Probe-drive integrated intelligent prevention and control system

Abstract

The invention provides a probing and driving integrated intelligent prevention and control system, and the system comprises an early warning radar device which is used for scanning the airspace in the visual field of the early warning radar device, determining an early warning target, and updating an early warning target information table in real time based on the determined early warning target; the first information processing device screens a preset number of early warning targets from the early warning target information table based on a preset screening strategy set as screening targets, and generates or updates a screening target information table; the guide radar device is in communication connection with the first data processing device, and the guide radar device scans the airspace in the field of view of the guide radar device, determines a to-be-processed target, compares and fuses the to-be-processed target with a screening target in the screening target information table, and generates or updates a to-be-processed target information table; the expelling array comprises a plurality of expelling devices, the expelling devices correspond to different expelling airspaces, and the expelling devices execute expelling operation on the to-be-expelled targets in the to-be-expelled target queues based on the respective to-be-expelled target queues; and a second information processing device.

Description

Technical Field

[0001] This disclosure relates to technical fields such as flight safety, and in particular to an intelligent prevention and control system integrating exploration and decoy. Background Technology

[0002] Bird strikes at airports are one of the major threats to aviation safety, especially during takeoff, landing and taxiing. Bird strikes can cause serious accidents such as engine damage and windshield breakage, resulting in significant economic losses and safety risks.

[0003] Existing bird control technologies mainly include manual patrols, physical fencing, laser bird deterrents, sound broadcasts, and radar monitoring, but they have many limitations.

[0004] First, although conventional early warning radars can cover medium and high altitudes (50 meters to 2000 meters), target selection is based only on simple physical parameters (such as RCS value or speed), and cannot combine airport geographical features (such as take-off and landing channels, warning zone coordinates) for intelligent priority ranking, resulting in a high false alarm rate and low-threat targets occupying system resources.

[0005] Secondly, existing radar systems mostly adopt a fixed strike strategy, and directional sound wave equipment only plays preset sounds (such as the common eagle call) without adaptively adjusting to the characteristics of bird species (such as the different sensitivity of pigeons to the calls of predators). Birds are prone to sound adaptation, resulting in a decrease in the deterrent effect.

[0006] In addition, the low-altitude area below 50 meters becomes a radar blind zone due to ground clutter interference. Traditional optoelectronic systems, as independent units, are not integrated with radar data, forming "information islands" and failing to achieve seamless coverage of the entire airspace.

[0007] More importantly, the existing system lacks a closed-loop optimization mechanism, its effectiveness evaluation relies on manual observation, it cannot generate trend forecasts, and it is always in a passive response state.

[0008] Therefore, there is an urgent need for an intelligent bird control system that integrates multi-source sensor collaboration, AI dynamic decision-making, adaptive strike, closed-loop learning, and full airspace coverage to achieve accurate, real-time, and sustainable bird control and meet the needs of smart airports. Summary of the Invention

[0009] This disclosure provides an intelligent prevention and control system integrating exploration and driving.

[0010] In some embodiments, the intelligent prevention and control system integrating exploration and decoy functions disclosed herein includes: The early warning radar device is used to scan the airspace within its field of view, identify early warning targets, and update the early warning target information table in real time based on the identified early warning targets. A first information processing device, which selects a preset number of early warning targets from the early warning target information table as filtering targets based on a preset filtering strategy set, and generates or updates the filtering target information table. A guidance radar device is communicatively connected to the first information processing device. The guidance radar device scans the airspace within its field of view to determine the target to be processed, and compares and merges the target to be processed with the filtered targets in the filtered target information table to generate or update the target information table. The expulsion array includes multiple expulsion devices, each corresponding to a different expulsion airspace, and each expulsion device performs expulsion operations based on its own queue of targets to be expelled. A second information processing device performs the following process: A risk level assessment is performed on each target in the target information table to determine the risk level of each target. The airspace corresponding to each target to be dealt with is determined based on the risk level and spatial location of each target to be dealt with. Each target to be processed is sent to the target queue of the expulsion device corresponding to the expulsion airspace of each target to be processed.

[0011] According to at least one embodiment of the present disclosure, the intelligent control system integrating exploration and deflection includes a photoelectric tracking module. The photoelectric tracking module continuously performs visual tracking on the target to be deflected in the deflection airspace, acquires image information of the target to be deflected, and performs species identification based on the image information to determine the species category of the target to be deflected. The photoelectric tracking module determines the driving effect of the driving device on the target based on the image information of the target to be driven away.

[0012] According to at least one embodiment of the intelligent prevention and control system integrating exploration and depot, the intelligent prevention and control system further includes: An optoelectronic radar device, wherein the optoelectronic radar device is communicatively connected to the guidance radar device; The photoelectric radar device scans the airspace within its field of view to obtain the scanning results of the early warning target; The photoelectric radar device performs a situational analysis of the early warning targets within its field of view based on the scanning results of the early warning targets and the information table of the targets to be processed, and generates or updates the tracking table of key early warning targets corresponding to the photoelectric radar device.

[0013] According to at least one embodiment of the intelligent prevention and control system integrating exploration and depot, the intelligent prevention and control system further includes: The third information processing device generates control commands based on the key early warning targets in the key early warning target tracking table to control the photoelectric radar device to visually track the key early warning targets within its field of view. The third information processing device performs species analysis based on image information acquired through visual tracking to determine the species category of the key early warning targets; The third information processing device independently evaluates the effectiveness of the expulsion operation based on the changes in the flight behavior of the key early warning target and generates an independent evaluation result. The third information processing device generates an assessment report based on the species category of the key early warning targets and the independent assessment results.

[0014] According to at least one embodiment of the intelligent prevention and control system integrating detection and deflection according to the present disclosure, the deflection device further includes a sound wave emission module and an information processing module (with a built-in sound selection strategy model). The information processing module selects a sound type based on the species category of the target to be deflected determined by the photoelectric tracking module. The sound wave emission module generates and emits a sound wave signal based on the selected sound type to perform a deflection operation on the target to be deflected. The information processing module selects sound types based on a preset sound selection strategy. The sound selection strategy includes: matching target sensitive sound types according to species category. Target and sensitive sound types include, but are not limited to, predator calls, cries of other species, gunshots, or artillery fire.

[0015] An intelligent prevention and control system integrating exploration and decoy systems according to at least one embodiment of this disclosure. During the expulsion operation, the photoelectric tracking module continuously tracks the target to be expelled, and the information processing module evaluates the expulsion effect based on the changes in the flight behavior of the target to be expelled and records the expulsion effect evaluation information. The changes in flight behavior include, but are not limited to: the target to be driven away flying away from the dangerous direction and area, turning back from the driving direction, flying quickly away from the driving area, or flying erratically. The dispersal effect evaluation information is used as training data by the information processing module to optimize the sound selection strategy.

[0016] According to at least one embodiment of the intelligent prevention and control system integrating exploration and deflection according to this disclosure, the third information processing device is communicatively connected to the information processing module of the deflection device; The third information processing device sends the independent evaluation result to the information processing module; The information processing module summarizes the expulsion effect evaluation information and the independent judgment results to generate summary expulsion evaluation information; The information processing module feeds and trains its own sound selection strategy model based on the aggregated expulsion assessment information in order to continuously optimize the sound selection strategy.

[0017] According to at least one embodiment of the intelligent control system integrating exploration and depot according to this disclosure, the feeding training includes, but is not limited to: In real time, data on sensitive sound types and corresponding flight behavior changes for each species are fed into the AI ​​model (data on the flight behavior changes of different birds (such as pigeons and swallows) in response to predator calls, gunshots, etc.) are categorized by species and input into the AI ​​model to establish a matching relationship between "species → effective sound"). Data on different sensitive sound types and corresponding flight behavior changes were fed to each species in a rotational order. Based on different seasons, data on sensitive sound types and corresponding flight behavior changes for each species are fed data accordingly. Based on the species migration season, data on sensitive sound types and corresponding flight behavior changes for each species during the migration season are fed to them.

[0018] According to at least one embodiment of the intelligent prevention and control system integrating exploration and depot, the intelligent prevention and control system further includes: Low-altitude surveillance device, used for continuous monitoring of low-altitude airspace below a preset altitude; The low-altitude monitoring device includes at least one of a single visible light photoelectric system, an infrared photoelectric system, or a compound eye photoelectric system.

[0019] According to at least one embodiment of the intelligent prevention and control system integrating exploration and driving according to this disclosure, the low-altitude monitoring device transmits the low-altitude target information it monitors to the first information processing device corresponding to the early warning radar device. The first information processing device updates the warning target information table based on the low-altitude target information to achieve bird situation control across the entire airspace.

[0020] According to at least one embodiment of the intelligent detection and control system integrating exploration and destructive capabilities disclosed herein, the early warning radar device includes: The S-band radar is configured to perform electronic beam scanning in the horizontal direction, covering an azimuth range of 0° to 360°, and generating horizontal position information and velocity data of the target. The X-band radar is configured to perform electronic beam scanning in the vertical direction, covering an elevation angle range of 0° to 180°, and generate target height information and vertical velocity data. A signal recognition and processing device includes a processor and a memory, wherein the memory stores instructions, and when the processor executes the instructions, the signal recognition and processing device performs the following: Receives target horizontal position and velocity data from S-band radar and altitude and vertical velocity data from X-band radar; The horizontal position and velocity data of the target from the S-band radar are aligned with the height and vertical velocity data from the X-band radar and fused to generate spatial state data of the target. The Kalman filter algorithm is applied to estimate the state of the spatial state data to generate the target motion trend trajectory. A convolutional neural network model is applied to determine the warning target based on the target's motion trend trajectory and the spatial state data, and the warning target information table is updated in real time based on the determined warning target.

[0021] According to at least one embodiment of the intelligent detection and control system integrating exploration and destructive capabilities disclosed herein, the early warning radar device includes: A phased array radar is configured to perform electronic beam scanning at an angle to obtain spatial state data of a target, the spatial state data including the target's spatial position and velocity; A signal recognition and processing device includes a processor and a memory, wherein the memory stores instructions, and when the processor executes the instructions, the signal recognition and processing device performs the following: Receive spatial state data of the target from the phased array radar; The Kalman filter algorithm is applied to estimate the state of the spatial state data to generate the target motion trend trajectory. A convolutional neural network model is applied to determine the warning target based on the target's motion trend trajectory and the spatial state data, and the warning target information table is updated in real time based on the determined warning target. Attached Figure Description

[0022] The accompanying drawings illustrate exemplary embodiments of the present disclosure and, together with the description thereof, serve to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification.

[0023] Figure 1 This is a schematic block diagram of the overall structure of an integrated intelligent prevention and control system for exploration and decoy, according to one embodiment of this disclosure.

[0024] Figure 2 This is a flowchart illustrating the execution process of the second information processing device according to one embodiment of the present disclosure.

[0025] Figure 3This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0026] Figure 4 This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0027] Figure 5 This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0028] Figure 6 This is a schematic diagram of the structure of a deflection device according to another embodiment of this disclosure.

[0029] Figure 7 This is a schematic diagram of the overall architecture of an integrated exploration and control intelligent prevention and control system, which is yet another embodiment of this disclosure. Detailed Implementation

[0030] The present disclosure will now be described in further detail with reference to the accompanying drawings and examples. It should be understood that the specific examples described herein are for illustrative purposes only and are not intended to limit the scope of the disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the accompanying drawings.

[0031] It should be noted that, where there is no conflict, the embodiments and features described in this disclosure can be combined with each other. The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0032] Figure 1 This is a schematic block diagram of the overall structure of an integrated intelligent prevention and control system for exploration and decoy, according to one embodiment of this disclosure.

[0033] Figure 2 This is a flowchart illustrating the execution process of the second information processing apparatus 400 according to one embodiment of the present disclosure.

[0034] refer to Figure 1 and Figure 2 In some embodiments of this disclosure, the intelligent prevention and control system integrating exploration and destructive capabilities includes: The early warning radar device 100 is used to scan the airspace within its field of view, determine the early warning targets, and update the early warning target information table in real time based on the determined early warning targets. The first information processing device 200 (first AI) filters a preset number of early warning targets from the early warning target information table based on a preset set of filtering strategies, and generates or updates the filtering target information table. The guidance radar device 300 is communicatively connected to the first information processing device 200. The guidance radar device 300 scans the airspace within its field of view to determine the target to be processed, and compares and merges the target to be processed with the screened targets in the screened target information table to generate or update the target information table (Table C). The expulsion array 500 includes multiple expulsion devices 510, each expulsion device 510 corresponds to a different expulsion airspace, and each expulsion device 510 performs expulsion operations based on its own queue of targets to be expelled. The second information processing device 400 (second AI) performs the following process: S110. Assess the risk level of each target in the target information table and determine the risk level of each target. S120. Determine the clearance airspace corresponding to each target based on its risk level and spatial location. S130. Send each target to be processed to the target queue of the expulsion device 510 corresponding to the expulsion airspace of each target to be processed.

[0035] The early warning radar device 100 can be deployed at a suitable location at an airport to continuously scan the airspace within its field of view (e.g., an area with a diameter of 8 kilometers) to detect aerial targets. This early warning radar device can identify potential threat targets such as birds and generate and update an early warning target information table (Table A) in real time based on the scan results. This early warning target information table records information on all detected targets, including parameters such as the target's position, speed, heading, and RCS value, and can be set to a maximum capacity of 1000 targets.

[0036] The first information processing device 200 (which may have a built-in first AI model) is communicatively connected to the early warning radar device 100 and receives all target data from the early warning target information table. Based on a preset set of filtering strategies, the first information processing device 200 filters a preset number of targets with higher risk from a large number of early warning targets as filtering targets, and generates a filtering target information table (i.e., Table B).

[0037] The screening strategy set includes, but is not limited to: whether the target is located near the takeoff and landing runway, whether it is a large target, whether its flight path points towards the airport, whether it is within three kilometers of the airport perimeter, whether it is close to or enters the restricted area, whether it is within the airport perimeter, whether it is a flock of birds, whether it is a circling target, and whether it is suspected to be a drone. Through this screening mechanism, the number of targets can be controlled to, for example, less than 200, achieving initial focus on high-risk targets.

[0038] The guidance radar device 300 is communicatively connected to the first information processing device 200, and is used to perform high-precision scanning of the airspace within its field of view to determine the targets to be processed. The guidance radar device compares the targets it detects with targets in the target information table (Table B) using multi-dimensional information such as coordinates, altitude, and elevation angle. For matching targets, information fusion is performed; for inconsistent targets, re-judgment is conducted according to the same screening strategy, ultimately generating or updating the target information table (Table C). This target information table (Table C) serves as the basis for subsequent fire control calculations, ensuring the accuracy and completeness of the target information.

[0039] The expulsion array 500 includes multiple expulsion devices 510, each deployed in different areas of the airport and corresponding to different expulsion airspaces. Each expulsion device 510 receives targets to be expelled from the second information processing unit 400 to generate or update its own queue of targets to be expelled, and performs expulsion operations on the targets in the queue within its responsible airspace.

[0040] The second information processing device 400 (which may have a built-in second AI model) is communicatively connected to the guidance radar device 300 to assess the risk level of each target in Table C. Assessment criteria may include the overlap time between the target and the aircraft, whether it has entered a warning zone, whether it is a flock of birds, a falcon, or an RCS greater than 0.01, classifying targets into different levels such as Level I high-risk targets (overlap time < 10 seconds) and Level II dangerous targets (10 to 20 seconds). Subsequently, based on the target's risk level and spatial location, the second information processing device 400 determines its corresponding clearance airspace and assigns each target to the queue of targets to be cleared by the corresponding clearance device 510, achieving precise task assignment.

[0041] Through the above structure and process, the system disclosed herein realizes a complete closed loop from wide-area detection to intelligent screening, from multi-source fusion to risk classification, and from task allocation to execution of expulsion, forming an efficient, intelligent, and collaborative prevention and control system.

[0042] The intelligent prevention and control system disclosed herein can achieve high-precision target screening and risk classification: By introducing a multi-dimensional filtering strategy set based on spatial relationships such as airport geographic coordinates, airways, and restricted areas, the false alarm problem caused by traditional systems relying solely on single physical parameters such as RCS or speed is avoided. This significantly improves the accuracy of identifying high-risk targets and reduces the waste of system resources.

[0043] The intelligent prevention and control system disclosed herein improves the reliability of target information fusion: The guidance radar device 300 compares and fuses its own detection results with the selected target information table using multi-dimensional information (coordinates, altitude, elevation angle, etc.), effectively eliminating single radar errors and generating a high-confidence target information table (Table C), providing a reliable data foundation for subsequent fire control calculations.

[0044] The intelligent prevention and control system disclosed herein achieves precise task allocation and efficient execution: The second information processing device 400 dynamically allocates the targets to be expelled to the corresponding expulsion device's target queue based on the target risk level and spatial location, ensuring that high-risk targets are processed first and improving system response efficiency and expulsion timeliness.

[0045] The intelligent prevention and control system disclosed herein supports collaborative prevention and control across the entire airspace: By working in concert with early warning radar, guidance radar and multiple deterrent devices, an integrated architecture of "detection-screening-fusion-decision-execution" is constructed to achieve comprehensive coverage and intelligent control of the airport's mid-to-high altitude airspace.

[0046] Figure 3 This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0047] refer to Figure 3 Based on the intelligent prevention and control system described above, the driving device 510 of the intelligent prevention and control system disclosed herein includes an optoelectronic tracking module 511. The optoelectronic tracking module 511 continuously performs visual tracking on the target to be driven away in the driving away airspace, acquires image information of the target to be driven away, and performs species identification based on the image information to determine the species category of the target to be driven away. The photoelectric tracking module 511 determines the driving effect of the driving device 510 performing the driving operation on the target based on the image information of the target to be driven away.

[0048] The photoelectric tracking module 511 is used to continuously visually track targets assigned to the target queue of the driving-off device 510 within its corresponding driving-off airspace, acquiring image information of the targets. Based on the acquired image information, the photoelectric tracking module 511 further identifies the species of the targets, such as determining what kind of bird they belong to, thereby providing a basis for optimizing and adjusting the subsequent driving-off strategy. The photoelectric tracking module 511 is also used to monitor changes in the flight behavior of the targets in real time during the driving-off operation, thereby determining whether the driving-off operation has produced the expected effect, achieving localized effect evaluation of a single driving-off mission.

[0049] The intelligent control system disclosed herein enables local closed-loop evaluation of the expulsion process: By integrating photoelectric tracking modules 511 onto each of the deterrent devices 510, continuous visual tracking and species identification of targets within the responsible airspace are achieved. This enables the system to confirm target attributes before executing deterrent operations, improving the targeting and rationality of deterrents. Simultaneously, during the deterrent process, the system analyzes changes in the target's flight behavior through image information, allowing for real-time judgment of the deterrent's effectiveness, thus forming a local closed loop of "execution-feedback".

[0050] Figure 4 This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0051] refer to Figure 4 For the intelligent prevention and control system integrating exploration and destructive capabilities described in the above embodiments, the intelligent prevention and control system further includes: The optoelectronic radar device 600 is communicatively connected to the guidance radar device 300. The photoelectric radar device 600 scans the airspace within its field of view to obtain the scanning results of early warning targets; Based on the scanning results of the early warning targets and the information table of the targets to be processed (Table C), the photoelectric radar device 600 performs early warning target situation analysis on the airspace within its field of view, and generates or updates the key early warning target tracking table (Table D) corresponding to the photoelectric radar device 600.

[0052] The photoelectric radar device 600 is communicatively connected to the guidance radar device 300, and is used to optically scan the airspace within its field of view at its deployment location, independently acquiring image information of aerial targets within that airspace, i.e., obtaining the early warning target scan result. This early warning target scan result may include optical perception data such as the target's visual characteristics, position, and movement trends.

[0053] The optoelectronic radar device 600 further analyzes the airspace within its field of view based on the scanning results of the early warning targets it obtains, and in conjunction with the high-risk target information in the target information table (Table C) generated by the guidance radar device 300.

[0054] Specifically, the photoelectric radar device 600 performs spatiotemporal matching and feature comparison between the targets it detects and the targets recorded in the target information table (Table C) to filter out key targets currently being driven away by the driving-away device 510, and generates or updates the key early warning target tracking table (Table D) corresponding to the photoelectric radar device 600. This key early warning target tracking table (Table D) serves as the input basis for subsequent visual tracking tasks, guiding the photoelectric radar device 600 to continuously monitor high-priority targets.

[0055] The intelligent control system disclosed herein achieves independent situational awareness of the targets to be driven away and focuses on key targets: By adding an optoelectronic radar device 600, the system can independently acquire optical detection data within the airspace and, based on the list of high-risk targets in the target information table (Table C), autonomously identify and screen key targets, generating a key early warning target tracking table (Table D). This mechanism enables the system to have external monitoring capabilities for the execution of expulsion missions, avoiding missed or false judgments that may result from relying on a single sensing source, and improving the robustness and reliability of the system's overall target management.

[0056] Figure 5 This is a schematic diagram of the overall architecture of an intelligent prevention and control system according to another embodiment of this disclosure.

[0057] refer to Figure 5 Preferably, for the intelligent prevention and control system of the above embodiments, the intelligent prevention and control system further includes: The third information processing device 700 (i.e., the AI ​​of the photoelectric radar device 600) generates control commands based on the key early warning targets in the key early warning target tracking table to control the photoelectric radar device 600 to visually track the key early warning targets within its field of view. The third information processing device 700 performs species analysis based on image information acquired through visual tracking to determine the species categories of key early warning targets; The third information processing unit 700 independently evaluates the effectiveness of the interception operation based on changes in the flight behavior of key early warning targets and generates independent evaluation results. The third information processing device 700 generates an assessment report based on the species categories of key early warning targets and independent evaluation results.

[0058] The third information processing device 700 can be the built-in artificial intelligence processing unit of the photoelectric radar device 600, used to perform high-level visual analysis and effect evaluation tasks on key early warning targets.

[0059] The third information processing device 700 generates control commands based on the key early warning targets in the key early warning target tracking table (Table D), and sends the control commands to the photoelectric radar device 600 to control the photoelectric radar device 600 to continuously visually track the key early warning targets within its field of view. During visual tracking, the third information processing device 700 receives image information collected by the photoelectric radar device 600, and performs species analysis based on the image information to identify the species category of the key early warning targets, such as determining whether they are pigeons, swallows, falcons, or drones.

[0060] Furthermore, the third information processing device 700 is also used to analyze changes in the flight behavior of key early warning targets during the expulsion operation, including whether they fly away from the danger direction and area, whether they turn back from the expulsion direction, whether they fly away from the expulsion area quickly, or whether they exhibit a panicked flight state. Based on the above changes in flight behavior, the third information processing device 700 independently evaluates the effectiveness of the expulsion operation and generates an independent evaluation result. Finally, the third information processing device 700 combines the species category of the key early warning targets with the independent evaluation result to generate an evaluation report, which serves as the data basis for the overall system performance evaluation and subsequent optimization.

[0061] Figure 6 This is a schematic diagram of the structure of the expulsion device 510 according to another embodiment of this disclosure.

[0062] refer to Figure 6 For the intelligent prevention and control system of the above embodiments, preferably, the driving device 510 further includes a sound wave emitting module 512 and an information processing module 513 (513 has a built-in sound selection strategy model). The information processing module 513 selects the sound type based on the species category of the target to be driven away determined by the photoelectric tracking module 511. The sound wave emitting module 512 generates and emits a sound wave signal based on the selected sound type to perform a driving operation on the target to be driven away. The information processing module 513 (i.e., AI) selects sound types based on a preset sound selection strategy. The sound selection strategy includes: matching target sensitive sound types according to species category. Target and sensitive sound types include, but are not limited to, predator calls, cries of other species, gunshots, or cannon shots.

[0063] The decoy device 510 includes a sound wave emitting module 512 and an information processing module 513. The information processing module 513 may have a built-in sound selection strategy model (which can be implemented through semantic models such as AI) to achieve intelligent decoy sound selection.

[0064] Based on the species category of the target to be driven away determined by the photoelectric tracking module 511, the information processing module 513 matches the corresponding target-sensitive sound type from a preset sound selection strategy and selects an appropriate sound type as the output signal for this driving-away operation. For example, when the photoelectric tracking module 511 identifies the target as a pigeon, the information processing module 513 will select sound types that have a significant driving-away effect on the species, such as predator calls, cries of its own kind, gunshots, or cannon shots, according to the sound selection strategy.

[0065] The sound wave emitting module 512 generates and emits a corresponding sound wave signal based on the sound type selected by the information processing module 513. This sound wave signal can be a directional sound beam, focused on the target direction, reducing noise interference to the surrounding environment.

[0066] The preset sound selection strategy includes matching target sensitive sound types based on species category, where sensitive sound types include, but are not limited to, predator calls, cries of other birds, gunshots, or artillery fire. This strategy is based on the differences in auditory sensitivity to specific sounds among different bird species, ensuring the targeting and effectiveness of the dispersal measures.

[0067] The intelligent prevention and control system disclosed herein achieves intelligent matching and precise strikes of expulsion methods: By configuring an information processing module 513 in the decoy device 510, the system can automatically select the most sensitive sound type for the species based on the species identification results of the photoelectric tracking module 511, thus avoiding the problem of low decoy efficiency caused by traditional systems only playing general sounds.

[0068] By employing directional sound wave emission, the utilization rate of sound energy is improved, and environmental noise pollution is reduced. This mechanism significantly enhances the targeting and effectiveness of the repelling operation, and improves the overall control efficiency of the system.

[0069] In some embodiments of this disclosure, the photoelectric tracking module 511 continuously tracks the target to be driven away during the drive-away operation, and the information processing module 513 evaluates the drive-away effect based on the changes in the flight behavior of the target to be driven away and records the drive-away effect evaluation information. Changes in flight behavior include, but are not limited to: the target to be driven away flying away from the dangerous direction and area, turning back from the direction of driving away, rapidly flying away from the driving away area, or flying erratically. The information on the dispersal effect evaluation is used as training data by the information processing module 513 to optimize the sound selection strategy.

[0070] The intelligent prevention and control system disclosed herein enables real-time evaluation of the deportation effect and local strategy optimization: By integrating an optoelectronic tracking module 511 and an information processing module 513 into the expulsion device 510, the system can continuously monitor changes in the flight behavior of the target to be expelled during the expulsion operation, and evaluate the effectiveness based on preset behavior patterns, generating expulsion effectiveness evaluation information. This expulsion effectiveness evaluation information is not only used for feedback judgment in this mission, but can also be used as training data to optimize the sound selection strategy, enabling the system to dynamically adjust the expulsion strategy according to the actual response. This mechanism significantly improves the intelligence level and long-term effectiveness of the expulsion operation.

[0071] In a preferred embodiment of this disclosure, the third information processing device 700 is communicatively connected to the information processing module 513 of the expulsion device 510. The third information processing device 700 sends the independent evaluation results to the information processing module 513; The information processing module 513 summarizes the expulsion effect evaluation information and the independent judgment results to generate summary expulsion evaluation information; The information processing module 513 feeds and trains its own voice selection strategy model (AI) based on the aggregated expulsion evaluation information in order to continuously optimize the voice selection strategy.

[0072] By establishing a communication connection between the third information processing device 700 and the information processing module 513, the system can aggregate the local expulsion effect evaluation information with the independent judgment results generated by the photoelectric radar device 600 to form a high-confidence aggregated expulsion evaluation information. This aggregated expulsion evaluation information is used as training data to feed and train the sound selection strategy model, realizing an upgrade from "local closed loop" to "multi-source collaborative learning," significantly improving the training quality and strategy optimization efficiency of the AI ​​model, and enhancing the stability and adaptability of the system's long-term expulsion effect.

[0073] The expulsion device disclosed herein may use the structure of the expulsion device shown in the applicant's prior patent application 202510814431.X or a similar structure, or the control device or similar module described in the prior patent application may be configured in the expulsion device disclosed herein, all of which fall within the protection scope of this disclosure.

[0074] For the intelligent control system integrating exploration and decoy in the above-described embodiments, the feeding training described above includes, but is not limited to: In real time, data on sensitive sound types and corresponding flight behavior changes for each species are fed into the AI ​​model (data on the flight behavior changes of different birds (such as pigeons and swallows) in response to predator calls, gunshots, etc.) are categorized by species and input into the AI ​​model to establish a matching relationship between "species → effective sound"). Data on different sensitive sound types and corresponding flight behavior changes were fed to each species in a rotational order. Based on different seasons, data on sensitive sound types and corresponding flight behavior changes for each species are fed data accordingly. Based on the species migration season, data on sensitive sound types and corresponding flight behavior changes for each species during the migration season are fed to them.

[0075] For the integrated detection and control intelligent prevention and control system described in the above embodiments, the information processing module 513 feeds and trains its own sound selection strategy model based on the summarized deportation assessment information to continuously optimize the sound selection strategy. This feeding and training includes multiple data feeding modes, aiming to improve the adaptability and deportation effectiveness of the AI ​​model in different scenarios.

[0076] First, the system feeds data on the sensitive sound types and corresponding flight behavior changes of each species in real time. Specifically, the system categorizes and stores the flight behavior changes of different birds after receiving sound stimuli such as predator calls, cries of their own kind, gunshots, or artillery fire, into species categories, and inputs this data into the sound selection strategy model to establish a mapping relationship between species and effective deterrent sounds.

[0077] Secondly, the system feeds data on different sensitive sound types and corresponding flight behavior changes to each species according to a preset rotation sequence. This rotation mechanism prevents birds from adapting to a single sound, ensuring the long-term effectiveness of the dispersal measures.

[0078] Furthermore, the system feeds data on the sensitive sound types and corresponding flight behavior changes of each species according to different seasons. For example, during the spring breeding season, birds are more sensitive to the calls of predators, and the system accordingly increases the training weight of such sounds.

[0079] In addition, the system feeds data on sensitive sound types and corresponding flight behavior changes for each species according to their migration season. For example, during peak migratory bird seasons, the system prioritizes loading historical deterrence response data for migratory birds to improve the success rate of deterring such targets.

[0080] Through the aforementioned multi-dimensional data feeding mechanism, the system achieves dynamic optimization and scene adaptation of the sound selection strategy model, significantly improving the generalization ability and long-term prevention and control effectiveness of the AI ​​model.

[0081] By introducing various training modes such as real-time feeding, rotational feeding, seasonal feeding, and migratory feeding, the system can dynamically adjust the training data input of the sound selection strategy model according to different species, times, and environmental characteristics. This prevents birds from adapting to fixed sounds and enhances the diversity and sustained effectiveness of the dispersal strategy. This mechanism enables the system to evolve from "passive response" to "active prediction."

[0082] Figure 7 This is a schematic diagram of the overall architecture of an integrated exploration and control intelligent prevention and control system according to another embodiment of this disclosure. Preferably, the intelligent prevention and control system further includes: The low-altitude monitoring device 800 is used for continuous monitoring of low-altitude airspace below a preset altitude; The low-altitude monitoring device 800 includes at least one of a single visible light photoelectric system, an infrared photoelectric system, or a compound eye photoelectric system.

[0083] Furthermore, the low-altitude surveillance device 800 transmits the low-altitude target information it monitors to the first information processing device 200 corresponding to the early warning radar device 100. The first information processing device 200 updates the early warning target information table based on low-altitude target information to achieve bird situation control across the entire airspace.

[0084] The low-altitude surveillance device 800 can be used to continuously monitor low-altitude airspace below a preset altitude (e.g., below 50 meters). By adding the low-altitude surveillance device 800, the system can compensate for the detection blind spots of the early warning radar device 100 and realize the monitoring of the low-altitude environment of the airport.

[0085] Single-visible-light optoelectronic systems are suitable for target identification under good daylight conditions; infrared optoelectronic systems can detect bird targets through thermal imaging at night or in low visibility conditions; compound-eye optoelectronic systems have a large field of view and high sensitivity, making them suitable for wide-area scanning and rapid response. The combined use of multiple optoelectronic sensors can improve the system's adaptability to complex weather and lighting conditions.

[0086] Furthermore, the low-altitude surveillance device 800 transmits the low-altitude target information it monitors to the first information processing device 200 corresponding to the early warning radar device 100. This low-altitude target information may include data such as the target's position, trajectory, and image features. The first information processing device 200 receives this information and, based on preset data fusion rules, integrates it with the mid-to-high-altitude target information detected by the early warning radar device 100, updating the early warning target information table (Table A) in real time.

[0087] Through this mechanism, the system incorporates the previously isolated low-altitude sensing data into the overall bird situation management system, realizing the data fusion of "mid-to-high altitude radar detection" and "low-altitude photoelectric blind spot filling", and constructing a full-airspace target monitoring network covering, for example, below 50 meters to high altitudes.

[0088] The intelligent prevention and control system disclosed herein achieves seamless coverage of the entire airspace and closed-loop fusion of multi-source data: By introducing the low-altitude surveillance device 800, the system effectively solves the radar detection blind spot problem in low-altitude areas and compensates for the monitoring shortcomings of traditional bird control systems during takeoff and landing. The low-altitude target information acquired by the surveillance device 800 is transmitted back to the first information processing unit 200 in real time to update the early warning target information table. This ensures that subsequent screening, fusion, and decision-making processes are based on complete air situation data including low-altitude targets, avoiding the phenomenon of "information silos." This mechanism not only enhances the system's ability to perceive low-altitude bird activity but also ensures data consistency throughout the entire process from early warning to bird removal, providing fundamental support for achieving a complete prevention and control chain of "full-domain perception—intelligent decision-making—precision strike—closed-loop optimization."

[0089] In some embodiments of this disclosure, the early warning radar device 100 includes: The S-band radar is configured to perform electronic beam scanning in the horizontal direction, with the preferred azimuth range being 0° to 360°, to generate the target's horizontal position information and velocity data. The X-band radar is configured to perform electronic beam scanning in the vertical direction, with the preferred coverage elevation angle range being 0° to 180°, generating target height information and vertical velocity data. The signal recognition and processing device includes a processor and a memory. The memory stores instructions, which, when executed by the processor, cause the signal recognition and processing device to perform the following actions: Receives target horizontal position and velocity data from S-band radar and altitude and vertical velocity data from X-band radar; The horizontal position and velocity data of the target from the S-band radar are aligned with the height and vertical velocity data from the X-band radar and fused to generate spatial state data of the target. The Kalman filter algorithm is applied to estimate the state of spatial state data and generate the target motion trend trajectory. A convolutional neural network model is applied to determine early warning targets based on the target's motion trend trajectory and spatial state data, and the early warning target information table is updated in real time based on the determined early warning targets.

[0090] In other embodiments of this disclosure, the early warning radar device 100 includes: The phased array radar is configured to perform electronic beam scanning at an angle to obtain spatial state data of the target, including the target's spatial position and velocity. The signal recognition and processing device includes a processor and a memory. The memory stores instructions, which, when executed by the processor, cause the signal recognition and processing device to perform the following actions: Receive spatial status data of targets from phased array radar; The Kalman filter algorithm is applied to estimate the state of spatial state data and generate the target motion trend trajectory. A convolutional neural network model is applied to determine early warning targets based on the target's motion trend trajectory and spatial state data, and the early warning target information table is updated in real time based on the determined early warning targets.

[0091] The two radar implementation methods described above can be deployed independently or used in combination, suitable for target monitoring needs in different airport environments. The S-band / X-band dual radar system is suitable for large-area surveillance, while the tilting phased array radar is suitable for staring scanning of key areas.

[0092] It should be noted that the species disclosed herein are not limited to various birds, but may also include drones, etc.

[0093] The radars described above in this disclosure include, but are not limited to, S-band, X-band, and Ku-band radars.

[0094] The intelligent prevention and control system disclosed herein achieves high-precision early warning detection and intelligent target recognition, and supports multiple radar architectures to adapt to different deployment requirements: In the implementation method employing S-band and X-band radar working in tandem, the system achieves high-precision three-dimensional airspace detection through a directional scanning mechanism. The S-band radar performs a 360° electronic beam scan in the horizontal direction, ensuring omnidirectional coverage around the airport and effectively capturing bird targets from any direction. The X-band radar scans from 0° to 180° in the vertical direction, accurately acquiring target height and vertical velocity information, compensating for the shortcomings of traditional radar in elevation coverage. After the two radar systems acquire horizontal and vertical motion parameters respectively, the signal recognition and processing device performs coordinate alignment and data fusion to generate complete target spatial status data. This architecture significantly improves the positioning accuracy and motion trend prediction capability of mid- and high-altitude targets, and is particularly suitable for bird monitoring tasks at large-scale, wide-area survey airports.

[0095] For the implementation using a tilted phased array radar, the system achieves high-density three-dimensional scanning of key areas through a single radar. This phased array radar is configured with tilted electronic beam scanning, directly acquiring the spatial position and velocity information of targets without the need for multi-radar data fusion, simplifying the system structure and reducing communication latency. Its strong beamforming capability allows for simultaneous measurement of azimuth, elevation, range, and velocity in a single scan, resulting in a higher data update rate and response speed. This solution is particularly suitable for staring surveillance of critical areas such as runway ends and takeoff and landing paths, meeting the requirements for high-timeliness and high-reliability key protection.

[0096] In summary, the intelligent bird strike prevention and control system disclosed herein achieves precise, real-time, and sustainable prevention and control of bird activity in airport airspace through multi-source sensor collaboration, AI dynamic decision-making, adaptive strike, and closed-loop learning mechanisms. The system overcomes the limitations of traditional radar blind zones by coordinating early warning radar and low-altitude surveillance devices, constructing a full-airspace perception network covering altitudes from below 50 meters to 2000 meters. The integration of guidance radar and multi-dimensional screening strategies improves the accuracy of target identification and resource utilization efficiency. A dual-source verification mechanism combining local evaluation by the bird strike deterrent device and independent judgment by electro-optical radar forms a closed-loop evaluation system of "execution-feedback-optimization." Furthermore, multi-dimensional training enables continuous evolution of the sound selection strategy model, allowing the system to evolve from "passive response" to "active prediction." This system not only significantly improves the targeting, effectiveness, and intelligence of bird strike operations but also provides a scalable and iterative technical solution for bird strike risk prevention and control in smart airports.

[0097] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., refer to specific features, structures, or characteristics described in connection with that embodiment / mode or example, which are included in at least one embodiment / mode or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0098] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0099] Those skilled in the art should understand that the above embodiments are merely for illustrating the present disclosure and are not intended to limit the scope of the disclosure. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications still fall within the scope of the present disclosure.

Claims

1. An integrated intelligent prevention and control system for exploration and control, characterized in that, include: The early warning radar device is used to scan the airspace within its field of view, identify early warning targets, and update the early warning target information table in real time based on the identified early warning targets. A first information processing device, which selects a preset number of early warning targets from the early warning target information table based on a preset set of filtering strategies, and generates or updates the filtering target information table. A guidance radar device is communicatively connected to the first information processing device. The guidance radar device scans the airspace within its field of view to determine the target to be processed, and compares and merges the target to be processed with the filtered targets in the filtered target information table to generate or update the target information table. The expulsion array includes multiple expulsion devices, each corresponding to a different expulsion airspace, and each expulsion device performs expulsion operations based on its own queue of targets to be expelled. A second information processing device performs the following process: A risk level assessment is performed on each target in the target information table to determine the risk level of each target. The airspace corresponding to each target to be dealt with is determined based on the risk level and spatial location of each target to be dealt with. and Each target to be processed is sent to the target queue of the expulsion device corresponding to the expulsion airspace of each target to be processed.

2. The intelligent control system integrating exploration and decoy as described in claim 1, characterized in that, The expulsion device includes a photoelectric tracking module, which continuously performs visual tracking on the target to be expelled in the expulsion airspace, acquires image information of the target to be expelled, and performs species identification based on the image information to determine the species category of the target to be expelled. The photoelectric tracking module determines the driving effect of the driving device on the target based on the image information of the target to be driven away.

3. The intelligent control system integrating exploration and decoy as described in claim 2, characterized in that, The intelligent prevention and control system also includes: An optoelectronic radar device, wherein the optoelectronic radar device is communicatively connected to the guidance radar device; The photoelectric radar device scans the airspace within its field of view to obtain the scanning results of the early warning target; The photoelectric radar device performs a situational analysis of the early warning targets within its field of view based on the scanning results of the early warning targets and the information table of the targets to be processed, and generates or updates the tracking table of key early warning targets corresponding to the photoelectric radar device.

4. The intelligent control system integrating exploration and decoy as described in claim 3, characterized in that, The intelligent prevention and control system also includes: The third information processing device generates control commands based on the key early warning targets in the key early warning target tracking table to control the photoelectric radar device to visually track the key early warning targets within its field of view. The third information processing device performs species analysis based on image information acquired through visual tracking to determine the species category of the key early warning targets; The third information processing device independently evaluates the effectiveness of the expulsion operation based on the changes in the flight behavior of the key early warning target and generates an independent evaluation result. The third information processing device generates an assessment report based on the species category of the key early warning targets and the independent assessment results.

5. The intelligent control system integrating exploration and decoy as described in claim 2, characterized in that, The expulsion device also includes a sound wave emitting module and an information processing module. The information processing module selects a sound type based on the species category of the target to be expelled determined by the photoelectric tracking module. The sound wave emitting module generates and emits a sound wave signal based on the selected sound type to perform an expulsion operation on the target to be expelled. The information processing module selects sound types based on a preset sound selection strategy. The sound selection strategy includes: matching target sensitive sound types according to species category. Target and sensitive sound types include, but are not limited to, predator calls, cries of other species, gunshots, or artillery fire.

6. The intelligent control system integrating exploration and decoy as described in claim 5, characterized in that, During the expulsion operation, the photoelectric tracking module continuously tracks the target to be expelled, and the information processing module evaluates the expulsion effect based on the changes in the flight behavior of the target to be expelled and records the expulsion effect evaluation information. The changes in flight behavior include, but are not limited to: the target to be driven away flying away from the dangerous direction and area, turning back from the driving direction, flying quickly away from the driving area, or flying erratically. The dispersal effect evaluation information is used as training data by the information processing module to optimize the sound selection strategy.

7. The intelligent control system integrating exploration and decoy as described in claim 6, characterized in that, The third information processing device is communicatively connected to the information processing module of the expulsion device; The third information processing device sends the independent evaluation result to the information processing module; The information processing module summarizes the expulsion effect evaluation information and the independent judgment results to generate summary expulsion evaluation information; The information processing module feeds and trains its own sound selection strategy model based on the aggregated expulsion assessment information in order to continuously optimize the sound selection strategy.

8. The intelligent control system integrating exploration and decoy as described in claim 7, characterized in that, The feeding training includes, but is not limited to: In real time, data on sensitive sound types and corresponding changes in flight behavior are fed to each species. Data on different sensitive sound types and corresponding flight behavior changes were fed to each species in a rotational order. Based on different seasons, data on sensitive sound types and corresponding flight behavior changes for each species are fed data accordingly. Based on the species migration season, data on sensitive sound types and corresponding flight behavior changes for each species during the migration season are fed to them.

9. The intelligent control system integrating exploration and decoy as described in claim 1, characterized in that, The intelligent prevention and control system also includes: Low-altitude surveillance device, used for continuous monitoring of low-altitude airspace below a preset altitude; The low-altitude monitoring device includes at least one of a single visible light photoelectric system, an infrared photoelectric system, or a compound eye photoelectric system.

10. The intelligent control system integrating exploration and decoy according to any one of claims 1 to 9, characterized in that, The low-altitude surveillance device transmits the low-altitude target information it monitors to the first information processing device corresponding to the early warning radar device. The first information processing device updates the warning target information table based on the low-altitude target information to achieve bird situation control across the entire airspace; Optionally, the early warning radar device includes: The S-band radar is configured to perform electronic beam scanning in the horizontal direction to generate the target's horizontal position information and velocity data. The X-band radar is configured to perform electronic beam scanning in the vertical direction to generate target height information and vertical velocity data. A signal recognition and processing device includes a processor and a memory, wherein the memory stores instructions, and when the processor executes the instructions, the signal recognition and processing device performs the following: Receives target horizontal position and velocity data from S-band radar and altitude and vertical velocity data from X-band radar; The horizontal position and velocity data of the target from the S-band radar are aligned with the height and vertical velocity data from the X-band radar and fused to generate spatial state data of the target. The Kalman filter algorithm is applied to estimate the state of the spatial state data to generate the target's motion trend trajectory; and A convolutional neural network model is applied to determine the warning target based on the target's motion trend trajectory and the spatial state data, and the warning target information table is updated in real time based on the determined warning target; Optionally, the early warning radar device includes: A phased array radar is configured to perform electronic beam scanning at an angle to obtain spatial state data of a target, the spatial state data including the target's spatial position and velocity; A signal recognition and processing device includes a processor and a memory, wherein the memory stores instructions, and when the processor executes the instructions, the signal recognition and processing device performs the following: Receive spatial state data of the target from the phased array radar; The Kalman filter algorithm is applied to estimate the state of the spatial state data to generate the target's motion trend trajectory; and A convolutional neural network model is applied to determine the warning target based on the target's motion trend trajectory and the spatial state data, and the warning target information table is updated in real time based on the determined warning target.

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