frequency threshold in an omnidirectional manner; Acoustic auxiliary commands are generated based on the type, transmission method, volume, and frequency band control parameters of the acoustic guidance signal; The system controls the gimbal, laser, and MEMS mirror to execute the biomimetic optical commands to simulate raptor attack behavior, and controls the speaker array to execute the acoustic auxiliary commands.

[0007] In one specific implementation, when a bird target is detected within a preset monitoring area, acquiring the bird target's location information, size category, and behavioral status includes: The radar sensor is controlled to transmit detection signals to the monitoring area and receive echo signals. Based on the echo signals, the distance, speed, angle and echo cross-section information of the moving target are obtained, and radar features are generated. When both the distance and speed information are greater than the corresponding preset detection thresholds, the acoustic sensor is controlled to collect bird call signals in the monitoring area and extract acoustic features from the bird call signals; the image sensor is controlled to collect color images of the monitoring area and extract visual features from the color images; and the infrared sensor is controlled to collect thermal images of the monitoring area and extract infrared features from the thermal images. The radar features, acoustic features, visual features and infrared features are weighted and fused to obtain a fused feature vector. The fused feature vector is then input into the target detection model to identify whether the moving target is a bird target and to obtain the location and species information of the bird target. Based on the distance information, angle information, and the pixel area occupied by the bird target in the color image, the actual size of the bird target is estimated, and the body type of the bird target is determined in combination with the species information. The pixel displacement of the bird target in multiple consecutive frames is obtained from the color image. The movement speed and direction are calculated based on the pixel displacement, and the behavior state of the bird target is identified based on the movement speed and direction.

[0008] In one specific implementation, the method further includes: The acoustic sensor is controlled to collect the environmental noise signal of the monitoring area, and the preset detection threshold is dynamically adjusted according to the environmental noise signal: when the environmental noise signal is higher than the preset high noise threshold, the preset detection threshold is increased; when the environmental noise signal is lower than the preset low noise threshold, the preset detection threshold is decreased. The temperature sensor is controlled to collect the ambient temperature, and the thermal image collected by the infrared sensor is temperature-corrected based on the ambient temperature.

[0009] In one specific implementation, estimating the actual size of the bird target includes: The distance d between the bird target and the gimbal is calculated based on the distance information obtained by the radar sensor. The bird target's pixel area A in the color image is used as the bird's projected area S. The horizontal field of view θ of the image sensor and the width W of the color image are combined with the pixel area A. The bird's projected area S is calculated using the formula S = A × (d × tan(θ / 2) / (W / 2))². The bird's projected area S is used as the estimated actual size of the bird target.

[0010] In one specific implementation, identifying the behavioral state of the bird target based on its movement speed and direction includes: When the movement speed is lower than the first speed threshold, the behavior state is determined to be stationary; when the movement speed is between the first speed threshold and the second speed threshold and the movement trajectory is irregular, the behavior state is determined to be foraging; when the movement speed is higher than the second speed threshold and the movement trajectory is smooth, the behavior state is determined to be flying.

[0011] In one specific implementation, the biomimetic motion sequence includes at least a high-altitude hovering motion sequence, a dive attack motion sequence, and a lateral assault motion sequence; in the high-altitude hovering motion sequence, the gimbal continuously rotates horizontally, and the laser continuously emits light; in the dive attack motion sequence, the gimbal descends vertically while accelerating horizontally, and the laser's emission frequency is higher at the end of the dive than at the beginning; in the lateral assault motion sequence, the gimbal rapidly swings horizontally, and the laser continuously emits light; The step of selecting a target bionic action sequence from a variety of preset bionic action sequences based on the bird target's location information and behavioral state specifically includes: When the distance between the bird target and the gimbal is greater than the first preset value, the high-altitude circling action sequence is selected; when the distance between the bird target and the gimbal is between the first preset value and the second preset value, the dive attack action sequence is selected; when the distance between the bird target and the gimbal is less than the second preset value, the lateral attack action sequence is selected. Specifically, when the behavior state is foraging, the target bionic action sequence adopts a strong execution style; when the behavior state is flying, the target bionic action sequence adopts a tracking execution style; and when the behavior state is stationary, the target bionic action sequence adopts a default execution style.

[0012] In one specific implementation, the method further includes: Acquire light intensity, wind speed, temperature, and guidance success rate; wherein, the guidance success rate is the proportion of successful guidance in historical guidance records; When the light intensity is higher than a preset strong light threshold and the guidance success rate is lower than a preset success rate threshold, the PWM duty cycle of the laser is increased to a preset maximum value. When the wind speed is higher than the preset wind speed threshold, a preset compensation amount is added to the current PWM duty cycle; When the temperature is lower than the preset low temperature threshold, the heating device is activated and the PWM duty cycle of the laser is reduced. When the guidance fails for a preset number of consecutive times, the system switches from the current bionic action sequence to another bionic action sequence and regenerates the bionic optical instructions.

[0013] In one specific implementation, the method further includes: When executing the bionic optical command and the acoustic auxiliary command, the bionic optical command is executed first, and the acoustic auxiliary command is executed after a preset time interval.

[0014] In one specific implementation, the method further includes: The system monitors the operating status of each sensor; when the image sensor malfunctions, it switches to target detection using the radar sensor and the infrared sensor; when the infrared sensor malfunctions, it switches to target detection using the radar sensor and the image sensor; when both the image sensor and the infrared sensor malfunction, it switches to target detection using only the radar sensor; when the laser malfunctions, it switches to acoustic guidance using only the speaker array.

[0015] According to a second aspect, embodiments of this application provide a multidimensional bird monitoring device based on biomimetic optics, comprising: Radar sensors are used to transmit detection signals to the monitored area and receive echo signals. Acoustic sensors are used to collect environmental noise signals and bird call signals in the monitored area; An image sensor is used to acquire color images of the monitored area; An infrared sensor is used to acquire thermal images of the monitored area; Temperature sensor, used to collect ambient temperature; A light sensor is used to collect ambient light intensity. Wind speed sensor, used to collect ambient wind speed; A laser, used to emit a laser beam; MEMS galvanometers are disposed in the output optical path of the laser and are used to scan the laser beam; The gimbal supports the laser and the MEMS galvanometer. A loudspeaker array is used to emit acoustic guidance signals toward the bird target; A heating device is used to activate heating when the ambient temperature is below a preset low-temperature threshold; and The main processor is connected to the radar sensor, the acoustic sensor, the image sensor, the infrared sensor, the temperature sensor, the light sensor, the wind speed sensor, the laser, the MEMS galvanometer, the gimbal, the speaker array, and the heating device, respectively, and the main processor is configured to execute the method described in any one of the above.

[0016] The multidimensional bird monitoring method and device based on biomimetic optics provided in this application have the following beneficial effects: This application embodiment utilizes pre-stored multiple biomimetic action sequences. Based on the bird target's location information and behavioral state, it selects a target biomimetic action sequence and controls the gimbal to move according to the target's biomimetic action sequence. Simultaneously, the MEMS galvanometer deflects synchronously in both the horizontal and vertical directions, causing the laser beam to form an elliptical scanning trajectory at the bird target's location. Compared to the simple scanning mode with a fixed frequency in existing technologies, this application embodiment uses the superposition of the gimbal's motion trajectory and the galvanometer's scanning trajectory to simulate the dynamic visual effects of raptor flight and wing flapping with the laser beam. Birds are less likely to adapt, and the long-term deterrence effect is stable.

[0017] This application's embodiments determine the execution style of the biomimetic action based on the bird target's behavioral state (stationary, foraging, flying). For example, a strong execution style is used when foraging, a tracking execution style is used when flying, and a default execution style is used when stationary. Compared to the single shooing method in the prior art, this application's embodiments achieve differentiated shooing based on the bird's behavioral state.

[0018] The embodiments of this application employ a multi-sensor fusion perception system, which integrates multimodal data from radar sensors, acoustic sensors, image sensors, and infrared sensors. Through feature-level fusion and adaptive weighted fusion using an attention mechanism, the accuracy and robustness of target detection are significantly improved, and the false alarm rate is greatly reduced.

[0019] In this embodiment, while using biomimetic optical guidance, ultrasonic signals, predator calls, or low-frequency warning sounds are used as acoustic guidance signals according to the bird's size category. The frequency bands of the acoustic guidance signals above a preset frequency threshold are formed into directional beams, while the frequency bands below the preset frequency threshold are emitted in an omnidirectional manner, thereby achieving coordinated driving away by optical and acoustic guidance and improving the driving away effect. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings required in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a multidimensional bird monitoring method based on biomimetic optics in one embodiment of this application. Detailed Implementation

[0022] The detailed description of the accompanying drawings is intended to illustrate embodiments of this application and is not intended to represent only the forms in which this application can be implemented. It should be understood that the same or equivalent functionality can be achieved by different embodiments intended to be included within the spirit and scope of this application.

[0023] One embodiment of this application provides a multidimensional bird monitoring method based on biomimetic optics, such as... Figure 1 As shown, the method includes the following steps: Step S10: When a bird target is detected in the preset monitoring area, the location information, body type and behavioral status of the bird target are obtained; the behavioral status includes stationary, foraging and flying.

[0024] Specifically, in this embodiment, the monitoring area refers to a pre-defined spatial range where bird control operations need to be carried out, such as the area around an airport runway, a high-voltage power transmission line corridor, or farmland. For example, in the application around an airport runway, the monitoring area is within 100 meters on both sides of the runway centerline. Any bird activity within this area is considered a potential threat, requiring the triggering of subsequent monitoring and control procedures. By acquiring multi-dimensional information such as the location, size, and behavioral state of the bird target, a data foundation is provided for subsequently developing differentiated control strategies. The classification of behavioral states is based on the bird's activity characteristics. Different states correspond to different alertness and reaction patterns. For example, birds in a stationary state may be in a resting or observing environment state, birds in a foraging state have a strong dependence on food sources, while birds in a flying state have high mobility and escape capabilities.

[0025] Step S20: Select a target bionic action sequence from a variety of preset bionic action sequences based on the bird target's location information and behavioral state; wherein, the target bionic action sequence consists of keyframes at consecutive time points, and each keyframe includes the horizontal angle and vertical angle of the gimbal, as well as the on / off state and emission frequency of the laser; the location information is used to determine the type of bionic action, and the behavioral state is used to determine the execution style of the bionic action under that type.

[0026] Specifically, the biomimetic motion sequence is a digital description of the limb movements and visual characteristics of birds of prey during their hunting flight. Multiple preset biomimetic motion sequences correspond to different deterrence tactics, such as simulating the behavior of birds of prey circling and surveying their airspace, high-speed swooping attacks, or sudden side-attacks. Each keyframe defines the azimuth and pitch angle the gimbal should point at a specific time, as well as whether the laser is activated and at what frequency. Executing these keyframes sequentially along the timeline creates a coherent biomimetic visual animation. Positional information (especially distance) determines the distance between the bird and the device; different tactical actions should be selected at different distances to achieve the best visual deterrence effect. Behavioral state determines the execution style superimposed on this tactical action. For example, when the bird target is 150 meters from the device and in flight, the system selects a high-altitude circling motion sequence as the base type and superimposes a tracking execution style, causing the gimbal to follow the target while simulating circling motion.

[0027] In one specific embodiment, the biomimetic action sequence is pre-generated and stored in the system's action sequence library in the following manner.

[0028] Each biomimetic motion sequence consists of 20 to 50 keyframes, with time intervals ranging from 100ms to 500ms between adjacent keyframes. The time interval is determined based on the intensity of the motion: intense actions (such as a side attack) use a short interval of 100ms, while gentle actions (such as high-altitude hovering) use a long interval of 500ms. The data structure of each keyframe includes the following fields: timestamp (relative time from the start of the sequence, in milliseconds), gimbal horizontal angle (in degrees, representing the target angle of the gimbal in the horizontal plane), gimbal vertical angle (in degrees, representing the target angle of the gimbal in the pitch direction), laser on / off status (Boolean value, 1 for on, 0 for off), and laser emission frequency (in kHz, representing the repetition frequency of the laser pulses).

[0029] Taking the dive attack sequence as an example, this sequence consists of 40 keyframes, with a total duration of 5 seconds and an interval of 125ms between adjacent keyframes. The angular variation follows this pattern: the horizontal angle changes linearly from the target's initial azimuth to a 15° deviation from the target's real-time azimuth, with a horizontal angular velocity of 10° / s in the first half of the sequence and accelerating to 30° / s in the second half; the vertical angle changes linearly from +10° (looking up) to -20° (looking down), simulating the flight trajectory of a raptor diving from high altitude. The laser's emission frequency is 5kHz in the first 10 frames of the sequence, gradually increasing to 12kHz in frames 11-20, and further increasing to 20kHz in frames 21-40, simulating the physical characteristic that the wing flapping frequency of a raptor increases with dive speed during a dive.

[0030] The high-altitude circling sequence consists of 30 keyframes, totaling 10 seconds in duration, with approximately 333ms between adjacent keyframes. The horizontal angle rotates uniformly from 0° to 360°, simulating the trajectory of a raptor circling once in the air; the vertical angle is fixed at +15° (looking up), simulating the raptor maintaining a high-altitude circling posture in the upper atmosphere. The laser is on throughout all keyframes, with a constant emission frequency of 10kHz, simulating the continuous visual signals emitted by the raptor.

[0031] The lateral assault sequence consists of 20 keyframes, totaling 2 seconds in duration, with 100ms intervals between adjacent keyframes. Its horizontal angle rapidly swings within ±25° of the target's azimuth, at a frequency of 3Hz; the vertical angle is fixed at 0° (horizontal orientation), directly pointing at the target's altitude. The laser is on throughout all keyframes, with a constant emission frequency of 15kHz.

[0032] Each biomimetic action sequence is stored in the system's non-volatile memory in JSON format. Each sequence contains fields such as sequence name, total sequence duration, and keyframe array. When the system starts, all action sequences are loaded into memory. During the driving task, the appropriate sequence is selected based on the target's location information and behavior status. The system then parses the keyframe data frame by frame to generate gimbal control commands, laser control commands, and MEMS galvanometer control commands.

[0033] Step S30: Determine the scanning parameters of the MEMS galvanometer; the scanning parameters are used to control the synchronous deflection of the MEMS galvanometer in the horizontal and vertical directions, so that the laser beam forms an elliptical scanning trajectory at the location of the bird target.

[0034] Specifically, the MEMS galvanometer employs a dual-axis MEMS micromirror with a mirror size of 2mm × 2mm, a scanning frequency of 10-50Hz (simulating the flapping frequency of bird wings at 3-20Hz), and a scanning angle of ±5°. The driving circuit uses a high-voltage amplifier to amplify the control signal (0-5V) to the driving voltage (0-150V). The scanning mode is a combination of sawtooth wave scanning (horizontal direction) and sine wave scanning (vertical direction), synthesizing an elliptical trajectory to simulate the flapping effect of wings. After the laser is reflected by the MEMS galvanometer, a dynamic elliptical scanning spot is formed at the location of the bird target. The specific dimensions of the major and minor axes of the spot are calculated and determined in real time based on the target distance and scanning angle. In this application, the scanning frequency of the MEMS galvanometer is set to 10-50Hz, matching the 3-20Hz flapping frequency of raptor wings, making the dynamic characteristics of the laser spot visually close to the frequency range of real raptor wing flapping, enhancing the visual deterrent effect on birds. The galvanometer scanning frequency is much higher than the motion frequency of the gimbal; the superposition of the two can simultaneously achieve macroscopic motion simulation and microscopic dynamic spot effect.

[0035] Step S40: Generate biomimetic optical commands based on the target biomimetic action sequence and the scanning parameters of the MEMS galvanometer.

[0036] Specifically, the biomimetic optical commands integrate the target biomimetic motion sequence and MEMS galvanometer scanning parameters into a complete control command set. This command set includes three parts: gimbal motion control, laser on / off control, and MEMS galvanometer scanning control. The gimbal motion control part includes the horizontal and vertical angles for each keyframe; the laser control part includes the on / off state and emission frequency for each keyframe; and the MEMS galvanometer control part includes parameters such as horizontal deflection angle, vertical deflection angle, and scanning frequency. This control command set is generated in a structured data format, facilitating subsequent parsing and execution by the control module. The command generation process must ensure that all parameters remain synchronized on the timeline. For example, when executing a dive attack motion sequence, when the gimbal rotates to the angle position specified in the 10th frame, the laser should simultaneously turn on and emit at a frequency of 20kHz, and the MEMS galvanometer should simultaneously start elliptical scanning, with the three working together to complete a complete biomimetic motion representation.

[0037] Step S50: Determine the type and transmission method of the acoustic guidance signal according to the body size category; wherein, if the body size category is a small bird, the acoustic guidance signal is an ultrasonic signal and the transmission method is pulse transmission; if the body size category is a medium-sized bird, the acoustic guidance signal is a predator call signal and the transmission method is continuous playback, and the volume of the predator call signal is determined according to the distance between the bird target and the speaker array; if the body size category is a large bird, the acoustic guidance signal is a low-frequency warning sound signal and the transmission method is continuous transmission.

[0038] Specifically, ultrasonic signals are inaudible to humans, but have a strong stimulating effect on small birds without causing significant noise pollution to the surrounding environment. Pulsed transmission creates intermittent sound pressure changes, preventing birds from adapting to the sound. For example, for a 15cm sparrow (a small bird), the system uses a 40kHz ultrasonic signal, transmitted in pulses lasting 200ms with 1-second intervals. Predator calls utilize the natural fear of predator calls in medium-sized birds; continuous playback maintains a sustained deterrent atmosphere, and volume adjustment ensures the signal effectively reaches the target location without wasting energy. For example, for a 30cm pigeon (a medium-sized bird), the system plays a falcon call. When the pigeon is 50 meters from the speaker array, the volume is set to 75dB; when the pigeon is 20 meters away, the volume automatically decreases to 65dB to avoid excessive sound pressure at close range. Low-frequency warning signals have strong penetrating power and vibration, attracting the attention of large birds and triggering their avoidance responses. For example, for eagles (large birds) with a wingspan of more than 1 meter, the system uses a low-frequency warning sound of 300 Hz, which can be effectively propagated in complex terrain by taking advantage of its strong diffraction ability.

[0039] Step S60: Determine the frequency band control parameters of the acoustic guidance signal; wherein, the frequency band control parameters are used to form directional beams in the frequency bands of the acoustic guidance signal that are higher than a preset frequency threshold, and to transmit the frequency bands that are lower than the preset frequency threshold in an omnidirectional manner.

[0040] Specifically, different frequency bands of acoustic signals possess different physical propagation characteristics. High-frequency signals have excellent directionality, making them suitable for directional beaming and focused emission, concentrating sound energy onto the area where birds are located and increasing the local sound pressure level. Low-frequency signals have strong diffraction capabilities and good diffraction performance; when emitted omnidirectionally, they can create a background warning sound field over a wide range, allowing birds to perceive the acoustic signal even behind obstacles. By controlling frequency band parameters to achieve differentiated transmission methods across different frequency bands, the needs of both directional deterrence and wide-area deterrence can be met.

[0041] In this embodiment, the preset frequency threshold is determined based on the physical parameters of the speaker array. The speaker array adopts a 4×4 layout (16 units), with a spacing of 10cm between adjacent speaker units. According to the phased array principle, the speaker array can effectively directionally control sound waves with wavelengths greater than twice the unit spacing. That is, sound waves with frequencies below approximately 1700Hz (sound speed 340m / s divided by 2×0.1m) mainly exhibit omnidirectional radiation characteristics, while sound waves with frequencies above this threshold can be directionally emitted through beamforming. Therefore, in this embodiment, the preset frequency threshold is set to 2kHz. The frequency band above 2kHz in the acoustic guidance signal (such as the 3-5kHz component in the predator call signal) is directionally emitted through a delay summation beamforming algorithm: the main processor calculates the distance difference from each speaker unit to the target position and converts it into a delay time. Each unit emits sound waves sequentially according to the set delay time, so that the sound waves emitted by each unit are superimposed in phase at the target position, forming a directional beam pointing towards the target, with a beamwidth of approximately 20°-30°. The acoustic guidance signal, with frequencies below 2kHz (such as the 200-500Hz component of a low-frequency warning sound), is emitted omnidirectionally, utilizing the diffraction characteristics of the low-frequency signal to create a wide-area sound field covering the area where the birds are located. The combined sound pressure level of the directional beam and the omnidirectional sound field reaches the preset volume value at the target location.

[0042] Step S70: Generate acoustic auxiliary commands based on the type, transmission method, volume, and frequency band control parameters of the acoustic guidance signal.

[0043] Specifically, acoustic assist commands integrate various acoustic guidance-related parameters into formatted control data to drive the speaker array to emit acoustic signals in a predetermined manner. These commands include signal waveform data, emission timing control, output power settings, and beam pointing angles, ensuring the speaker array can accurately reproduce the required acoustic guidance signal. For example, for medium-sized birds, the acoustic assist commands include an audio waveform file of the predator's call (MP3 format, 128kbps bitrate), a continuous playback mode indicator, a target volume value of 65dB, and beam pointing angles (30° horizontal, -5° vertical). The speaker array interprets these commands and drives each unit to emit sound waves according to the set delay parameters.

[0044] In step S80, the gimbal, laser, and MEMS mirror are controlled to execute the biomimetic optical commands to simulate raptor attack behavior, and the speaker array is controlled to execute the acoustic auxiliary commands.

[0045] Specifically, the execution of biomimetic optical commands involves the coordinated action of three components: a gimbal, a laser, and a MEMS galvanometer. The gimbal, acting as a platform, simulates the overall changes in the raptor's body posture, i.e., its flight trajectory and orientation changes in the air. The laser's on / off state and emission frequency simulate the changes in brightness and flickering rhythm of reflective points on the raptor's body during wing flapping. The MEMS galvanometer's scanning generates dynamically moving light spots in a localized area near the bird's target location, simulating the localized light spot jittering effect caused by light reflection at the edges of the raptor's wings or claws during high-speed movement. The motion trajectories of the three components are strictly synchronized on the timeline according to the definition of keyframes in the biomimetic action sequence, and are superimposed to form a complete visual image of the raptor attack. For example, at t=0, the gimbal rotates horizontally towards the target at a speed of 8° / s, while simultaneously diving downwards at a speed of 6° / s; the laser alternately switches on and off at a frequency of 10Hz (50ms on, 50ms off); and the MEMS galvanometer performs an elliptical scan at a frequency of 50Hz. The three elements work together to create a complete animation of an eagle swooping down. The loudspeaker array emits corresponding acoustic guidance signals according to acoustic auxiliary commands, achieving coordinated optical and acoustic driving.

[0046] In some embodiments, when a bird target is detected within a preset monitoring area, acquiring the bird target's location information, size category, and behavioral status includes: The radar sensor is controlled to transmit detection signals to the monitoring area and receive echo signals. Based on the echo signals, the distance, speed, angle and echo cross-section information of the moving target are obtained, and radar features are generated.

[0047] Specifically, the radar sensor uses millimeter-wave or microwave frequency signals to calculate the target's distance information by the time difference between the transmitted and echo signals, extracts the target's velocity information using the Doppler effect, and obtains angle information by analyzing the phase difference of the received signals through an array antenna. The echo cross-section is related to the target's material, shape, and size; different types of target objects have different echo cross-section characteristic values. This information can be used to initially distinguish between birds, drones, or other moving objects. For example, the radar sensor uses a 24GHz FMCW radar module with a transmit power of 12dBm, a detection range of 10-100 meters, a range resolution of 0.5 meters, and a velocity resolution of 0.1 m / s. When the radar detects a target at a distance of 50 meters, a velocity of 5 m / s, a horizontal angle of 30°, and an RCS of 0.01 m², it generates a radar feature vector [50m, 5m / s, 30°, 0.01m²] containing four dimensions: distance, velocity, angle, and RCS, which serves as input data for subsequent multi-sensor fusion identification.

[0048] When the distance information and speed information are both greater than the corresponding preset detection threshold, the acoustic sensor is controlled to collect bird call signals in the monitoring area and extract acoustic features from the bird call signals; the image sensor is controlled to collect color images of the monitoring area and extract visual features from the color images; and the infrared sensor is controlled to collect thermal images of the monitoring area and extract infrared features from the thermal images.

[0049] Specifically, distance and velocity thresholds are set to exclude interference signals from non-bird targets that are too far away or too slow, such as fluttering leaves or small animals crawling on the ground. For example, a distance threshold of 10 meters and a velocity threshold of 0.5 m / s will only trigger subsequent sensor acquisition if a target simultaneously meets the conditions of being more than 10 meters away and having a velocity greater than 0.5 m / s. When the radar detects a target at a distance of 50 meters and a velocity of 5 m / s that meets the above conditions, a GPIO interrupt signal triggers the acoustic sensor, image sensor, and infrared sensor to start synchronously, thus avoiding power consumption and data redundancy caused by prolonged continuous operation of the sensors. Acoustic features can be extracted from both the time and frequency domains, including parameters such as short-time energy, zero-crossing rate, power spectral density, and frequency centroid, as well as Mel-frequency cepstral coefficients (MFCC), for example, extracting a 13-dimensional MFCC feature vector. Visual features are extracted from images using methods such as histogram of oriented gradients or activation values ​​of intermediate layers in convolutional neural networks, for example, extracting a 128-dimensional visual feature vector using the backbone network of YOLOv8n (CSPDarknet). Infrared features reflect the distribution pattern of target surface temperature. Birds have a constant body temperature and a significant temperature difference with the surrounding environment, resulting in recognizable contour features in thermal images. For example, statistical features such as the average temperature, maximum temperature, minimum temperature, and temperature gradient of the target area can be extracted.

[0050] The radar features, acoustic features, visual features, and infrared features are weighted and fused to obtain a fused feature vector. The fused feature vector is then input into the target detection model to identify whether the moving target is a bird target and to obtain the location and species information of the bird target.

[0051] Specifically, weighted fusion refers to assigning different weight coefficients to feature vectors of different modalities and then concatenating or splicing them. The weights are dynamically determined based on the reliability of each sensor under specific environmental conditions. For example, under sunny midday conditions (sufficient light), the weight of visual features is set to 0.4, radar features to 0.3, infrared features to 0.2, and acoustic features to 0.1; under nighttime conditions, the weight of infrared features is increased to 0.4, the weight of visual features is decreased to 0.1, the weight of radar features remains at 0.3, and the weight of acoustic features is 0.2. After weighting, the features are concatenated to form a 256-dimensional fused feature vector, which is input into the YOLOv8n target detection model (optimized with TensorRT FP16) to identify whether the moving target is a bird (confidence threshold 0.5) and outputs the bird species label (e.g., "sparrow") and three-dimensional spatial coordinates.

[0052] In this embodiment, the specific composition of the fused feature vector is as follows: the radar feature vector is 32-dimensional, including target distance (1-dimensional), velocity (1-dimensional), horizontal angle (1-dimensional), vertical angle (1-dimensional), echo cross section (1-dimensional), and the statistical characteristics of the above parameters (mean, variance, maximum value, minimum value, a total of 4 dimensions × 5 parameters = 20 dimensions), as well as frequency domain characteristics such as peak frequency and spectral width of the Doppler spectrum (a total of 12 dimensions).

[0053] The acoustic feature vector is 64-dimensional, including 13-dimensional Mel frequency cepstral coefficients (MFCC) and their first and second differences (39 dimensions in total), short-time energy (1 dimension), zero-crossing rate (1 dimension), spectral centroid (1 dimension), spectral bandwidth (1 dimension), spectral roll-off point (1 dimension), and the mean and variance statistics of the above parameters in 5 consecutive frames (20 dimensions in total).

[0054] The visual feature vector is 128-dimensional and is obtained by global average pooling of the feature map output from the last pooling layer of the YOLOv8n backbone network (CSPDarknet). It contains texture features, edge features and shape features of the bird target region.

[0055] The infrared feature vector is 32-dimensional, including the average temperature (1-dimensional), maximum temperature (1-dimensional), minimum temperature (1-dimensional), temperature standard deviation (1-dimensional), temperature gradient (temperature change rate in the horizontal and vertical directions, 2-dimensional in total), and the statistics of each interval of the temperature distribution histogram of the target area (26-dimensional in total).

[0056] The four feature vectors mentioned above are each L2 normalized, and then the fusion weights for each modality are calculated using an attention mechanism. The attention weights are calculated as follows: each modality feature vector is input into a fully connected layer (output dimension 32), activated by ReLU, and then input into a softmax layer, outputting four weight coefficients (summing up to 1). Each modality feature vector is multiplied by its corresponding weight coefficient and then concatenated to form a 256-dimensional fusion feature vector. Under sufficient lighting conditions, the weight coefficient for visual features is relatively high (approximately 0.4); under nighttime conditions, the weight coefficient for infrared features is relatively high (approximately 0.4); and under noisy environmental conditions, the weight coefficient for acoustic features decreases (approximately 0.05-0.1).

[0057] Based on the distance information, angle information, and the pixel area occupied by the bird target in the color image, the actual size of the bird target is estimated, and the body type of the bird target is determined in combination with the species information.

[0058] Specifically, given the target distance and sensor field of view parameters, the pixel area in the image can be converted into the actual physical area based on perspective projection geometry, thus obtaining the approximate body size of the bird target. Species information provides a standard size reference value for that bird species. By comparing the estimated size with the standard reference value, a comprehensive determination is made as to whether the target belongs to the small, medium, or large category. For example, if a target has a pixel area of ​​2500 pixels measured at a distance of 50 meters, the converted actual projected area is 0.015 m², and the species identification result is "pigeon" (standard size reference value is approximately 0.02 m²), it is comprehensively determined to be a medium-sized bird. The determination of the size category directly affects the selection of the subsequent acoustic guidance signal type.

[0059] The pixel displacement of the bird target in multiple consecutive frames is obtained from the color image. The movement speed and direction are calculated based on the pixel displacement, and the behavior state of the bird target is identified based on the movement speed and direction.

[0060] Specifically, the pixel position changes of the same bird target in multiple consecutive frames reflect its projected motion trajectory on the image plane. Combining the inter-frame time interval and the target's distance information, the pixel displacement can be converted into the motion velocity and direction vector in actual space. The temporal variation pattern of the motion velocity magnitude and direction is closely related to the bird's behavioral intentions, and different behavioral states can be distinguished by analyzing the velocity values ​​and trajectory smoothness. For example, if a target's pixel displacements in five consecutive frames (frame interval 100ms) are (2,3), (3,4), (2,5), (4,6), and (3,7) pixels, and combined with the calibration parameter of 50 meters (0.01 meters per pixel), the average velocity is calculated to be 1.5 m / s, the motion direction is 45° east of north, and the trajectory curvature changes frequently, indicating a foraging state.

[0061] In some embodiments, the method further includes: The acoustic sensor is controlled to collect the environmental noise signal of the monitoring area, and the preset detection threshold is dynamically adjusted according to the environmental noise signal: when the environmental noise signal is higher than the preset high noise threshold, the preset detection threshold is increased; when the environmental noise signal is lower than the preset low noise threshold, the preset detection threshold is decreased.

[0062] Specifically, ambient noise levels affect the radar sensor's ability to detect weak targets. When ambient noise increases, the background noise floor in the received signal rises, reducing the signal-to-noise ratio of the target echo signal. In this case, the detection threshold needs to be increased to avoid excessive false alarms triggered by noise. Conversely, in quiet environments with a lower noise floor, the detection threshold can be lowered to improve the sensitivity to weak target signals. Dynamic threshold adjustment allows the sensor to maintain reasonable detection performance under different acoustic environmental conditions. For example, a preset high noise threshold of 60dB and a preset low noise threshold of 30dB can be used. When the acoustic sensor detects ambient noise of 65dB (e.g., during aircraft takeoff and landing near an airport runway), the velocity detection threshold can be increased from 0.5m / s to 0.6m / s (a 20% increase); when the ambient noise is 25dB (e.g., in a farmland at night), the velocity detection threshold can be decreased to 0.45m / s (a 10% decrease) to improve the sensitivity to weak target signals.

[0063] The temperature sensor is controlled to collect the ambient temperature, and the thermal image collected by the infrared sensor is temperature-corrected based on the ambient temperature.

[0064] Specifically, infrared sensors detect the infrared energy radiated by the target itself, which is related to the temperature difference between the target and the ambient temperature. Changes in ambient temperature affect the accuracy of the detector's absolute temperature measurement; for example, background radiation increases in hot weather, while the detector's dark current drifts in cold weather. Temperature correction maps the raw reading of each pixel in the thermal image to the true temperature value after ambient temperature compensation, improving the accuracy of subsequent infrared feature extraction. For example, when the temperature sensor acquires an ambient temperature of 35°C, the infrared detector's dark current correction coefficient is 0.98, and the background radiation compensation value is +2°C, correcting the raw reading of 298K to a true temperature value of 300K; when the ambient temperature is -5°C, the dark current correction coefficient is 1.02, and the background radiation compensation value is -1°C, correcting the raw reading of 268K to a true temperature value of 267K, ensuring the accuracy of infrared feature extraction.

[0065] In this embodiment, the ambient noise signal is acquired at a frequency of 1 Hz, with each acquisition lasting 1 second. The acoustic sensor performs an FFT transform on the acquired time-domain signal to calculate the total energy within the 100 Hz-20 kHz frequency band as the ambient noise level (in dB). A preset high-noise threshold of 60 dB and a preset low-noise threshold of 30 dB are established. When the ambient noise level is higher than 60 dB, the speed detection threshold is linearly increased from 0.5 m / s to 0.65 m / s (a 30% increase), and the distance detection threshold is linearly increased from 10 m to 13 m (a 30% increase). When the ambient noise level is lower than 30 dB, the speed detection threshold is linearly decreased to 0.4 m / s (a 20% decrease), and the distance detection threshold is linearly decreased to 8 m (a 20% decrease). Dynamic adjustment employs a first-order low-pass filter to avoid detection instability caused by sudden threshold changes.

[0066] Temperature calibration employs a two-point calibration method. Before the equipment leaves the factory, the infrared sensor is pointed at two blackbody radiation sources with known temperatures of 0°C and 50°C, respectively. The raw digital values ​​output by the sensor are recorded, establishing a linear mapping relationship between temperature and the raw reading: T_real = a × T_raw + b, where a and b are calibration coefficients. During actual operation, the temperature sensor collects the ambient temperature T_env in real time, and the calibration coefficients are compensated based on the ambient temperature: a_comp = a × (1 + α × (T_env - 25°C)), b_comp = b × (1 + β × (T_env - 25°C)), where α and β are compensation coefficients determined by the temperature drift parameters provided by the infrared detector at the factory. After ambient temperature compensation, the raw reading of each pixel in the thermal image is mapped to the compensated real temperature value, and then infrared features are extracted.

[0067] In some embodiments, estimating the actual size of the bird target includes: The distance d between the bird target and the gimbal is calculated based on the distance information obtained by the radar sensor. The bird target's pixel area A in the color image is used as the bird's projected area S. The horizontal field of view θ of the image sensor and the width W of the color image are combined with the pixel area A. The bird's projected area S is calculated using the formula S = A × (d × tan(θ / 2) / (W / 2))². The bird's projected area S is used as the estimated actual size of the bird target.

[0068] Specifically, the physical meaning of this formula is as follows: given the field of view angle θ and image width W, the relationship between the actual spatial size of each pixel in the image and the distance d can be calculated. The term d × tan(θ / 2) / (W / 2) represents the actual width value corresponding to each pixel at distance d. Squaring this value and multiplying it by the pixel area occupied by the target yields the projected area of ​​the target on the plane perpendicular to the line of sight. This projected area approximately reflects the cross-sectional area of ​​the bird's body, and body size categories are classified based on the range of this area value. The distance information in the formula is provided by a radar sensor, and its measurement accuracy is not affected by ambient lighting conditions.

[0069] For example, assume the radar measures the target distance as d = 50 meters, the image sensor's horizontal field of view is θ = 90°, the image width is W = 1920 pixels, and the target detection box area is A = 2500 pixels. Substituting into the formula: S = 2500 × (50 × tan(45°) / (1920 / 2))² = 2500 × (50 × 1 / 960)² =2500 × (0.0521)² = 2500 × 0.00271 = 6.78 × 10 - ³ m² The calculated area S ≈ 0.0068m², which is less than 0.01m², indicating a small bird (such as a sparrow). If the pixel area of ​​the other target is A = 15000 pixels, the calculated area S ≈ 0.041m², which is between 0.01m² and 0.05m², indicating a medium-sized bird (such as a pigeon). If the pixel area of ​​the other target is A = 30000 pixels, the calculated area S ≈ 0.081m², which is greater than 0.05m², indicating a large bird (such as an eagle).

[0070] In this embodiment, the thresholds for small (0.01 m²) and large (0.05 m²) bird size categories are determined based on statistical data of the body cross-sectional area of ​​common birds. According to ornithological measurements, the body cross-sectional area of ​​the sparrow (Passer montanus) is approximately 0.005-0.008 m², and that of the swallow (Hirundo rustica) is approximately 0.006-0.009 m², both less than 0.01 m², and thus classified as small birds. The body cross-sectional area of ​​the pigeon (Columba livia) is approximately 0.015-0.025 m², that of the crow (Corvus torquatus) is approximately 0.02-0.035 m², and that of the magpie (Pica) is approximately 0.05-0.05 m². The body area of ​​a bird is approximately 0.018-0.028 m², all between 0.01 m² and 0.05 m², classifying it as a medium-sized bird; the body cross-sectional area of ​​a hawk (Accipitridae) is approximately 0.06-0.12 m², a falcon (Falconidae) is approximately 0.05-0.09 m², and an eagle (Aquila) is approximately 0.10-0.20 m², all greater than 0.05 m², classifying them as large birds.

[0071] The above thresholds can be adaptively adjusted according to the actual application scenario. In airport scenarios, since large birds (such as eagles and geese) pose a greater threat to flight safety, the large bird threshold can be lowered to 0.04 m², allowing more birds to be classified as large and prioritized for treatment. In farmland scenarios, since small birds (such as sparrows) cause greater damage to crops, the small bird threshold can be raised to 0.015 m², allowing more birds to be classified as small and triggering ultrasonic deterrence.

[0072] In some embodiments, identifying the behavioral state of a bird target based on its movement speed and direction includes: When the movement speed is lower than the first speed threshold, the behavior state is determined to be stationary; when the movement speed is between the first speed threshold and the second speed threshold and the movement trajectory is irregular, the behavior state is determined to be foraging; when the movement speed is higher than the second speed threshold and the movement trajectory is smooth, the behavior state is determined to be flying.

[0073] Specifically, the first and second speed thresholds are empirical values ​​determined based on statistical data from bird biomechanics, used to distinguish different speed ranges. Birds at rest are not completely still; they may exhibit slight body swaying or head movement, but the overall displacement is minimal. Therefore, a speed below the first threshold qualifies them as stationary. Foraging behavior is characterized by slow movement on the ground or vegetation, accompanied by frequent changes in direction and pauses. Their speed falls between the two thresholds, and their trajectory exhibits significant curvature and rate of change of direction. Flight is characterized by continuous, stable movement at relatively high speeds with gentle changes in heading and a smooth trajectory.

[0074] For example, the first velocity threshold is set to 0.5 m / s, and the second velocity threshold is set to 2 m / s. The displacement of a target over 10 consecutive frames (100 ms interval) is (0,0), (0,0), (1,0), (0,0), (0,0), (0,1), (0,0), (0,0), (0,0), (0,0), (0,0) pixels. Combined with the distance calibration parameter (0.005 meters per pixel), the calculated average velocity is 0.1 m / s, which is lower than the first velocity threshold. Therefore, the target is considered stationary, and the bird may be perched or observing its surroundings.

[0075] The displacement of the other target in 10 consecutive frames is (2,3), (3,4), (2,5), (4,6), (3,7), (1,4), (5,3), (2,2), (4,5), (3,6) pixels, with an average speed of 1.8 m / s (between 0.5 m / s and 2 m / s). The trajectory curvature changes frequently and the direction is discontinuous, indicating that the bird is in a foraging state and is slowly moving on the ground in search of food.

[0076] Another target's displacement in 10 consecutive frames is (10,5), (11,6), (10,5), (12,5), (11,6), (10,7), (11,5), (12,6), (10,5), (11,6) pixels, with an average speed of 3.5 m / s (higher than the second speed threshold). The trajectory is smooth and the direction is stable (continuously flying in the north-northeast direction), so it is determined to be in flight.

[0077] In some embodiments, the biomimetic motion sequence includes at least a high-altitude hovering motion sequence, a dive attack motion sequence, and a lateral assault motion sequence; in the high-altitude hovering motion sequence, the gimbal continuously rotates in the horizontal direction, and the laser continuously emits light; in the dive attack motion sequence, the gimbal descends vertically while accelerating horizontally, and the laser emission frequency is higher at the end of the dive than at the beginning of the dive; in the lateral assault motion sequence, the gimbal rapidly swings horizontally, and the laser continuously emits light.

[0078] The step of selecting a target bionic action sequence from a variety of preset bionic action sequences based on the bird target's location information and behavioral state specifically includes: When the distance between the bird target and the gimbal is greater than the first preset value, the high-altitude circling action sequence is selected; when the distance between the bird target and the gimbal is between the first preset value and the second preset value, the dive attack action sequence is selected; when the distance between the bird target and the gimbal is less than the second preset value, the lateral attack action sequence is selected.

[0079] Specifically, when the behavior state is foraging, the target bionic action sequence adopts a strong execution style; when the behavior state is flying, the target bionic action sequence adopts a tracking execution style; and when the behavior state is stationary, the target bionic action sequence adopts a default execution style.

[0080] Specifically, the high-altitude circling sequence simulates the flight posture of a raptor circling and patrolling at high altitudes. The gimbal performs continuous uniform or variable-speed rotation in the horizontal direction, and the laser continuously emits a laser beam, which forms a dynamic light spot under the modulation of the MEMS galvanometer. This action is suitable for long-range deterrence, making birds aware of the presence of raptor activity in the area. The dive attack sequence simulates the attack posture of a raptor swooping down from high altitude after spotting prey. The gimbal gradually decreases its pitch angle in the vertical direction while accelerating its rotation towards the target position in the horizontal direction. The launch frequency increases at the end of the dive to enhance the sense of approach. The lateral attack sequence simulates the attack posture of a raptor rapidly passing by from the side. The gimbal performs rapid reciprocating swings in the horizontal direction, suitable for close-range chasing to force birds to flee quickly. The first and second preset values ​​constitute the distance segment boundaries centered on the device, and different distance intervals correspond to different tactical actions.

[0081] For example, the first preset value is set to 30 meters, and the second preset value is set to 10 meters.

[0082] Example 1: When the radar detects a bird target 150 meters away from the device, the system selects a high-altitude circling sequence. This sequence consists of 30 keyframes, lasting 10 seconds. The gimbal rotates horizontally from 0° to 360° at a constant speed (simulating a full circle), while maintaining a vertical angle of +10° (looking up at the sky). The laser continuously emits light, and the MEMS galvanometer scans at a frequency of 50Hz, forming a continuous dynamic light spot to transmit a signal to distant birds that "there is a bird of prey in the area."

[0083] Example 2: When the radar detects a bird target 25 meters away from the device (between 10 and 30 meters), the system selects a dive attack sequence. This sequence consists of 40 keyframes and lasts for 5 seconds. The gimbal's horizontal angle accelerates from the target's initial azimuth (30°) to the target's real-time azimuth (35°), while the vertical angle gradually decreases from +5° to -15° (simulating a dive). The laser's emission frequency gradually increases from 5kHz at the beginning of the dive to 20kHz at the end of the dive, simulating the visual effect of a raptor's wings flapping and accelerating during a dive.

[0084] Example 3: When the radar detects a bird target 8 meters (less than 10 meters) away from the device, the system selects a side-attack sequence. This sequence consists of 20 keyframes and lasts for 2 seconds. The gimbal's horizontal angle rapidly swings to both sides of the target's azimuth (±20°, swing frequency 3Hz), while the vertical angle is locked at the target's pitch angle (0°). The laser continuously fires, simulating the attack posture of a raptor rapidly swooping down from the side, forcing the bird to flee in an emergency.

[0085] Based on this, if the bird's behavior is foraging, the target bionic motion sequence adopts a strong execution style. For example, in Example 2 above, the gimbal rotation speed of the dive attack sequence is increased by 1.5 times (from the usual 30° / s to 45° / s), and the laser flashing frequency is increased by 1.3 times, to interrupt the bird's foraging behavior with a more violent bionic motion. If the behavior is flying, the target bionic motion sequence adopts a tracking execution style, that is, the gimbal adds the bird's movement offset to the angle of each keyframe, so that the laser beam always moves with the bird in flight. For example, if the target is flying eastward at a speed of 3 m / s, the gimbal's horizontal angle is additionally increased by about 0.5° of tracking offset when executing each keyframe. If the behavior is stationary, the default execution style is adopted, that is, the preset angle sequence of the keyframes is executed directly without adding additional modulation.

[0086] In this embodiment, when the behavior state is flight, the target bionic action sequence adopts a tracking execution style, which is implemented as follows: The tracking offset is calculated using a target motion prediction method based on Kalman filtering. The system maintains the target's state vector X = [x, y, z, vx, vy, vz]. T Where x, y, and z are the target's position coordinates in three-dimensional space, vx, vy, and vz are the target's velocity components in three directions, and T represents the matrix transpose. The prediction model is a uniform motion model: X_pred(k+1) = F × X(k), where F is the state transition matrix. The observation vector Z(k) = [d, θ_h, θ_v] T Provided by the radar sensor, where d is the range, θ_h is the horizontal angle, and θ_v is the elevation angle. The Kalman filter is updated every 100ms, outputting the predicted values ​​of the target's current position (x_pred, y_pred, z_pred) and velocity (vx_pred, vy_pred, vz_pred).

[0087] The formula for calculating the actual pointing angle of the gimbal is: Actual horizontal angle = Keyframe preset horizontal angle + θ_track_h; Actual vertical angle = keyframe preset vertical angle + θ_track_v; Where θ_track_h = arctan(vx_pred × Δt / d_pred), θ_track_v = arctan(vy_pred × Δt / d_pred), Δt is the inter-frame time interval (i.e., the time difference between adjacent keyframes), and d_pred is the predicted distance. The above tracking offset is smoothed using a first-order low-pass filter with a filter coefficient of 0.3 to avoid high-frequency jitter caused by target position measurement noise in the gimbal.

[0088] When the behavior state is foraging, the target bionic action sequence adopts a strong execution style, and its specific modulation coefficients are as follows: The angle amplitude modulation factor is 1.5, meaning that the horizontal and vertical angle swing amplitudes of the gimbal are both multiplied by 1.5. For example, in a dive attack sequence, the vertical angle changes from +10° to -20° (a change of 30°), but under a strong execution style, the change amplitude expands to 45°, i.e., from +15° to -30°. The gimbal rotation speed modulation factor is 1.3, meaning the horizontal axis rotation speed is increased from the usual 30° / s to 39° / s, and the vertical axis rotation speed is increased from the usual 20° / s to 26° / s. The laser emission frequency modulation factor is 1.5, meaning the emission frequency is increased from the usual 10kHz to 15kHz. The laser switching frequency modulation factor is 1.2, meaning the usual switching frequency is increased from 10Hz to 12Hz.

[0089] When the behavior state is stationary, the target bionic action sequence adopts the default execution style, that is, all modulation coefficients are 1.0, the gimbal directly executes according to the preset angle sequence of the key frame, and the laser executes according to the preset switching state and emission frequency, without any additional modulation.

[0090] In some embodiments, the method further includes: The system acquires light intensity, wind speed, temperature, and guidance success rate; wherein the guidance success rate is the proportion of successful guidance in historical guidance records.

[0091] When the light intensity is higher than a preset strong light threshold and the guidance success rate is lower than a preset success rate threshold, the PWM duty cycle of the laser is increased to a preset maximum value.

[0092] When the wind speed is higher than the preset wind speed threshold, a preset compensation amount is added to the current PWM duty cycle.

[0093] When the temperature is lower than the preset low temperature threshold, the heating device is activated and the PWM duty cycle of the laser is reduced.

[0094] When the guidance fails for a preset number of consecutive times, the system switches from the current bionic action sequence to another bionic action sequence and regenerates the bionic optical instructions.

[0095] Specifically, light intensity directly affects the visibility of the laser beam in the air. In strong light environments, high ambient brightness reduces the contrast of the laser spot, affecting birds' perception of it. In this case, increasing the PWM duty cycle can increase the effective brightness of the laser to compensate for the decreased visibility. When wind speeds are high, there are many floating particles in the air, causing scattering and attenuation of the laser beam as it travels through the atmosphere. Increasing the PWM duty cycle provides compensating power to ensure the laser spot still has sufficient visibility upon reaching the target location. In low-temperature environments, the performance of internal laser components may drift. Reducing the PWM duty cycle can control the heat generated by the laser and, in conjunction with a heating device, maintain the equipment's operating temperature within the normal range. The guidance success rate statistics reflect the actual effectiveness of the current deterrence strategy. Consecutive failures indicate that birds have adapted to the current biomimetic action sequence or that the sequence is ineffective for that particular bird species. Switching to other biomimetic action sequences can break the birds' expected adaptation.

[0096] For example, if the light sensor detects a light intensity of 60,000 lux (exceeding the preset strong light threshold of 50,000 lux) and the historical guidance success rate is 75% (below the preset success rate threshold of 80%), the system will increase the laser's PWM duty cycle from the current 60% to the preset maximum value of 100% to enhance the laser's visibility in strong light environments.

[0097] The wind speed sensor detected a wind speed of 18 m / s (exceeding the preset wind speed threshold of 15 m / s). The system increases the preset compensation by 20% (e.g., from 60% to 80%) based on the current PWM duty cycle to overcome laser attenuation caused by atmospheric scattering.

[0098] The temperature sensor detected an ambient temperature of -15°C (below the preset low temperature threshold of -10°C). The system then activated the heating device (10W power) to heat and maintain the temperature of the laser. At the same time, the PWM duty cycle of the laser was reduced from the current 60% to 50% to prevent the laser from overheating in the low temperature environment.

[0099] The guidance record statistics show that after three consecutive guidance failures (the birds did not leave the monitoring area or returned quickly after being guided), the system switches from the current biomimetic action sequence to another biomimetic action sequence, such as from the "dive attack action sequence" to the "lateral attack action sequence", and regenerates biomimetic optical instructions to break the birds' adaptive expectations.

[0100] In some embodiments, the method further includes: When executing the bionic optical command and the acoustic auxiliary command, the bionic optical command is executed first, and the acoustic auxiliary command is executed after a preset time interval.

[0101] Specifically, optical signals travel at the speed of light, and birds can perceive them almost instantly when the laser is turned on, over a distance of several meters to hundreds of meters. Acoustic signals, however, travel at approximately 340 meters per second in the air, exhibiting a perceptible propagation delay at longer distances. By setting a time difference between executing optical commands first and acoustic commands later, the acoustic and optical signals arrive at the bird's location at roughly the same time, achieving synchronized arrival of audiovisual signals and enhancing the synergistic effect of multimodal stimulation. The preset time interval can be calculated by dividing the distance between the bird target and the gimbal by the speed of sound. For close-range deterrence scenarios, this preset time interval can be shortened or set to zero.

[0102] For example, when the bird target is 170 meters away from the device, the time required for the acoustic signal to travel from the device to the target location is approximately 170 / 340 = 0.5 seconds. The system is set to a preset time interval of 0.5 seconds, meaning that the bionic optical command is executed first, followed by the acoustic auxiliary command 0.5 seconds later. This ensures that the laser light signal and the acoustic signal arrive at the bird target location at 170 meters simultaneously. The bird sees the visual signal of the raptor and hears the corresponding acoustic signal at the same time, enhancing the synergistic effect of the deterrent stimulus.

[0103] When the bird target is 50 meters away from the device, the time required for the acoustic signal to propagate is approximately 50 / 340 ≈ 0.15 seconds. The system accordingly shortens the preset time interval to 0.15 seconds. When the bird target is less than 10 meters away from the device, the acoustic signal propagation delay is less than 0.03 seconds. The human ear and the bird's auditory system can hardly distinguish this time difference, so the system can set the preset time interval to zero, that is, the bionic optical command and the acoustic auxiliary command are executed simultaneously.

[0104] In some embodiments, the method further includes: The system monitors the operating status of each sensor; when the image sensor malfunctions, it switches to target detection using the radar sensor and the infrared sensor; when the infrared sensor malfunctions, it switches to target detection using the radar sensor and the image sensor; when both the image sensor and the infrared sensor malfunction, it switches to target detection using only the radar sensor; when the laser malfunctions, it switches to acoustic guidance using only the speaker array.

[0105] Specifically, sensor operational status monitoring is achieved by reading the self-test register status of each sensor, communication handshake responses, or signal validity verification. When the image sensor malfunctions and cannot provide color image data, target detection can still be maintained by combining distance, speed, and angle information from the radar sensor with temperature distribution information from the infrared sensor. When the infrared sensor malfunctions, detection relies on both the radar and image sensors; the image sensor can still perform visual recognition tasks independently under good lighting conditions. When both sensors malfunction, detection relies solely on the radar sensor. In this case, it is impossible to distinguish specific bird species and behavioral states, but basic moving target identification and tracking can be performed based on the motion characteristics and scattering cross-section of the radar echo. When the laser malfunctions, the optical deterrence function fails; the speaker array can operate independently to maintain basic deterrence capabilities acoustically. Fault switching time should be controlled within 100ms to ensure guidance continuity.

[0106] For example, if the image sensor's image signal becomes invalid due to lens damage, the system status monitoring module determines the image sensor malfunction through communication timeout detection and switches to radar and infrared sensors for target detection within 50ms. At this time, the infrared sensor provides temperature distribution and contour information of the bird target, while the radar sensor provides distance, speed, and angle information of the target. The fusion of the two can still achieve effective bird target detection, but species identification is not possible.

[0107] For example, if the laser driver circuit detects an overcurrent condition, the system determines that the laser is faulty, shuts off the laser power within 80ms, and switches to acoustic guidance solely by the speaker array. At this time, acoustic guidance can still play predator calls or low-frequency warning sounds to maintain basic deterrence capabilities acoustically. Although the deterrence effect is somewhat reduced compared to the combined optical and acoustic mode, the system can still function normally.

[0108] In this embodiment, the operating status of each sensor is monitored in the following specific ways: Power supply voltage monitoring: The ADC pin of the main processor is connected to the voltage divider sampling points of the power supply lines of each sensor to collect voltage values ​​at a frequency of 10Hz. The normal voltage range is 11.5V to 12.5V (the system power supply voltage is 12V). When five consecutive sampling values ​​are all below 11V or above 13V, it is determined that the power supply voltage is abnormal, a "power failure" log is recorded, and the corresponding fault handling procedure is triggered.

[0109] Communication Status Monitoring: The main processor communicates with each sensor via I2C bus (temperature sensor, light sensor), SPI bus (radar sensor), and UART serial port (acoustic sensor, infrared sensor, image sensor). The main processor sends a heartbeat query command to each sensor every second, and the sensor should respond within 100ms of receiving the command. If no response is received after three consecutive heartbeat queries (i.e., a timeout of 300ms × 3 = 900ms), the sensor is considered to have a communication failure, a "communication failure" log is recorded, and a fault switch is initiated.

[0110] Data Quality Monitoring: The main processor verifies the validity of data collected by each sensor. For image sensors, the verification methods are: checking the CRC checksum of the image data for correctness, checking if the image resolution is still 1920×1080, and checking if the image brightness histogram is normal (excluding completely black or completely white images). For infrared sensors, the verification methods are: checking the effective pixel ratio of the thermal image and checking if the temperature value is within a reasonable range (e.g., -40°C to 85°C). For acoustic sensors, the verification methods are: checking if the root mean square value of the audio signal is zero or abnormally high, and checking for continuous clipping distortion. When 10 consecutive frames of data are determined to be abnormal, the sensor is considered faulty, a "data anomaly" log is recorded, and a fault switch is initiated.

[0111] Performance degradation monitoring: The system periodically (every 24 hours) compiles the detection performance indicators of each sensor, including target detection rate, false alarm rate, and data effectiveness rate. When a certain indicator drops by more than 20% compared to the historical average, it is determined that the sensor performance has degraded, a "performance degradation" log is recorded, and maintenance is requested.

[0112] The fault levels are classified as follows: abnormal power supply voltage and communication failure are considered serious faults, and the use of the sensor should be stopped immediately and a switch should be performed; abnormal data is considered a general fault, and a software reset should be attempted first (send a reset command and wait for 500ms). If the reset is successful, the sensor can continue to be used. If the reset fails, a switch should be performed; performance degradation is considered a minor fault, and only the log is recorded for maintenance reference. No switch should be performed.

[0113] Another embodiment of this application proposes a multidimensional bird monitoring device based on biomimetic optics, comprising: Radar sensors are used to transmit detection signals to the monitored area and receive echo signals. Acoustic sensors are used to collect environmental noise signals and bird call signals in the monitored area; An image sensor is used to acquire color images of the monitored area; An infrared sensor is used to acquire thermal images of the monitored area; Temperature sensor, used to collect ambient temperature; A light sensor is used to collect ambient light intensity. Wind speed sensor, used to collect ambient wind speed; A laser, used to emit a laser beam; MEMS galvanometers are disposed in the output optical path of the laser and are used to scan the laser beam; The gimbal supports the laser and the MEMS galvanometer. A loudspeaker array is used to emit acoustic guidance signals toward the bird target; A heating device is used to activate heating when the ambient temperature is below a preset low-temperature threshold; and The main processor is connected to the radar sensor, the acoustic sensor, the image sensor, the infrared sensor, the temperature sensor, the light sensor, the wind speed sensor, the laser, the MEMS galvanometer, the gimbal, the speaker array, and the heating device, respectively, and the main processor is configured to execute the method described in any one of the above.

[0114] Specifically, in this embodiment, the aforementioned sensors and actuators are integrated into the same housing, forming an integrated biomimetic optics-based multidimensional bird monitoring device. Radar and acoustic sensors, acting as active detection devices, emit detection signals and receive return signals, while image and infrared sensors, acting as passive receivers, collect light and thermal radiation information from the environment; these two functions complement each other. The laser is a semiconductor or solid-state laser, whose emitted laser beam is reflected by a MEMS galvanometer before exiting into external space. The MEMS galvanometer is characterized by its small size, fast response speed, and high deflection accuracy, enabling the realization of complex two-dimensional scanning patterns. The gimbal is a two-axis servo-driven gimbal, capable of independent rotation in both horizontal and vertical directions, with a large range of motion. The speaker array is a phased array or beamforming array composed of multiple speaker units, capable of controlling the direction of acoustic signal emission. A heating device is located near the laser; low-temperature start-up heating is used to maintain the laser's operating temperature within the rated range, ensuring stable laser output performance. The main processor is an embedded processor with multiple sensor interfaces and high computing power. It runs target detection algorithms and drive-away strategy control programs, and is responsible for coordinating and controlling the working timing and parameter configuration of all sensors and actuators.

[0115] For example, in a specific implementation, the device is installed on the crossarm of a power transmission tower (15 meters high), in the safety zone on both sides of an airport runway (500 meters apart), or on a utility pole near farmland. The main processor continuously monitors moving targets within a 50-meter radius using radar sensors. When a bird target is detected, image and infrared sensors are activated to collect multimodal data. After AI model recognition and decision tree algorithms select the optimal guidance strategy, the device drives the gimbal, laser, MEMS mirror, and speaker array to perform biomimetic optical guidance and acoustic-assisted guidance, effectively deterring the birds. The device is equipped with a 50W solar panel and a 12V / 100Ah lithium iron phosphate battery, supporting independent operation for 2-3 days in continuous cloudy or rainy weather.

[0116] In a specific device implementation, the model numbers and key parameters of each component are as follows: The radar sensor uses an Infineon BGT24MTR11 chip-based 24GHz FMCW radar module with an operating frequency of 24.125GHz, a transmit power of 12dBm, a detection range of 10-100 meters, a range resolution of 0.5 meters, a velocity resolution of 0.1m / s, a horizontal beamwidth of 30°, a vertical beamwidth of 15°, and a microstrip patch array antenna.

[0117] The image sensor is an OV2710 2-megapixel CMOS image sensor with a resolution of 1920×1080 and a frame rate of 30fps. It is equipped with automatic exposure and wide dynamic range (WDR) functions, with a dynamic range of ≥100dB and an adaptability to light intensity of 10-100000 lux. The lens is a 3.6mm focal length fixed lens with a horizontal field of view of 90° and a vertical field of view of 60°.

[0118] The infrared sensor uses an uncooled vanadium oxide (VOx) microbolometer infrared detector with a resolution of 384×288, a pixel size of 17μm, and a thermal sensitivity (NETD) of ≤50mK@300K. The infrared lens uses a germanium lens with a focal length of 19mm, an F number of 1.0, and a detection band of 8-14μm.

[0119] The temperature sensor uses the SHT30 digital temperature sensor with an I2C interface, a measurement range of -40°C to 85°C, an accuracy of ±0.5°C, and a resolution of 0.01°C.

[0120] The light sensor uses a BH1750 digital light intensity sensor with an I2C interface, a measurement range of 1-65535 lux, and a resolution of 1 lux.

[0121] The wind speed sensor uses a WindSonic ultrasonic anemometer, with a measurement range of 0-60 m / s and an accuracy of ±0.1 m / s.

[0122] The laser employs a 532nm semiconductor-pumped solid-state laser (DPSS) with an output power ≤5mW (Class 3R safety rating, compliant with IEC 60825-1:2014 standard), a beam divergence angle <1mrad, and is equipped with a collimating lens (50mm focal length), a beam expander (to increase the beam diameter to 5mm), and a protective window (coated with an anti-reflective coating, transmittance >99%). The laser features a constant current drive circuit with current stability ±1% and a hardware interlock switch (automatically shuts off the laser when the device tilts >15° or when personnel are detected approaching).

[0123] The MEMS galvanometer uses a biaxial MEMS micromirror with a mirror size of 2mm×2mm, a scanning frequency of 10-50Hz, a scanning angle of ±5°, and a driving circuit that uses a high-voltage amplifier (the control signal is amplified from 0-5V to the driving voltage of 0-150V).

[0124] The gimbal is a 2-axis gimbal with a horizontal rotation of ±180° and a vertical pitch of ±90°. The horizontal axis uses a harmonic reducer and a brushless DC motor (speed 0-45° / s), while the vertical axis uses a worm gear and a stepper motor (speed 0-30° / s). The positioning accuracy is ±0.5°.

[0125] The loudspeaker array is a 16-unit loudspeaker array (4×4 layout), each unit is a full-range loudspeaker (5cm in diameter, 5W power), with a frequency response of 200Hz-20kHz, sensitivity of 85dB / W / m, and a unit spacing of 10cm. Directional transmission is achieved through a delay summation beamforming algorithm.

[0126] The main processor uses the NVIDIA Jetson Orin Nano embedded computing platform, equipped with 8GB LPDDR5 memory, GPU computing power of 40 TOPS (INT8), CPU with 6 core ARM Cortex-A78AE (1.5GHz), built-in 64GB eMMC, supports SD card expansion up to 512GB, provides multiple interfaces such as USB 3.0, GPIO, I2C, SPI, UART, etc., runs Linux operating system and AI inference framework, and is equipped with YOLOv8n and EfficientNet-B0 models optimized by TensorRT.

[0127] The heating device is a PTC ceramic heater with a rated power of 10W. It is located near the laser and starts heating when the ambient temperature is below -10°C to maintain the laser's operating temperature within the range of 0°C to 40°C.

[0128] All the above components are integrated into an outdoor enclosure with an IP65 protection rating. A solar panel is installed on the top of the enclosure, and a lithium iron phosphate battery and MPPT charging controller are installed inside. The entire unit is fixed to the crossarm of a transmission tower, airport perimeter post, or farmland support frame using clamps or flanges.

[0129] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technological improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A multidimensional monitoring method for birds based on biomimetic optics, characterized in that, The method includes the following steps: When a bird target is detected within a preset monitoring area, the location information, size category, and behavioral status of the bird target are acquired; the behavioral status includes stationary, foraging, and flying. Based on the location information and behavioral state of the bird target, a target biomimetic action sequence is selected from a variety of preset biomimetic action sequences; wherein, the target biomimetic action sequence consists of keyframes at consecutive time points, and each keyframe includes the horizontal angle and vertical angle of the gimbal, as well as the on / off state and emission frequency of the laser; the location information is used to determine the type of biomimetic action, and the behavioral state is used to determine the execution style of the biomimetic action under that type; Determine the scanning parameters of the MEMS galvanometer; the scanning parameters are used to control the synchronous deflection of the MEMS galvanometer in the horizontal and vertical directions, so that the laser beam forms an elliptical scanning trajectory at the location of the bird target; Generate biomimetic optical commands based on the target biomimetic action sequence and the scanning parameters of the MEMS galvanometer; The type and transmission method of the acoustic guidance signal are determined based on the bird size category; wherein, if the bird size category is small, the acoustic guidance signal is an ultrasonic signal, and the transmission method is pulse transmission; if the bird size category is medium, the acoustic guidance signal is a predator call signal, and the transmission method is continuous playback, with the volume of the predator call signal determined according to the distance between the bird target and the speaker array; if the bird size category is large, the acoustic guidance signal is a low-frequency warning sound signal, and the transmission method is continuous transmission. Determine the frequency band control parameters of the acoustic guidance signal; wherein, the frequency band control parameters are used to form directional beams in the frequency bands of the acoustic guidance signal that are above a preset frequency threshold, and to transmit the frequency bands that are below the preset frequency threshold in an omnidirectional manner; Acoustic auxiliary commands are generated based on the type, transmission method, volume, and frequency band control parameters of the acoustic guidance signal; The system controls the gimbal, laser, and MEMS mirror to execute the biomimetic optical commands to simulate raptor attack behavior, and controls the speaker array to execute the acoustic auxiliary commands.

2. The method according to claim 1, characterized in that, The method includes the following steps: The radar sensor is controlled to transmit detection signals to the monitoring area and receive echo signals. Based on the echo signals, the distance, speed, angle and echo cross-section information of the moving target are obtained, and radar features are generated. When both the distance and speed information are greater than the corresponding preset detection thresholds, the acoustic sensor is controlled to collect bird call signals in the monitoring area and extract acoustic features from the bird call signals; the image sensor is controlled to collect color images of the monitoring area and extract visual features from the color images; and the infrared sensor is controlled to collect thermal images of the monitoring area and extract infrared features from the thermal images. The radar features, acoustic features, visual features and infrared features are weighted and fused to obtain a fused feature vector. The fused feature vector is then input into the target detection model to identify whether the moving target is a bird target and to obtain the location and species information of the bird target. Based on the distance information, angle information, and the pixel area occupied by the bird target in the color image, the actual size of the bird target is estimated, and the body type of the bird target is determined in combination with the species information. The pixel displacement of the bird target in multiple consecutive frames is obtained from the color image. The movement speed and direction are calculated based on the pixel displacement, and the behavior state of the bird target is identified based on the movement speed and direction.

3. The method according to claim 2, characterized in that, The method includes the following steps: The acoustic sensor is controlled to collect the environmental noise signal of the monitoring area, and the preset detection threshold is dynamically adjusted according to the environmental noise signal: when the environmental noise signal is higher than the preset high noise threshold, the preset detection threshold is increased; when the environmental noise signal is lower than the preset low noise threshold, the preset detection threshold is decreased. The temperature sensor is controlled to collect the ambient temperature, and the thermal image collected by the infrared sensor is temperature-corrected based on the ambient temperature.

4. The method according to claim 2, characterized in that, The estimation of the actual size of the bird target includes: The distance d between the bird target and the gimbal is calculated based on the distance information obtained by the radar sensor. The bird target's pixel area A in the color image is used as the bird's projected area S. The horizontal field of view θ of the image sensor and the width W of the color image are combined with the pixel area A. The bird's projected area S is calculated using the formula S = A × (d × tan(θ / 2) / (W / 2))². The bird's projected area S is used as the estimated actual size of the bird target.

5. The method according to claim 2, characterized in that, The method includes: When the movement speed is lower than the first speed threshold, the behavior state is determined to be stationary; when the movement speed is between the first speed threshold and the second speed threshold and the movement trajectory is irregular, the behavior state is determined to be foraging; when the movement speed is higher than the second speed threshold and the movement trajectory is smooth, the behavior state is determined to be flying.

6. The method according to claim 1, characterized in that, The biomimetic motion sequence includes at least a high-altitude hovering motion sequence, a dive attack motion sequence, and a lateral assault motion sequence; in the high-altitude hovering motion sequence, the gimbal continuously rotates horizontally, and the laser continuously emits light; in the dive attack motion sequence, the gimbal descends vertically while accelerating horizontally, and the laser emission frequency is higher at the end of the dive than at the beginning; in the lateral assault motion sequence, the gimbal rapidly swings horizontally, and the laser continuously emits light; The step of selecting a target bionic action sequence from a variety of preset bionic action sequences based on the bird target's location information and behavioral state specifically includes: When the distance between the bird target and the gimbal is greater than the first preset value, the high-altitude circling action sequence is selected; when the distance between the bird target and the gimbal is between the first preset value and the second preset value, the dive attack action sequence is selected; when the distance between the bird target and the gimbal is less than the second preset value, the lateral attack action sequence is selected. Specifically, when the behavior state is foraging, the target bionic action sequence adopts a strong execution style; when the behavior state is flying, the target bionic action sequence adopts a tracking execution style; and when the behavior state is stationary, the target bionic action sequence adopts a default execution style.

7. The method according to claim 1, characterized in that, The method further includes the following steps: Acquire light intensity, wind speed, temperature, and guidance success rate; wherein, the guidance success rate is the proportion of successful guidance in historical guidance records; When the light intensity is higher than a preset strong light threshold and the guidance success rate is lower than a preset success rate threshold, the PWM duty cycle of the laser is increased to a preset maximum value. When the wind speed is higher than the preset wind speed threshold, a preset compensation amount is added to the current PWM duty cycle; When the temperature is lower than the preset low temperature threshold, the heating device is activated and the PWM duty cycle of the laser is reduced. When the guidance fails for a preset number of consecutive times, the system switches from the current bionic action sequence to another bionic action sequence and regenerates the bionic optical instructions.

8. The method according to claim 1, characterized in that, The method further includes the following steps: When executing the bionic optical command and the acoustic auxiliary command, the bionic optical command is executed first, and the acoustic auxiliary command is executed after a preset time interval.

9. The method according to claim 2, characterized in that, The method includes the following steps: Monitor the operating status of each sensor; when the image sensor malfunctions, switch to target detection using the radar sensor and the infrared sensor; when the infrared sensor malfunctions, switch to target detection using the radar sensor and the image sensor; when both the image sensor and the infrared sensor malfunction, switch to target detection using only the radar sensor. When the laser malfunctions, the system switches to acoustic guidance solely from the speaker array.

10. A multidimensional bird monitoring device based on biomimetic optics, characterized in that, include: Radar sensors are used to transmit detection signals to the monitored area and receive echo signals. Acoustic sensors are used to collect environmental noise signals and bird call signals in the monitored area; An image sensor is used to acquire color images of the monitored area; An infrared sensor is used to acquire thermal images of the monitored area; Temperature sensor, used to collect ambient temperature; A light sensor is used to collect ambient light intensity. Wind speed sensor, used to collect ambient wind speed; A laser, used to emit a laser beam; MEMS galvanometers are disposed in the output optical path of the laser and are used to scan the laser beam; The gimbal supports the laser and the MEMS galvanometer. A loudspeaker array is used to emit acoustic guidance signals toward the bird target; A heating device is used to activate heating when the ambient temperature is below a preset low temperature threshold. as well as The main processor is connected to the radar sensor, acoustic sensor, image sensor, infrared sensor, temperature sensor, light sensor, wind speed sensor, laser, MEMS galvanometer, gimbal, speaker array and heating device respectively, and the main processor is configured to perform the method according to any one of claims 1 to 9.

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