Low altitude aerial vehicle detection system and method based on distributed fiber optic vibration sensing

Abstract

The application provides a low-altitude aircraft detection system and method based on distributed optical fiber vibration sensing, and belongs to the technical field of cross of optical fiber sensing and low-altitude aircraft detection; the system comprises the following steps: shallowly burying distributed optical fibers under the ground surface of a region to be monitored; through the cooperative action of an optical fiber analyzer, a signal processing unit, a target discrimination unit, a positioning unit and a warning output unit, collecting vibration response signals generated by the optical fibers due to the ground vibration induced by the downwash airflow in the flight process of a low-altitude aircraft; extracting multi-dimensional features from abnormal vibration events based on a four-element joint discrimination mechanism; and discriminating and positioning low-altitude aircraft events. The application does not need the target to actively emit radio signals, can realize continuous detection and accurate positioning of low-altitude aircrafts in radio suppression, communication limited or concealed deployment scenes, and is suitable for low-altitude target monitoring in various complex environments.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of fiber optic sensing and low-altitude aircraft detection, and particularly relates to a low-altitude aircraft detection system and method based on distributed fiber optic vibration sensing. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the rapid development of low-altitude aircraft technology, the application of drones and other low-altitude flight equipment is becoming increasingly widespread. At the same time, the problems of illegal and covert flights in specific scenarios are becoming increasingly prominent, posing serious challenges to public safety and ecological protection. In no-fly zones within scenic areas, illegal drone flights may disrupt the normal order of the area, damage the natural landscape, and even cause safety accidents. In sensitive areas, radio jamming zones, and areas with restricted communication, covert drone flights may leak classified information and endanger regional security.

[0004] However, existing low-altitude aircraft detection technologies generally suffer from the following technical shortcomings: (1) Existing low-altitude aircraft monitoring technologies mostly rely on radar, radio detection and optoelectronic equipment, but these methods cannot be used to monitor normally in scenarios such as electromagnetic shielding and communication interruption.

[0005] (2) Existing distributed fiber optic vibration monitoring technology is mainly aimed at ground contact vibration targets. It cannot design special identification logic for non-contact ground vibration induced by the downwash airflow of low-altitude aircraft, resulting in low detection accuracy and weak interference discrimination ability for UAVs. It is also difficult to meet the multiple requirements of covert deployment, continuous monitoring and accurate positioning, and cannot meet the low-altitude security needs of special scenarios. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, this invention provides a low-altitude aircraft detection system and method based on distributed optical fiber vibration sensing. It does not require the target to actively transmit radio signals and can achieve continuous detection and accurate positioning of low-altitude aircraft in scenarios with radio suppression, limited communication, or covert deployment. It is suitable for low-altitude target monitoring in various complex environments.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: The first aspect of the present invention provides a low-altitude aircraft detection system based on distributed optical fiber vibration sensing.

[0008] A low-altitude aircraft detection system based on distributed fiber optic vibration sensing includes: A shallow-buried distributed optical fiber loop is buried in the shallow layer of the ground in the area to be monitored, and forms a closed loop along the area to be monitored. An optical fiber analyzer is connected to both ends of the shallowly buried distributed optical fiber loop and is used to acquire vibration response signals of each monitoring section along the shallowly buried distributed optical fiber loop. The signal processing unit is used to preprocess the vibration response signal and extract abnormal vibration events; The target discrimination unit extracts harmonic features, time-domain envelope features, energy distribution features of adjacent monitoring segments, dual-end demodulation time difference features, and continuous trajectory features from the abnormal vibration event based on a four-element joint discrimination mechanism to identify low-altitude aircraft events. The positioning unit is used to determine the position of the low-altitude aircraft based on the position mapping relationship along the optical fiber, the demodulation time difference at both ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments. The early warning output unit is used to output the target position, trajectory, and alarm information of low-altitude aircraft.

[0009] Furthermore, the shallow-buried distributed optical fiber loop adopts a closed loop structure deployed along the boundary of the area to be monitored, and a serpentine loop is used for enhanced deployment inside the area to be monitored.

[0010] Furthermore, the signal processing unit performs filtering, segmentation, time-frequency transformation, and abnormal triggering processing on the vibration response signal to obtain candidate abnormal events.

[0011] Furthermore, the signal processing unit includes a signal filtering module, a signal segmentation module, a feature extraction module, and an abnormal event detection module. The abnormal event detection module employs a combination of thresholding and trend analysis, pre-setting vibration amplitude thresholds and trend thresholds. When the characteristic parameters of a signal segment exceed either preset threshold, it is determined to be an abnormal vibration segment, thus completing the coarse screening of abnormal events. Instead of directly determining the target type, it only transmits the event corresponding to the abnormal signal segment as a candidate abnormal event to the target discrimination unit.

[0012] Furthermore, the target discrimination unit integrates a discrimination algorithm module, an interference differentiation module, and a confidence assessment module internally to distinguish between low-altitude aircraft events and interference events.

[0013] Furthermore, the integrated discrimination algorithm module performs discrimination operations based on five levels of discrimination logic, with each level of discrimination logic implemented by an independent functional layer: The first layer is the event triggering layer, used for preliminary screening of abnormal events; the second layer is the rotor harmonic screening layer, used to capture rotor harmonic fingerprint characteristics; the third layer is the spatial consistency layer, used to judge the vibration response envelope and eliminate isolated local vibration interference based on the state response; the fourth layer is the trajectory confirmation layer, used to eliminate sudden and discrete interference events; the fifth layer is the comprehensive confidence judgment layer, used to set a confidence threshold based on the judgment results of the first four layers, and to comprehensively judge interference events based on the threshold comparison results.

[0014] Furthermore, the positioning unit includes a position mapping module, a time difference calculation module, a peak positioning module, and a trajectory tracking module; wherein, the position mapping module pre-stores the laying location information of the optical fiber loop, and forms a position mapping table by establishing a mapping relationship between each monitoring point along the optical fiber and the actual geographical coordinates, so as to ensure that the vibration signal position corresponds to the actual geographical location.

[0015] The second aspect of the present invention provides a method for detecting low-altitude aircraft based on distributed optical fiber vibration sensing.

[0016] Low-altitude aircraft detection methods based on distributed fiber optic vibration sensing include: The vibration response signals at both ends of the shallowly buried distributed optical fiber loop are obtained, and the position mapping relationship along the optical fiber is established. The vibration response signal is preprocessed to extract abnormal vibration events; The abnormal vibration event is extracted with multidimensional features including harmonic features, time-domain envelope features, energy distribution features of adjacent monitoring segments, time difference features of demodulation at both ends, and continuous trajectory features. Joint discrimination of abnormal vibration events based on multidimensional features to identify low-altitude aircraft events; The location of the low-altitude aircraft is determined based on the optical fiber location mapping relationship, the demodulation time difference between the two ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments, and the positioning results and alarm information are output.

[0017] Furthermore, joint discrimination is performed on abnormal vibration events, including: Based on whether the candidate abnormal event has a stable dominant frequency and multiple harmonic peaks, it is determined whether the candidate abnormal event meets the harmonic characteristic conditions of a low-altitude aircraft. Based on the continuous response of the candidate abnormal event in adjacent monitoring segments, determine whether the candidate abnormal event satisfies the spatial continuity condition; Based on the positional changes of the candidate abnormal event within a continuous time window, determine whether the candidate abnormal event satisfies the trajectory continuity condition.

[0018] Furthermore, the joint discrimination of abnormal vibration events also includes: comparing the interference characteristics of candidate abnormal events with those of wind events and footstep events; when a candidate abnormal event does not meet the continuous dispersed disturbance characteristics of wind events and does not meet the intermittent pulse disturbance characteristics of footstep events, the candidate abnormal event is determined to be a candidate event of a low-altitude aircraft.

[0019] The above one or more technical solutions have the following beneficial effects: (1) This invention adopts a passive detection system, which senses weak vibration signals caused by low-altitude aircraft through a shallowly buried distributed optical fiber loop. It does not require the low-altitude aircraft to actively emit any radio signals, thus fundamentally eliminating the dependence on electronic radiation sources such as target communication and radar. Therefore, this invention can still work stably in environments with strong radio suppression, communication denial, or electronic interference, and has extremely strong anti-electromagnetic interference and covert detection capabilities. It is particularly suitable for the protection of important areas and the monitoring of low-altitude targets in areas with limited communication.

[0020] (2) This invention constructs a spatially continuous sensing link based on a shallowly buried distributed optical fiber loop. By combining the collaborative processing of the signal processing unit, target discrimination unit, and positioning unit, and utilizing a four-element joint discrimination mechanism and a dual-end demodulation time difference positioning method, it can accurately extract the harmonic fingerprint, spatial envelope, and continuous motion trajectory of low-altitude aircraft from a continuous spatiotemporal vibration field. Compared with existing methods that rely on discrete point sensors or short-term observations, this invention achieves long-term, continuous, and wide-range trajectory tracking and accurate positioning of low-altitude aircraft, effectively avoiding the adverse effects of complex environments (such as terrain undulations, vegetation obstruction, background noise, etc.) on detection continuity and positioning accuracy.

[0021] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0023] Figure 1 This is a structural diagram of the low-altitude aircraft detection system based on distributed optical fiber vibration sensing in Embodiment 1 of the present invention.

[0024] Figure 2 This is a flowchart of low-altitude aircraft event discrimination in Embodiment 1 of the present invention. Detailed Implementation

[0025] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0027] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0028] Example 1 This embodiment discloses a low-altitude aircraft detection system based on distributed fiber optic vibration sensing.

[0029] A low-altitude aircraft detection system based on distributed fiber optic vibration sensing includes: A shallow-buried distributed optical fiber loop is buried in the shallow layer of the ground in the area to be monitored, and forms a closed loop along the area to be monitored. An optical fiber analyzer is connected to both ends of the shallowly buried distributed optical fiber loop and is used to acquire vibration response signals of each monitoring section along the shallowly buried distributed optical fiber loop. The signal processing unit is used to preprocess the vibration response signal and extract abnormal vibration events; The target discrimination unit extracts harmonic features, time-domain envelope features, energy distribution features of adjacent monitoring segments, dual-end demodulation time difference features, and continuous trajectory features from the abnormal vibration event based on a four-element joint discrimination mechanism to identify low-altitude aircraft events. The positioning unit is used to determine the position of the low-altitude aircraft based on the position mapping relationship along the optical fiber, the demodulation time difference at both ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments. The early warning output unit is used to output the target position, trajectory, and alarm information of low-altitude aircraft.

[0030] Based on the above systematic design, this invention eliminates the need for the target to actively transmit radio signals, enabling continuous detection and accurate positioning of low-altitude aircraft in scenarios involving radio jamming, limited communication, or covert deployment. It is suitable for low-altitude target monitoring in various complex environments. To facilitate understanding of the technical solution of this invention, the specific implementation methods are further explained and described below.

[0031] like Figure 1As shown, the low-altitude aircraft detection system based on distributed optical fiber vibration sensing includes: a shallowly buried distributed optical fiber loop, an optical fiber analyzer, a signal processing unit, a target discrimination unit, a positioning unit, and an early warning output unit. These components work collaboratively to achieve full-process detection, discrimination, positioning, and early warning of low-altitude aircraft. The specific structure and functions are as follows: 1) Shallow-buried distributed optical fiber loop.

[0032] As the sensing carrier of the entire system, the shallow-buried distributed optical fiber loop is made of single-mode optical fiber that is resistant to aging, tension, and soil corrosion. It is buried in the shallow layer of the ground in the area to be monitored, with a burial depth controlled between 0.3 and 0.8 meters. This burial depth range can effectively capture ground coupling vibrations induced by the downwash of low-altitude aircraft, while avoiding damage to the optical fiber caused by pedestrians, small animals, and natural settlement. The optical fiber loop forms a closed loop around the area to be monitored. The shape of the loop is adaptively designed according to the boundary contour of the area to be monitored, and can adopt a rectangular, polygonal, or irregular closed structure to ensure that there are no blind spots in the area to be monitored. The laying density of the optical fiber loop is adjusted according to the monitoring accuracy requirements. At least one optical fiber is laid per meter in the core monitoring area, and the laying density can be appropriately reduced in the edge area to achieve a balance between monitoring accuracy and deployment cost. Both ends of the optical fiber loop are treated with sealed connectors to prevent soil moisture and impurities from entering the optical fiber interface and affecting the stability of optical signal transmission.

[0033] 2) Fiber optic resolver.

[0034] The fiber optic resolver is mechanically sealed at both ends of the distributed fiber optic loop, eliminating the need for wireless signal transmission. Its core consists of a laser transmitter, an optical receiver, a signal demodulator, and a data interface.

[0035] The laser transmitter is used to emit continuous and stable pulsed laser light into the fiber optic loop. The laser wavelength is selected as 1550nm, which has the advantages of low transmission loss and strong anti-interference ability, and is suitable for long-distance monitoring needs.

[0036] An optical receiver is used to receive backscattered light signals propagating in an optical fiber, convert the optical signals into electrical signals, and transmit them to a signal demodulator.

[0037] The signal demodulator is used to perform preliminary demodulation of electrical signals, extract vibration response signals along the optical fiber, filter noise interference during optical signal transmission, and output standardized vibration signal data.

[0038] The data interface can be RS485 or Ethernet to achieve high-speed data transmission with the signal processing unit and ensure the real-time performance of the vibration signal.

[0039] 3) Signal processing unit.

[0040] The signal processing unit is electrically connected to the fiber optic analyzer and adopts an embedded processor design. It integrates a signal filtering module, a signal segmentation module, a feature extraction module, and an abnormal event detection module. These modules work together to complete the preprocessing and initial screening of vibration signals.

[0041] The signal filtering module uses an adaptive Kalman filter algorithm combined with wavelet denoising technology to filter out weak and irregular disturbances in the natural environment (such as soil thermal expansion and contraction, and small airflow disturbances) and electronic noise, while retaining effective vibration signals.

[0042] The signal segmentation module uses the sliding window method to segment the continuous vibration signal according to a preset time window (window duration 0.5-1s), which facilitates subsequent feature extraction and analysis.

[0043] The feature extraction module is used to extract the time-domain features (including peak value, amplitude, pulse width, and time-domain envelope) and frequency-domain features (including main frequency, harmonic amplitude, and frequency distribution) of each signal segment, providing data support for target discrimination.

[0044] The abnormal event detection module employs a combination of threshold and trend analysis methods. It presets vibration amplitude and trend thresholds. When the characteristic parameters of a signal segment exceed these thresholds, it is determined to be an abnormal vibration segment, thus completing the initial screening of abnormal events. During this initial screening, the target type is not directly determined; instead, the abnormal signal segment is transmitted to the target discrimination unit.

[0045] In the specific implementation process, the abnormal event detection module performs a coarse screening of abnormal vibration segments according to the process of "background baseline establishment, feature parameter calculation, threshold triggering, trend confirmation, and event merging output". After the system starts, an initial time period without obvious external disturbances is selected as the background noise segment. The mean, standard deviation, and median absolute deviation of the background vibration of each monitoring segment are calculated, and an adaptive background baseline is formed for each monitoring segment accordingly. For the vibration signal within each sliding time window, the abnormal event detection module calculates the peak amplitude, root mean square amplitude, short-time energy, energy change rate, and envelope rise slope of that window. Among them, the peak amplitude is used to characterize the instantaneous disturbance intensity, the root mean square amplitude and short-time energy are used to characterize the overall vibration level of the signal segment, and the energy change rate and envelope rise slope are used to characterize the trend of the vibration signal changing from the background state to the abnormal state.

[0046] During the threshold determination process, the abnormal event detection module compares the peak amplitude, root mean square amplitude, or short-term energy of the current window with a preset amplitude threshold. When any amplitude-type feature exceeds the corresponding threshold, it is marked as an amplitude trigger window. Simultaneously, it compares the short-term energy and envelope amplitude of the current window with the previous window or several consecutive historical windows, calculating the energy growth rate and envelope change slope. When the energy growth rate or envelope change slope exceeds a preset trend threshold, it is marked as a trend trigger window. To reduce false triggers caused by single-point noise, instantaneous spikes, or fiber optic contact anomalies, the abnormal event detection module further sets a continuous verification condition: only when an amplitude trigger window or trend trigger window appears within at least two consecutive sliding windows, or forms a synchronous or near-synchronous response on adjacent monitoring segments, is it confirmed as an abnormal vibration segment.

[0047] For confirmed abnormal vibration segments, the abnormal event detection module records their start and end times, corresponding fiber optic monitoring segment numbers, peak amplitude, short-term energy, energy change rate, envelope characteristics, and response range of adjacent monitoring segments. If multiple abnormal windows are consecutive in time or the interval is less than the preset merging interval, they are merged into the same candidate abnormal event; if an abnormal window appears isolated within a single window and does not meet the persistence verification condition, it is discarded as transient noise. After completing the above processing, the abnormal event detection module only outputs the candidate abnormal events and their basic characteristic parameters, without determining whether they belong to low-altitude aircraft targets at this stage. Instead, the candidate abnormal events are transmitted to the target discrimination unit, which further combines rotor harmonic characteristics, spatial continuity, double-end time difference constraints, and continuous trajectory characteristics to determine the target type. This processing method can retain the weak vibration signal induced by the downwash airflow of low-altitude aircraft while reducing the impact of natural background disturbances, transient pulse interference, and local abnormal noise on the subsequent discrimination process.

[0048] 4) Target discrimination unit.

[0049] The target discrimination unit adopts a four-element joint discrimination mechanism of "rotor harmonic fingerprint recognition + adjacent segment spatial continuity analysis + dual-end time difference constraint + continuous trajectory confirmation". It integrates discrimination algorithm module, interference differentiation module and confidence evaluation module to achieve accurate differentiation between low-altitude aircraft events and interference events.

[0050] The discrimination algorithm module is as follows: Figure 2 The five-level discrimination logic shown performs discrimination operations. Each level of discrimination logic is implemented by an independent functional layer, specifically: The first layer is the event triggering layer, used to receive abnormal vibration segments output by the signal processing unit and complete the initial screening of abnormal events. The second layer is the rotor harmonic screening layer, used to extract the main frequency, harmonics, and harmonic distribution in the signal by performing short-time Fourier transform (STFT) or wavelet analysis on the abnormal segment signal, to determine whether there are stable main frequency intervals and multi-level harmonic peaks, and to capture the rotor harmonic fingerprint feature of "group appearance of fundamental frequency plus harmonics" unique to multi-rotor aircraft. The third layer is the spatial consistency layer, used to determine whether a continuous vibration has formed by analyzing the vibration response signals of adjacent monitoring segments. The first layer is the dynamic response envelope, and whether the response center exhibits smooth movement or short-term hovering to exclude isolated local vibration interference; the second layer is the trajectory confirmation layer, which tracks the positional changes of abnormal vibration segments within a continuous time window (1-3s) to verify whether a traceable and predictable spatiotemporal trajectory can be formed, and to exclude sudden and discrete interference events; the third layer is the comprehensive confidence judgment layer, which combines the judgment results of the first four layers to set a confidence threshold (threshold range 0.7-0.9). When the judgment confidence reaches the threshold, "low-altitude aircraft event" is output; otherwise, it is judged as an interference event.

[0051] As a preferred implementation, the interference differentiation module is specifically designed to distinguish drones from common interference events such as wind and footsteps. It establishes a discrimination model based on the differences in vibration characteristics among these three events. Specifically, the interference differentiation module uses the harmonic characteristics, spatial response characteristics, temporal duration characteristics, trajectory continuity characteristics, and pulse rhythm characteristics of candidate abnormal events as input features to construct an event feature vector. : ; in, It represents the harmonic stability characteristics and is used to characterize whether candidate anomalous events have a stable dominant frequency and multiple harmonic peaks; It represents the spatial response characteristics, used to characterize whether abnormal vibrations form a continuous response across multiple adjacent monitoring segments; It represents the duration characteristic and is used to characterize whether an abnormal signal persists within a continuous time window; This indicates the continuity of the trajectory and is used to characterize whether the response center has smooth movement or short-term hovering characteristics; It represents the pulse rhythm characteristics and is used to characterize whether an abnormal signal exhibits a short-duration, intermittent, locally concentrated pulse response.

[0052] Based on the above feature vectors, feature matching models are established for low-altitude aircraft events, wind events, and footstep events, respectively, denoted as: ; ; ; in, This represents a low-altitude aircraft event model. This represents a wind event model. Represents a footstep event model; "This indicates that such events typically have corresponding characteristics," "" indicates that this type of event typically does not have corresponding characteristics. The interference differentiation module distinguishes events based on the feature vectors of candidate anomalies. The matching degree between the event and various event models is calculated, and the matching scores for low-altitude aircraft, wind, and footsteps are calculated respectively. The event type with the highest matching score that exceeds the preset discrimination threshold is taken as the preliminary category of candidate abnormal events.

[0053] Furthermore, the vibration signal corresponding to the UAV exhibits characteristics such as a narrow-band main peak with multiple harmonics, continuous response across multiple monitoring segments, a smooth movement or short-term hovering of the response center, and repetitive visibility within a continuous time window. Therefore, its harmonic stability characteristics, spatial response characteristics, temporal duration characteristics, and trajectory continuity characteristics all show a high degree of matching, while its pulse rhythm characteristics show a low degree of matching. The vibration signal corresponding to wind is characterized by large-scale, weakly localized, background disturbances, lacking a stable harmonic stack and unable to form a trackable local motion trajectory. Therefore, its temporal duration characteristics may be strong, but its harmonic stability characteristics, spatial local continuity characteristics, and trajectory continuity characteristics show a low degree of matching. The vibration signal corresponding to footsteps exhibits a localized, pulsed, and intermittent response, with concentrated vibration amplitude and short duration. The event rhythm differs significantly from the continuous vibration generated by the rotor's continuous downwash. Therefore, its pulse rhythm characteristics show a high degree of matching, while its harmonic stability characteristics, temporal duration characteristics, and trajectory continuity characteristics show a low degree of matching.

[0054] Furthermore, the interference differentiation module uses a weighted scoring method to calculate the matching degree between candidate abnormal events and various event models. The calculation form is as follows: ; in, Indicates that the candidate exception event belongs to the first Matching score for class events Indicates the first The weights of each feature Indicates the first The first feature and the second Matching values ​​for event-like models This indicates the number of features involved in the discrimination.

[0055] If the matching score of a low-altitude aircraft event is higher than that of a wind event and a footstep event, and exceeds a preset matching threshold, then the candidate abnormal event will be output as a suspected low-altitude aircraft event; if the matching score of a wind event or a footstep event is higher, then it will be removed as an interference event or its alarm confidence will be reduced.

[0056] The confidence assessment module is used to quantitatively evaluate the discrimination results. Combining the rotor harmonic screening results, spatial consistency analysis results, trajectory confirmation results, and interference differentiation results, it outputs a comprehensive confidence score to provide a basis for subsequent early warning. As an optional implementation, machine learning algorithms such as support vector machines and random forests can also be introduced as subordinate optimization schemes. By training samples, feature weights and discrimination thresholds can be optimized to further improve discrimination accuracy and anti-interference ability.

[0057] 5) Positioning unit.

[0058] The positioning unit communicates bidirectionally with the target discrimination unit and the fiber optic analyzer, and integrates a position mapping module, a time difference calculation module, a peak positioning module, and a trajectory tracking module to achieve accurate positioning and trajectory tracking of low-altitude aircraft.

[0059] The location mapping module pre-stores the fiber optic loop laying location information. By establishing a mapping relationship between each monitoring point along the fiber optic line and the actual geographical coordinates, a location mapping table is formed to ensure the accurate correspondence between the vibration signal location and the actual geographical location.

[0060] The time difference calculation module is used to calculate the time difference between the two ends of the optical fiber loop when the same vibration signal is received, combined with the propagation speed of the optical signal in the optical fiber (approximately 2 × 10⁻⁶). 8 (m / s), to preliminarily calculate the approximate location where the vibration occurred.

[0061] The peak location module is used to extract the peak vibration amplitude of the abnormal vibration segment, and combined with the location mapping table, to determine the monitoring segment with the strongest vibration and accurately locate the target.

[0062] The trajectory tracking module is used to track the position changes of low-altitude aircraft in real time. By combining the positioning results within a continuous time window, it generates the target's motion trajectory and calculates parameters such as the target's flight speed and direction, providing staff with comprehensive target motion information.

[0063] 6) Early warning output unit.

[0064] The early warning output unit is electrically connected to the positioning unit and integrates a data storage module, a visualization output module, an audible and visual alarm module, and a data interface module to realize multi-form output of monitoring results and support for subsequent processing.

[0065] The data storage module is used to store the raw vibration signals collected by the fiber optic analyzer, the characteristic data after signal processing, the target discrimination results, the positioning information and the motion trajectory data. The storage time is no less than 30 days, which is convenient for subsequent traceability and analysis.

[0066] The visualization output module uses an LCD screen or host computer software to display the fiber optic cable distribution map of the monitored area, the real-time coordinates of the target, the movement trajectory, the judgment confidence level, and the alarm status in real time, presenting the monitoring results intuitively.

[0067] The audible and visual alarm module is used to automatically trigger audible and visual alarms when a low-altitude aircraft event is detected. The alarm sound intensity is not less than 80dB, and the alarm light uses a red flashing mode to remind staff to take timely action.

[0068] The data interface module supports integration with security systems and monitoring center platforms, enabling real-time transmission of monitoring data and alarm information to relevant platforms, thus facilitating collaborative operation among multiple systems.

[0069] Example 2 This embodiment discloses a method for detecting low-altitude aircraft based on distributed optical fiber vibration sensing.

[0070] Low-altitude aircraft detection methods based on distributed fiber optic vibration sensing include: The vibration response signals at both ends of the shallowly buried distributed optical fiber loop are obtained, and the position mapping relationship along the optical fiber is established. The vibration response signal is preprocessed to extract abnormal vibration events; The abnormal vibration event is extracted with multidimensional features including harmonic features, time-domain envelope features, energy distribution features of adjacent monitoring segments, time difference features of demodulation at both ends, and continuous trajectory features. Joint discrimination of abnormal vibration events based on multidimensional features to identify low-altitude aircraft events; The location of the low-altitude aircraft is determined based on the optical fiber location mapping relationship, the demodulation time difference between the two ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments, and the positioning results and alarm information are output.

[0071] Furthermore, joint discrimination is performed on abnormal vibration events, including: Based on whether the candidate abnormal event has a stable dominant frequency and multiple harmonic peaks, it is determined whether the candidate abnormal event meets the harmonic characteristic conditions of a low-altitude aircraft. Based on the continuous response of the candidate abnormal event in adjacent monitoring segments, determine whether the candidate abnormal event satisfies the spatial continuity condition; Based on the positional changes of the candidate abnormal event within a continuous time window, determine whether the candidate abnormal event satisfies the trajectory continuity condition.

[0072] Furthermore, the joint discrimination of abnormal vibration events also includes: comparing the interference characteristics of candidate abnormal events with those of wind events and footstep events; when a candidate abnormal event does not meet the continuous dispersed disturbance characteristics of wind events and does not meet the intermittent pulse disturbance characteristics of footstep events, the candidate abnormal event is determined to be a candidate event of a low-altitude aircraft.

[0073] Furthermore, the low-altitude aircraft detection method based on distributed fiber optic vibration sensing can be implemented through the following steps: Step 1: Signal Acquisition.

[0074] The shallow-buried distributed optical fiber loop is pre-laid and debugged to ensure the loop is intact, the mechanical connection between the optical fiber resolver and both ends of the fiber is sealed, and there is no signal leakage. The optical fiber resolver is then activated, and the laser transmitter emits a continuous and stable 1550nm pulsed laser into the optical fiber loop. During laser propagation in the fiber, when a low-altitude aircraft flies at low altitude over the area to be monitored, the downwash airflow generated by its rotor rotation acts on the ground surface, inducing vibrations in the shallow subsurface. This vibration is transmitted to the shallow-buried optical fiber loop, causing slight deformation of the fiber, which in turn causes changes in the intensity and phase of the backscattered light signal in the fiber. The optical receiver receives the changed backscattered light signal, converts it into an electrical signal, and transmits it to the signal demodulator. The demodulator performs preliminary demodulation of the electrical signal, filters noise during optical signal transmission, and outputs a standardized vibration response signal along the fiber. This signal is transmitted to the signal processing unit through a data interface. The entire process does not rely on wireless signal transmission, ensuring normal operation even in environments with radio suppression and limited communication.

[0075] Furthermore, during the laying of the fiber optic loop, obstacles such as underground pipelines and building foundations must be avoided. After laying, a sealing test and vibration sensing test must be conducted to ensure that the fiber optic loop is undamaged, has no signal leakage, and that the vibration sensing sensitivity meets monitoring requirements (the minimum detectable vibration amplitude is not less than 10). -9 m).

[0076] Step 2: Extracting abnormal events.

[0077] The signal processing unit receives the vibration response signal transmitted by the fiber optic analyzer. First, it filters out natural interferences such as soil thermal expansion and contraction, minor airflow disturbances, and electronic noise using an adaptive Kalman filter algorithm combined with wavelet denoising technology, retaining the effective vibration signal. Then, it uses a sliding window method to segment the continuous vibration signal into several signal segments according to a time window of 0.5-1s. The feature extraction module extracts the time-domain features (peak value, amplitude, pulse width, time-domain envelope) and frequency-domain features (dominant frequency, harmonic amplitude, frequency distribution) of each signal segment. The abnormal event detection module presets vibration amplitude thresholds and change trend thresholds, compares the feature parameters of each signal segment with the thresholds, and determines an abnormal vibration segment when the vibration amplitude of a signal segment exceeds the amplitude threshold and the change trend conforms to abnormal characteristics, thus completing the coarse screening of abnormal events. The feature data of the abnormal vibration segment is then transmitted to the target discrimination unit to exclude normal vibration signals with no monitoring value.

[0078] Furthermore, the filtering parameters of the adaptive Kalman filter algorithm can be adaptively adjusted according to the environmental characteristics of the area to be monitored. The wavelet denoising technology adopts the db4 wavelet basis and the number of decomposition layers is 3-5, ensuring that noise can be effectively filtered without losing effective vibration signals. The duration of the sliding window can be adjusted according to the monitoring accuracy requirements. A 0.5s window is used in the core monitoring area and a 1s window is used in the edge area to balance monitoring accuracy and processing efficiency.

[0079] Step 3: Joint feature discrimination. The target discrimination unit receives the feature data of the abnormal vibration segment and performs joint discrimination operation according to the five-level discrimination logic.

[0080] 1) Event Trigger: Confirm the validity of the abnormal vibration segment, eliminate false abnormal signals caused by fiber optic damage or poor contact, and complete the initial screening of abnormal events.

[0081] 2) Rotor harmonic screening: Perform short-time Fourier transform (STFT) or wavelet analysis on the abnormal signal to extract the main frequency, harmonics and harmonic distribution in the signal, and determine whether there is a stable main frequency interval and multi-level harmonic peaks. If the feature of "group appearance of fundamental frequency plus harmonics" exists, it is initially determined to be a suspected low-altitude aircraft event; otherwise, it is determined to be a potential interference event.

[0082] 3) Spatial consistency analysis: retrieve vibration response signals from adjacent monitoring segments, analyze whether the vibration amplitude and time domain envelope of each adjacent monitoring segment form a continuous response envelope, and whether the response center shows a smooth movement or short-term hovering state. If these conditions are met, a suspected low-altitude aircraft event is further confirmed. If these conditions are not met (e.g., only a single monitoring segment has vibration, or the response envelope is discrete), it is determined to be an interference event.

[0083] 4) Trajectory confirmation: Within a continuous time window of 1-3 seconds, track the positional changes of the abnormal vibration segment to verify whether a traceable and predictable spatiotemporal trajectory can be formed. If the trajectory is continuous and smooth and conforms to the flight characteristics of low-altitude aircraft (such as uniform movement and short-term hovering), the confidence of the suspected event is increased. If the trajectory is discrete and irregular, it is determined to be an interference event.

[0084] 5) Comprehensive Confidence Judgment: Based on the results of the first four layers of discrimination, the comprehensive confidence is calculated. When the confidence reaches the preset threshold of 0.7-0.9, the "low-altitude aircraft event" is output. At the same time, through the interference differentiation module, the target type is further confirmed and interference is eliminated by combining the differences in vibration characteristics of drones, wind, and footsteps. When the confidence does not reach the threshold, it is judged as an interference event and no alarm is triggered.

[0085] Furthermore, the window length of the short-time Fourier transform is set to 256-512 points, with an overlap rate of 50%-75%, to ensure accurate extraction of harmonic features. The confidence threshold can be adaptively adjusted according to the interference situation in the monitored area. In scenarios with more interference (such as densely populated scenic spots), the threshold can be increased to 0.8-0.9, while in scenarios with less interference, the threshold can be adjusted to 0.7-0.8 to reduce false alarms and false negatives.

[0086] Step 4: Target positioning.

[0087] Based on the low-altitude aircraft event signal and corresponding abnormal vibration segment data output by the target discrimination unit received by the positioning unit, the system first uses the position mapping module to call the pre-stored fiber optic position mapping table to determine the location of the fiber optic monitoring point corresponding to the abnormal vibration segment. Then, the time difference calculation module calculates the time difference between the two ends of the fiber optic loop receiving the vibration signal, and combines it with the propagation speed of the light signal in the fiber optic to preliminarily calculate the approximate location of the vibration. The peak positioning module extracts the peak value of the vibration amplitude of the abnormal vibration segment, determines the monitoring segment with the strongest vibration, and, combined with the approximate location, accurately calculates the real-time geographic coordinates of the low-altitude aircraft. The trajectory tracking module tracks the target's position changes in real time, combines the positioning results within a continuous time window to generate the target's motion trajectory, calculates the target's flight speed, flight direction, and other parameters, and transmits the positioning information and trajectory data to the early warning output unit.

[0088] Furthermore, the location mapping table is established using GPS positioning technology to accurately locate each monitoring point along the optical fiber, with a positioning accuracy of no less than 1m; the time difference calculation uses a high-precision timing module with a timing accuracy of no less than 1ns, ensuring the accuracy of the time difference calculation, thereby improving the positioning accuracy, and ultimately achieving a positioning accuracy of no less than 5m.

[0089] Step 5: Early warning output.

[0090] The early warning output unit receives positioning information, movement trajectory, and target identification results transmitted by the positioning unit. First, it stores the relevant data through the data storage module for subsequent tracing and analysis. Then, through the visualization output module, it displays in real-time the fiber optic cable distribution map of the monitored area, the target's real-time coordinates, movement trajectory, identification confidence level, and alarm status on an LCD screen or host computer software. When a low-altitude aircraft event is identified, the audible and visual alarm module automatically triggers an alarm to alert staff for timely action. Simultaneously, the monitoring data and alarm information are transmitted in real-time to the security system and monitoring center platform via the data interface module, enabling multi-system collaborative operation. Staff can then take control and removal measures based on the early warning information.

[0091] Furthermore, the low-altitude aircraft detection method based on distributed fiber optic vibration sensing also includes a system calibration step, namely: every 15-30 days, the fiber optic resolver, signal processing unit, and positioning unit are calibrated. The vibration signal induced by the downwash airflow of the low-altitude aircraft is simulated by a standard vibration source, and the parameters of each unit are adjusted to ensure that the detection accuracy, discrimination accuracy, and positioning accuracy of the system meet the monitoring requirements. When the environment of the area to be monitored changes (such as seasonal changes or terrain changes), the system parameters need to be recalibrated to improve the environmental adaptability of the system.

[0092] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0093] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A low-altitude aircraft detection system based on distributed fiber optic vibration sensing, characterized in that, include: A shallow-buried distributed optical fiber loop is buried in the shallow layer of the ground surface in the area to be monitored, forming a closed loop along the area to be monitored. The burial range can effectively capture the ground coupling vibration induced by the downwash airflow of low-altitude aircraft. When the low-altitude aircraft flies at low altitude in the area to be monitored, the downwash airflow generated by its rotor rotation acts on the ground surface, inducing vibration in the shallow layer of the ground surface. This vibration is transmitted to the shallow-buried optical fiber loop, causing the optical fiber to undergo slight deformation, which in turn causes changes in the intensity and phase of the backscattered light signal in the optical fiber. An optical fiber analyzer is connected to both ends of the shallowly buried distributed optical fiber loop and is used to acquire vibration response signals of each monitoring section along the shallowly buried distributed optical fiber loop. The signal processing unit is used to preprocess the vibration response signal and extract abnormal vibration events; The target discrimination unit, based on a four-element joint discrimination mechanism of rotor harmonic fingerprint recognition, adjacent segment spatial continuity analysis, dual-end time difference constraint, and continuous trajectory confirmation, integrates a discrimination algorithm module, an interference differentiation module, and a confidence assessment module. It extracts harmonic features, time-domain envelope features, adjacent monitoring segment energy distribution features, dual-end demodulation time difference features, and continuous trajectory features from the abnormal vibration events to identify low-altitude aircraft events. The integrated discrimination algorithm module performs discrimination operations based on a five-level discrimination logic, with each level implemented by an independent functional layer: the first layer is the event triggering layer, used for preliminary screening of abnormal events; the second layer is the rotor harmonic screening layer, used to capture rotor harmonic fingerprint features; the third layer is the spatial consistency layer, used to perform vibration response envelope judgment and exclude isolated local vibration interference based on the state response; the fourth layer is the trajectory confirmation layer, used to exclude sudden and discrete interference events; and the fifth layer is the comprehensive confidence judgment layer, used to set a confidence threshold based on the discrimination results of the first four layers and comprehensively determine interference events based on the threshold comparison results. The positioning unit is used to determine the position of the low-altitude aircraft based on the position mapping relationship along the optical fiber, the demodulation time difference at both ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments. The early warning output unit is used to output the target position, trajectory, and alarm information of low-altitude aircraft.

2. The low-altitude aircraft detection system based on distributed fiber optic vibration sensing as described in claim 1, characterized in that, The shallow-buried distributed optical fiber loop adopts a closed loop structure deployed along the boundary of the area to be monitored, and a serpentine loop is used for enhanced deployment inside the area to be monitored.

3. The low-altitude aircraft detection system based on distributed fiber optic vibration sensing as described in claim 1, characterized in that, The signal processing unit performs filtering, segmentation, time-frequency transformation, and abnormal triggering processing on the vibration response signal to obtain candidate abnormal events.

4. The low-altitude aircraft detection system based on distributed fiber optic vibration sensing as described in claim 3, characterized in that, The signal processing unit includes a signal filtering module, a signal segmentation module, a feature extraction module, and an abnormal event detection module. The abnormal event detection module employs a combination of thresholding and trend analysis. It presets vibration amplitude thresholds and trend thresholds. When the characteristic parameters of a signal segment exceed either preset threshold, it is determined to be an abnormal vibration segment, thus completing the coarse screening of abnormal events. Instead of directly determining the target type, it only transmits the events corresponding to the abnormal signal segments as candidate abnormal events to the target discrimination unit.

5. The low-altitude aircraft detection system based on distributed fiber optic vibration sensing as described in claim 1, characterized in that, The positioning unit includes a position mapping module, a time difference calculation module, a peak positioning module, and a trajectory tracking module. The position mapping module pre-stores the fiber optic loop laying location information and establishes a mapping relationship between each monitoring point along the fiber optic line and the actual geographical coordinates to form a position mapping table, so as to ensure that the vibration signal position corresponds to the actual geographical location.

6. A method for detecting low-altitude aircraft based on distributed fiber optic vibration sensing, characterized in that, include: The vibration response signals at both ends of the shallowly buried distributed optical fiber loop are acquired, and the position mapping relationship along the optical fiber is established. Among them, the burial range can effectively capture the surface coupling vibration induced by the downwash airflow of low-altitude aircraft. When the low-altitude aircraft flies at low altitude in the area to be monitored, the downwash airflow generated by its rotor rotation acts on the ground surface, inducing vibration in the shallow ground layer. This vibration is transmitted to the shallowly buried optical fiber loop, causing the optical fiber to undergo slight deformation, which in turn causes changes in the intensity and phase of the backscattered light signal in the optical fiber. The vibration response signal is preprocessed to extract abnormal vibration events; The abnormal vibration event is extracted with multidimensional features including harmonic features, time-domain envelope features, energy distribution features of adjacent monitoring segments, time difference features of demodulation at both ends, and continuous trajectory features. A multi-dimensional feature-based joint discrimination of abnormal vibration events is used to identify low-altitude aircraft events. Specifically, a four-element joint discrimination mechanism based on rotor harmonic fingerprint recognition, adjacent segment spatial continuity analysis, dual-end time difference constraints, and continuous trajectory confirmation is integrated with a discrimination algorithm module, an interference differentiation module, and a confidence assessment module to achieve accurate differentiation between low-altitude aircraft events and interference events. The integrated discrimination algorithm module performs discrimination operations based on a five-level discrimination logic, with each level implemented by an independent functional layer: the first layer is the event triggering layer, used for preliminary screening of abnormal events; the second layer is the rotor harmonic screening layer, used to capture rotor harmonic fingerprint features; the third layer is the spatial consistency layer, used to judge the vibration response envelope and exclude isolated local vibration interference based on the state response; the fourth layer is the trajectory confirmation layer, used to exclude sudden and discrete interference events; and the fifth layer is the comprehensive confidence judgment layer, used to set a confidence threshold based on the discrimination results of the first four layers and comprehensively judge interference events based on the threshold comparison results. The location of the low-altitude aircraft is determined based on the optical fiber location mapping relationship, the demodulation time difference between the two ends, the characteristic peak segment, and the energy distribution of adjacent monitoring segments, and the positioning results and alarm information are output.

7. The low-altitude aircraft detection method based on distributed fiber optic vibration sensing as described in claim 6, characterized in that, Joint discrimination of abnormal vibration events includes: Based on whether the candidate abnormal event has a stable dominant frequency and multiple harmonic peaks, it is determined whether the candidate abnormal event meets the harmonic characteristic conditions of a low-altitude aircraft. Based on the continuous response of the candidate abnormal event in adjacent monitoring segments, determine whether the candidate abnormal event satisfies the spatial continuity condition; Based on the positional changes of the candidate abnormal event within a continuous time window, determine whether the candidate abnormal event satisfies the trajectory continuity condition.

8. The low-altitude aircraft detection method based on distributed fiber optic vibration sensing as described in claim 7, characterized in that, The joint discrimination of abnormal vibration events also includes: comparing the interference characteristics of candidate abnormal events with those of wind events and footstep events; when a candidate abnormal event does not meet the continuous dispersed disturbance characteristics of wind events and does not meet the intermittent pulse disturbance characteristics of footstep events, the candidate abnormal event is determined to be a candidate event of a low-altitude aircraft.

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