A method, apparatus, storage medium, and electronic device for monitoring low-altitude flight paths.

Abstract

This application discloses a method, apparatus, storage medium, and electronic device for monitoring low-altitude flight paths, relating to the field of information technology. The method includes: acquiring the position information and geomagnetic field strength of each sampled track point when an aircraft flies along a target flight path; generating a flight track point sequence for the aircraft under different sliding windows based on the position information and geomagnetic field strength of each sampled track point; searching for a reference track point sequence corresponding to the flight track point sequence from a standard flight path geomagnetic fingerprint template library based on the position information of each track point in the flight track point sequence; calculating the similarity between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence; and determining in real time whether there is any abnormal behavior when the aircraft flies along the target flight path based on the similarity. This application can effectively address abnormal behaviors such as GNSS deception and track deviation.

Description

Technical Field

[0001] This application relates to the field of information technology, and in particular to a method, apparatus, storage medium and electronic device for monitoring low-altitude air routes. Background Technology

[0002] As an emerging industry, the low-altitude economy is experiencing a golden age of rapid development. With continuous technological advancements, technologies for low-altitude aircraft such as drones and electric vertical takeoff and landing (eVTOL) aircraft are maturing, providing solid technological support for the development of the low-altitude economy.

[0003] High-precision navigation and positioning are the primary support for flight path planning and monitoring in the low-altitude airspace. Most existing low-altitude aircraft rely on GNSS (Global Positioning System) and BeiDou (Global Navigation Satellite System) positioning methods for navigation support. It is important to note that GNSS positioning faces the risk of positioning rejection in certain environments (typically urban canyons), making GNSS-based navigation and positioning methods alone insufficient to meet the rapidly evolving needs of the low-altitude airspace. Furthermore, relying solely on GNSS positioning for flight path monitoring carries risks such as GNSS spoofing. Because aircraft lack effective means to distinguish between valid and fake GNSS messages, they are highly susceptible to GNSS spoofing, leading to various dangers such as flight path deviations, uncontrollable flight, and difficulty in tracing standard reference trajectories.

[0004] Currently, to address the shortcomings of GNSS positioning, existing flight path monitoring methods typically require the deployment of radar and integrated sensing equipment along pre-defined flight paths. However, this passive monitoring approach, when there are a large number of aircraft along the flight path, is limited by the processing capacity of the equipment, leading to problems such as monitoring gaps and delays, which can easily cause flight accidents. Moreover, the installation of a large number of devices also results in high deployment costs. Summary of the Invention

[0005] In view of this, this application provides a method, device, storage medium and electronic device for monitoring low-altitude flight paths, which mainly solves the problems of lack of monitoring and lag in GNSS spoofing and track deviation scenarios, effectively responds to abnormal behaviors such as GNSS spoofing and track deviation, and can also reduce deployment costs.

[0006] According to a first aspect of this application, a method for monitoring low-altitude flight paths is provided, the method comprising:

[0007] Acquire the location information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route;

[0008] Based on the location information and geomagnetic field strength of each sampled track point, a sequence of flight track points for the aircraft under different sliding windows is generated;

[0009] Based on the position information of each track point in the flight track point sequence, the reference track point sequence corresponding to the flight track point sequence is searched from the standard route geomagnetic fingerprint template library. The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route. The standard reference trajectory includes the position information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength.

[0010] Based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence, the similarity between the flight track point sequence and the reference track point sequence is calculated.

[0011] Based on the similarity, it is determined in real time whether the aircraft exhibits any abnormal behavior while flying along the target route.

[0012] According to a second aspect of this application, a low-altitude flight path monitoring device is provided, the device comprising:

[0013] The acquisition unit is used to acquire the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route.

[0014] The generation unit is used to generate a sequence of flight track points of the aircraft under different sliding windows based on the position information of each sampled track point and the geomagnetic field strength.

[0015] The search unit is used to search for the reference track point sequence corresponding to the flight track point sequence from the standard route geomagnetic fingerprint template library based on the position information of each track point in the flight track point sequence. The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route. The standard reference trajectory includes the position information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength.

[0016] The calculation unit is used to calculate the similarity between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence.

[0017] The determination unit is used to determine in real time whether the aircraft exhibits abnormal behavior while flying along the target route based on the similarity.

[0018] According to a third aspect of this application, a storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the aforementioned low-altitude flight path monitoring method.

[0019] According to a fourth aspect of this application, an electronic device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the aforementioned low-altitude flight path monitoring method.

[0020] By employing the aforementioned technical solution, this application provides a low-altitude flight path monitoring method, apparatus, storage medium, and electronic device. Compared to existing flight path monitoring methods, this method can acquire flight path sequence sequences of an aircraft flying along a target flight path under different sliding windows. By comparing these sequences with reference path sequence sequences in a pre-configured standard flight path geomagnetic fingerprint template library, it can identify changes in geomagnetic characteristics within the geomagnetic fence in real time. This allows for timely detection of abnormal behaviors such as GNSS spoofing and path deviation, effectively addressing the problems of monitoring gaps and delays in GNSS spoofing and path deviation scenarios. Furthermore, compared to existing technologies, this application can reduce the number of monitoring devices on the flight path, thereby reducing deployment costs and improving monitoring efficiency.

[0021] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0023] Figure 1 A flowchart illustrating a low-altitude flight path monitoring method provided in an embodiment of this application is shown.

[0024] Figure 2 A flowchart illustrating the method for constructing a standard airway geomagnetic fingerprint template library provided in an embodiment of this application is shown.

[0025] Figure 3 A satellite map schematic diagram of route 1 provided in an embodiment of this application is shown;

[0026] Figure 4 A satellite map schematic diagram of route 2 provided in an embodiment of this application is shown;

[0027] Figure 5 A satellite map schematic diagram of route 3 provided in an embodiment of this application is shown;

[0028] Figure 6 This paper illustrates three initial standard reference trajectories provided in an embodiment of this application.

[0029] Figure 7 This paper presents a schematic diagram of the geomagnetic field intensity variation curve of the initial standard reference trajectory provided in an embodiment of this application.

[0030] Figure 8 A schematic diagram of a standard reference trajectory provided in an embodiment of this application is shown;

[0031] Figure 9 This paper presents a schematic diagram of the geomagnetic field intensity variation curve of the standard reference trajectory provided in the embodiments of this application;

[0032] Figure 10 This paper presents a schematic diagram of the geomagnetic field intensity variation curve of the deception trajectory provided in an embodiment of this application;

[0033] Figure 11 This paper illustrates a schematic diagram of the actual flight path of the deception trajectory provided in an embodiment of this application.

[0034] Figure 12 This illustration shows a schematic diagram of the trajectory calculated based on incorrect positioning after a drone is lured, according to an embodiment of this application.

[0035] Figure 13 A schematic diagram of the determination result for trajectory 0 provided in an embodiment of this application is shown;

[0036] Figure 14 A schematic diagram of the determination result for trajectory 1 provided in an embodiment of this application is shown;

[0037] Figure 15 A schematic diagram of the determination result for trajectory 2 provided in an embodiment of this application is shown;

[0038] Figure 16 A schematic diagram of the determination result for trajectory 3 provided in an embodiment of this application is shown;

[0039] Figure 17 A schematic diagram of the determination result for trajectory 4 provided in an embodiment of this application is shown;

[0040] Figure 18 A schematic diagram of the determination result for trajectory 5 provided in an embodiment of this application is shown;

[0041] Figure 19 A schematic diagram of the determination result for trajectory 6 provided in an embodiment of this application is shown;

[0042] Figure 20 A schematic diagram of the determination result for trajectory 7 provided in an embodiment of this application is shown;

[0043] Figure 21 A schematic diagram of the determination result for trajectory 8 provided in an embodiment of this application is shown;

[0044] Figure 22 A schematic diagram of the determination result for trajectory 9 provided in an embodiment of this application is shown;

[0045] Figure 23 A schematic diagram of the determination result for trajectory 10 provided in an embodiment of this application is shown;

[0046] Figure 24 A schematic diagram of the structure of a low-altitude flight path monitoring device provided in an embodiment of this application is shown. Detailed Implementation

[0047] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0048] Existing regulatory methods suffer from gaps and delays in oversight, which can easily lead to flight accidents, and are also costly to implement.

[0049] To address the aforementioned issues, this invention presents a system architecture for monitoring low-altitude flight routes, comprising three main parts: the construction of a standard flight route geomagnetic fingerprint template library, the pre-installation of a quasi-flight geomagnetic fingerprint template library, and the discrimination of changes in geomagnetic features within geomagnetic fences.

[0050] In constructing the standard flight path geomagnetic fingerprint template library, after the flight path planning is completed, a low-altitude aircraft equipped with a geomagnetic sensing unit first flies within the flight path. During the flight, geomagnetic field strength data is collected in real time to complete the construction of the standard flight path geomagnetic fingerprint template library. The standard flight path geomagnetic fingerprint template library records a standard reference trajectory for that flight path. This standard reference trajectory includes the position coordinates and geomagnetic field strength of all location points, which can be specifically represented as follows: ,in, Indicating the first in the standard reference trajectory i The position coordinates of each point Indicating the first in the standard reference trajectory i The geomagnetic field strength at each location point.

[0051] For the pre-installation of the standard route geomagnetic fingerprint template library, after the standard route geomagnetic fingerprint template library is built, it is pre-configured through remote or manual connection during the take-off phase of low-altitude aircraft to provide support for subsequent geomagnetic-based route supervision.

[0052] To identify changes in geomagnetic characteristics within the geomagnetic fence, the system monitors geomagnetic changes in real time during the flight of the aircraft along the designated route. When abnormal behaviors such as GNSS spoofing and track deviation are detected, an alarm function will be activated to ensure that the aircraft flies in accordance with the designated route.

[0053] This invention provides a low-altitude flight path monitoring method, primarily used to identify abnormal behaviors such as GNSS spoofing and track deviations of aircraft during designated flight path phases. Figure 1 As shown, the method includes:

[0054] Step 10: Obtain the location information and geomagnetic field intensity of each sampling track point when the aircraft flies along the target route.

[0055] The aircraft mainly include drones, small light helicopters, electric vertical take-off and landing aircraft, airships, and rotorcraft. The target route is any route planned for the aircraft. The sampling track point is the location point where the geomagnetic sensing unit collects information when the aircraft flies along the target route. The location information of the sampling track point includes longitude, latitude, and altitude relative to the ground.

[0056] In this embodiment of the invention, before the aircraft takes off, a designated route (target route) needs to be set for the aircraft, and a pre-built standard route geomagnetic fingerprint template library needs to be loaded. Since aircraft may be spoofed by GNSS during flight, it is impossible to determine whether there is abnormal behavior such as deviation from the flight path by latitude and longitude. In this case, the geomagnetic-based flight path monitoring method in the embodiments of the present invention can be used.

[0057] Specifically, during the flight of the aircraft, the geomagnetic sensing unit is used to collect the geomagnetic field intensity at each sampling point in real time. Simultaneously, the location information of each sampling track point is collected. In order to enable the use of location information from each sampled track point and geomagnetic field strength It can detect changes in the magnetic characteristics within the geomagnetic fence, thereby identifying abnormal behaviors such as aircraft deviations from their flight paths.

[0058] Step 20: Based on the location information of each sampled track point and the geomagnetic field strength, generate a sequence of flight track points for the aircraft under different sliding windows.

[0059] The flight trackpoint sequence includes the location information and geomagnetic field strength of multiple trackpoints, and the size of the sliding window can be set according to actual business needs.

[0060] In this embodiment of the invention, after obtaining the position information and geomagnetic field strength of each sampling track point during the flight of the aircraft, a flight track point sequence of the aircraft under different sliding windows is generated based on the position information and geomagnetic field strength of each sampling track point. Specifically, step 20 includes: generating a flight sampling trajectory based on the position information and geomagnetic field strength of each sampling track point; interpolating the flight sampling trajectory to obtain an interpolated flight sampling trajectory; and determining the flight track point sequence of the aircraft under different sliding windows based on the interpolated flight sampling trajectory.

[0061] When determining the interpolated flight sampling trajectory, the flight sampling trajectory is interpolated based on the position information of each sampling track point to obtain the position information of each first interpolation point; for any one of the first interpolation points, several sampling track points closest to the arbitrary first interpolation point are determined from the sampling track points; the geomagnetic field strength of the arbitrary first interpolation point is calculated based on the geomagnetic field strength corresponding to the several sampling track points; and the position information and geomagnetic field strength of each track point in the interpolated flight sampling trajectory are determined based on the position information and geomagnetic field strength of each sampling track point, as well as the position information and geomagnetic field strength of each first interpolation point.

[0062] The sampled trackpoints and the first interpolation point together constitute the trackpoints in the flight trackpoint sequence. The location information of the first interpolation point includes longitude, latitude, and altitude relative to the ground.

[0063] Specifically, based on the location information of each sampling track point and geomagnetic field strength Generate flight sampling trajectory ,in, L This represents the trajectory sampling length. The interpolation interval is then set. d According to the interpolation interval d Interpolate the flight sampling trajectory to obtain the interpolated flight sampling trajectory. The interpolated flight sampling trajectory includes both the first interpolation point and the sampled track points; these are collectively referred to as track points. When calculating the position information of the first interpolation point, the position information of each sampled track point and the interpolation interval can be used as a reference. dCalculations are performed. When calculating the geomagnetic field strength at the first interpolation point, for any given first interpolation point, several sampling track points closest to that point are determined from the sampled track points. Then, based on the geomagnetic field strengths of these sampling track points, the geomagnetic field strength of the first interpolation point is calculated. This can be done by taking the average of the geomagnetic field strengths of these sampling track points, or by performing a weighted summation of the geomagnetic field strengths of these sampling track points. The weighting coefficients of the sampling track points can be determined using inverse distance weighting or a Gaussian kernel function, etc. After calculating the location information and geomagnetic field strength of each first interpolation point, the interpolated flight sampling trajectory is determined based on the location information and geomagnetic field strength of each first interpolation point, as well as the location information and geomagnetic field strength of each sampled track point.

[0064] Furthermore, based on the interpolated flight sampling trajectory, the flight waypoint sequence under different sliding windows is defined as follows:

[0065] .

[0066] By comparing the flight track point sequence with the standard route geomagnetic fingerprint template library, it is possible to determine whether the aircraft exhibits abnormal behaviors such as GNSS deception and track deviation when flying along the target route.

[0067] Step 30: Based on the position information of each track point in the flight track point sequence, search for the reference track point sequence corresponding to the flight track point sequence in the standard route geomagnetic fingerprint template library.

[0068] The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route. The standard reference trajectory includes the location information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength.

[0069] In this embodiment of the invention, to determine the reference track point sequence corresponding to the flight track point sequence in the standard route geomagnetic fingerprint template library, step 30 specifically includes: determining the reference track point sequence under different sliding windows based on the standard reference trajectory in the standard route geomagnetic fingerprint template library; determining the reference track point sequence closest to the flight track point sequence based on the position information of each track point in the flight track point sequence and the position information of each reference track point in the reference track point sequence under different sliding windows; and determining the reference track point sequence closest to the flight track point sequence as the reference track point sequence corresponding to the flight track point sequence.

[0070] Specifically, based on the standard reference trajectory in the standard route geomagnetic fingerprint template library, the reference track point sequence under different sliding windows is defined as follows:

[0071] .

[0072] For any sequence of flight waypoints under a sliding window Calculate its sequence with reference track points under different sliding windows. The average Euclidean distance between The specific formula is as follows:

[0073] .

[0074] Then, based on the calculated average Euclidean distance, find... Minimum reference track point sequence within the corresponding time window Therefore, by following the above method, the reference track point sequence corresponding to the flight track point sequence under different time windows can be determined from the standard route geomagnetic fingerprint template library.

[0075] Step 40: Calculate the similarity between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence.

[0076] In this embodiment of the invention, after determining the reference trackpoint sequence corresponding to the flight trackpoint sequence, the similarity between the geomagnetic field intensities of the two sequences is calculated. Specifically, step 40 includes: calculating the average Euclidean distance between the flight trackpoint sequence and the reference trackpoint sequence based on the geomagnetic field intensities of each trackpoint in the flight trackpoint sequence and the geomagnetic field intensities of each reference trackpoint in the reference trackpoint sequence; and determining the similarity between the flight trackpoint sequence and the reference trackpoint sequence based on the average Euclidean distance.

[0077] Specifically, the first geomagnetic field strength sequence is determined based on the geomagnetic field strength of each waypoint in the flight trackpoint sequence. Simultaneously, based on the geomagnetic field intensity of each reference track point in the reference track point sequence, a second geomagnetic field intensity sequence is determined. Then, the first geomagnetic field intensity sequence was calculated. With the second geomagnetic field intensity sequence The average Euclidean distance between The specific formula is as follows:

[0078] .

[0079] After calculating the average Euclidean distance, this average Euclidean distance can be used to represent the similarity between the flight waypoint sequence and the reference waypoint sequence.

[0080] In addition to using the average Euclidean distance to represent the similarity between two sequences, this invention can also use a correlation coefficient to represent the similarity between two sequences. Based on this, the method further includes: calculating the correlation coefficient between the flight waypoint sequence and the reference waypoint sequence based on the geomagnetic field strength of each waypoint in the flight waypoint sequence and the geomagnetic field strength of each reference waypoint in the reference waypoint sequence; and determining the similarity between the flight waypoint sequence and the reference waypoint sequence based on the correlation coefficient. Wherein, the correlation coefficient... The specific calculation formula is as follows:

[0081] ,

[0082] in, For reference track point sequence The average geomagnetic intensity, ; Flight waypoint sequence The average geomagnetic intensity, .

[0083] After calculating the correlation coefficient, the correlation coefficient can be used to represent the similarity between the flight waypoint sequence and the reference waypoint sequence.

[0084] Step 50: Based on the similarity, determine in real time whether the aircraft exhibits any abnormal behavior while flying along the target route.

[0085] Corresponding to the two implementation methods above, when the average Euclidean distance is used as the similarity index, a distance anomaly threshold is calculated based on the standard deviation of the geomagnetic field strength of each reference track point in the reference track point sequence corresponding to the flight track point sequence. If the average Euclidean distance is greater than the distance anomaly threshold, it is determined that the aircraft exhibits abnormal track deviation behavior in the corresponding sliding window. The specific calculation formula for the distance anomaly threshold is as follows:

[0086] ,

[0087] in, , For reference track point sequence Standard deviation of the geomagnetic field intensity at each reference track point.

[0088] When a correlation coefficient is used as a similarity indicator, if the correlation coefficient is less than or equal to a preset correlation coefficient, it is determined that the aircraft exhibits abnormal behavior of deviating from its flight path within the corresponding sliding window. The preset correlation coefficient can be set according to actual business requirements.

[0089] Furthermore, embodiments of the present invention also provide a method for constructing a standard airway geomagnetic fingerprint template library, such as... Figure 2 As shown, the method includes:

[0090] Step 60: Collect the location information and geomagnetic field intensity of each initial track point on the target route, and generate an initial standard reference trajectory based on the location information and geomagnetic field intensity of each initial track point.

[0091] In this embodiment of the invention, when constructing the standard flight path geomagnetic fingerprint template library, an aircraft equipped with a geomagnetic sensing unit flies along the target flight path to obtain at least one initial standard reference trajectory. The initial standard reference trajectory consists of multiple initial waypoints and flight segments, with any two initial waypoints constituting a flight segment. During the aircraft's flight, the position information and geomagnetic field strength of each initial waypoint are collected. The initial waypoint sequence is defined as... ,in, Indicates the first k The location information of the initial track point includes longitude, latitude, and altitude relative to the ground.

[0092] In addition, an initial set of standard reference trajectories is defined. The m-th initial standard reference trajectory is:

[0093] ,

[0094] in, For the first m The sampling length of the initial standard reference trajectory, For the first m The first initial standard reference trajectory t The location information of the initial waypoints. For the first m The first initial standard reference trajectory t The geomagnetic field strength at each initial track point. This allows us to base our understanding on... An initial standard reference trajectory is established, and a standard route geomagnetic fingerprint template library is constructed.

[0095] Step 70: Based on the position information of each initial track point, interpolate the initial standard reference trajectory to obtain the position information of each second interpolation point.

[0096] In the embodiments of the present invention, at the initial track point and Latitude and longitude interpolation is performed between them, with an interpolation interval of . d The unit is meters, and this generates a sequence of intermediate waypoints, denoted as:

[0097] .

[0098] Then, the interpolated trajectories of all flight segments are merged to obtain the standard reference trajectory corresponding to the target route, denoted as:

[0099] ,

[0100] in, This represents the latitude and longitude coordinates of the nth track point after interpolation. N This represents the total number of interpolation points. The coordinates of the second interpolation point can be determined based on the position information of each initial track point and the interpolation interval. d calculate.

[0101] Step 80: For any one of the second interpolation points, determine several initial track points that are closest to the second interpolation point from the initial track points, and calculate the geomagnetic field strength of the second interpolation point based on the geomagnetic field strength corresponding to the several initial track points.

[0102] For embodiments of the present invention, when calculating any second interpolation point When considering the intensity of the Earth's magnetic field, find the nearest [geomagnetic field]. An initial waypoint, and for Geomagnetic field strength at the initial track point The geomagnetic field strength at the nth second interpolation point is calculated using a weighted average. The specific calculation formula is as follows:

[0103] ,

[0104] in, Indicates and The closest A set of initial waypoints Denotes the weighting coefficients, which satisfy... The weighting coefficients can be selected using inverse distance weighting or Gaussian kernel function. Inverse distance weighting determines the weights based on the inverse power relationship of distance, with closer points having higher weights. Gaussian kernel function dynamically distributes weights through exponential decay of distance, with the weights decreasing exponentially as distance increases.

[0105] Step 90: Based on the geomagnetic field strength of each initial track point and the geomagnetic field strength of each second interpolation point, calculate the standard deviation of the geomagnetic field strength of each initial track point and the standard deviation of the geomagnetic field strength of each second interpolation point, respectively.

[0106] In this embodiment of the invention, the initial track point and the second interpolation point on the standard reference trajectory are collectively referred to as reference track points. The formula for calculating the standard deviation of the geomagnetic field intensity is as follows:

[0107] .

[0108] It should be noted that a geomagnetic field strength standard can also be preset. By comparing the geomagnetic field strength of the reference track point with this standard, the standard deviation of the geomagnetic field strength corresponding to each reference track point can be calculated.

[0109] Step 100: Based on the location information, geomagnetic field strength and standard deviation of each initial track point, and the location information, geomagnetic field strength and standard deviation of each second interpolation point, determine the standard reference trajectory corresponding to the target route, and construct the standard route geomagnetic fingerprint template library corresponding to the target route based on the standard reference trajectory corresponding to the target route.

[0110] The standard route geomagnetic fingerprint template library differs for different routes.

[0111] For embodiments of the present invention, the standard reference trajectory recorded in the standard route geomagnetic fingerprint template library can be specifically represented as follows:

[0112] ,

[0113] in, This represents the position information of the nth reference track point. This represents the geomagnetic field strength at the nth reference track point. This represents the standard deviation of the geomagnetic field strength at the nth reference track point.

[0114] To verify the reliability of the low-altitude flight path monitoring method described in this embodiment of the invention, flight tests were conducted at a test site with airspace usage permits. During the flight, the system simultaneously recorded key parameters such as the UAV's latitude and longitude, altitude, three-axis geomagnetic field strength data, and inertial measurement unit data. This embodiment of the invention designed three flight paths, namely Flight 1, Flight 2, and Flight 3, and the satellite maps of the three flight paths are shown below. Figure 3 , Figure 4 and Figure 5 As shown.

[0115] The following details the process of constructing a standard route geomagnetic fingerprint template library based on geomagnetic field strength data collected from real flight routes. Taking route 3 as an example, route 3 consists of three initial track points and two segments. For route 3, three initial standard reference trajectories were collected. The sampling location coordinates and corresponding geomagnetic field strengths of these trajectories are as follows: Figure 6 and Figure 7 As shown, Figure 6 To illustrate the three initial standard reference trajectories, Figure 7 The curve showing the variation of the geomagnetic field intensity is displayed.

[0116] For the geomagnetic field intensity at the same location on these three initial standard reference trajectories, the average value of the three acquisitions is taken, and then the interpolation interval is set. d =0.3 meters, interpolate the initial standard parameter trajectory to obtain the standard reference trajectory, and then set... =10, and the geomagnetic field strength and standard deviation of the geomagnetic field strength at the nth second interpolation point are calculated using inverse distance weighting, thereby constructing a standard route geomagnetic fingerprint template library. The visual interface of this fingerprint template library is as follows: Figure 8 As shown, Figure 8 The image shows three initial standard reference trajectories, Projected_0, Projected_1, and Projected_2, as well as the standard reference trajectory Fused_Mg from the standard flight path geomagnetic fingerprint template library. Figure 9 This is a curve showing the variation of the geomagnetic field intensity. Figure 9 The data was further plotted with a range of three times the standard deviation above and below the data to reflect the variation range and stability of the geomagnetic characteristics of the flight path.

[0117] The following verifies the track deviation discrimination method based on the differences in real geomagnetic field characteristics of this invention. First, a GNSS decoy trajectory is created, preventing the UAV from determining whether it has deviated from the track using latitude and longitude. The specific implementation process is as follows:

[0118] (1) The UAV performs flight missions along flight path 3, actively deviates from the predetermined flight path during flight, and continuously collects geomagnetic field strength data;

[0119] (2) Project the latitude and longitude information of the deviated track onto route 3 to form a trajectory disguised as not deviating from the route, in order to simulate the scenario where the UAV cannot detect its own deviation by latitude and longitude under GNSS deception.

[0120] This yielded geomagnetic field strength data for a total of 11 decoy trajectories, including one normal flight trajectory. The geomagnetic field strength of each flight trajectory is as follows: Figure 10 As shown, Figure 11 The actual flight paths of these decoy trajectories were shown. Figure 12 The video demonstrates the trajectory calculated based on incorrect positioning after a drone was lured into a trap.

[0121] According to the track deviation discrimination method provided in the embodiments of the present invention, a sliding window is set. W =100, interpolation interval d =0.3 meters, the corresponding discrimination distance is 0.3. 100 = 30 meters. At the same time, set up... c=3. When the geomagnetic field strength within the sliding window deviates from the standard reference trajectory by more than three times the standard deviation, it is considered a deviated trackpoint. Under the above settings, deviation detection is performed on each of the eleven trajectories. To quantify the degree of deviation, this embodiment of the invention defines the deviation rate as the ratio of the number of trackpoints identified as deviated to the total number of trackpoints in that trajectory. The specific calculation formula is as follows:

[0122] ,

[0123] in, This indicates the number of items that were flagged as deviations from the waypoint. This represents the total number of waypoints in the trajectory. Further, the confidence level for trajectory deviation is defined as: Confidence Level = 1 - Deviation Rate. The deviation rates and confidence levels for each trajectory are shown in Table 1 of the test results.

[0124] Table 1. Track deviation detection results based on geomagnetic features in GNSS decoy scenarios.

[0125]

[0126] The experimental results above demonstrate that the track deviation discrimination method based on geomagnetic feature differences proposed in this embodiment can effectively distinguish between normal tracks and abnormal tracks spoofed by GNSS. Table 1 shows that the deviation rate of the normal track is the lowest, at only 8.66%, with a corresponding confidence level of 91.34%. In contrast, the deviation rates of the other spoofed tracks are generally above 20%, with significantly lower confidence levels, fully verifying the robustness and practicality of this method in complex environments.

[0127] Table 2 lists the classification performance metrics of the track deviation discrimination method based on geomagnetic feature differences on 11 test tracks, including accuracy, precision, recall, and F1 score. Overall, most tracks exhibit high accuracy, especially tracks 7, 8, and 9, whose accuracy exceeds 95%, indicating that the method can effectively distinguish between deviation points and normal points. Except for track 10, the recall rates of the remaining tracks reach or approach 100%, indicating that the embodiments of the present invention have few false negatives in detecting deviation points and possess good detection capabilities. Precision fluctuates somewhat; some tracks (such as tracks 1, 2, and 3) have lower precision, possibly indicating some false positives. Track 10 is a normal track; its deviation point recall and precision are both 0, and its F1 score is 0, which is consistent with reality, indicating that this track was not misclassified as a deviation, thus verifying the effectiveness and stability of the method. In summary, the embodiments of the present invention demonstrate good robustness and practicality in judging track deviations under complex GNSS deception environments.

[0128] Table 2 Classification performance evaluation metrics for different trajectories

[0129]

[0130] The following is a schematic diagram of the test track determination results, such as... Figures 13-23 As shown, it illustrates the spatial distribution of deviation points and normal points for each trajectory. Figures 13-23 In the diagram, normal points are represented in gray, and deviation points are highlighted in red, facilitating a visual observation of the classification effectiveness and deviation point locations. The diagram further validates the method's accurate identification of deviation behavior in most trajectories, particularly trajectories 7 to 9, where the distribution boundaries between deviation points and normal trajectories are clear, and the classification results highly match the actual deviation areas. Some trajectories (such as trajectories 2 and 3) exhibit certain false alarms, reflecting challenges in areas with drastic magnetic field changes or complex geographical locations. Overall, the results in the diagram are highly consistent with the classification indicators in the table, further validating the effectiveness of the method.

[0131] This invention provides a low-altitude flight path monitoring method that can acquire flight path sequence sequences of an aircraft flying along a target flight path under different sliding windows. By comparing these sequences with reference path sequence sequences in a pre-configured standard flight path geomagnetic fingerprint template library, it can identify changes in geomagnetic features within the geomagnetic fence in real time. This allows for timely detection of abnormal behaviors such as GNSS spoofing and path deviation, effectively addressing the problems of monitoring gaps and delays in GNSS spoofing and path deviation scenarios. Furthermore, compared to existing technologies, this invention can reduce the number of monitoring devices on the flight path, thereby reducing deployment costs and improving monitoring efficiency.

[0132] Furthermore, as Figure 1 and Figure 2 The specific implementation of the method shown in this embodiment provides a low-altitude flight path monitoring device, such as... Figure 24 As shown, the device includes: an acquisition unit 101, a generation unit 102, a search unit 103, a calculation unit 104, and a determination unit 105.

[0133] The acquisition unit 101 can be used to acquire the position information and geomagnetic field intensity of each sampling track point when the aircraft flies along the target route.

[0134] The generation unit 102 can be used to generate a sequence of flight track points for the aircraft under different sliding windows based on the location information of each sampled track point and the geomagnetic field strength.

[0135] The search unit 103 can be used to search for a reference track point sequence corresponding to the flight track point sequence from the standard route geomagnetic fingerprint template library based on the position information of each track point in the flight track point sequence. The standard route geomagnetic fingerprint template library records a standard reference trajectory corresponding to the target route. The standard reference trajectory includes the position information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength.

[0136] The calculation unit 104 can be used to calculate the similarity between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence.

[0137] The determination unit 105 can be used to determine in real time whether there is any abnormal behavior when the aircraft flies along the target route based on the similarity.

[0138] In some embodiments, the generation unit 102 includes: a generation module, an interpolation module, and a determination module.

[0139] The generation module can be used to generate flight sampling trajectories based on the location information of each sampling track point and the geomagnetic field strength.

[0140] The interpolation module can be used to interpolate the flight sampling trajectory to obtain the interpolated flight sampling trajectory.

[0141] The determining module can be used to determine the sequence of flight track points of the aircraft under different sliding windows based on the interpolated flight sampling trajectory.

[0142] In some embodiments, the interpolation module may be specifically used to interpolate the flight sampling trajectory based on the position information of each sampled track point to obtain the position information of each first interpolation point;

[0143] For any one of the first interpolation points, determine several sampling track points that are closest to the first interpolation point from among the sampling track points; calculate the geomagnetic field strength of the first interpolation point based on the geomagnetic field strength corresponding to the several sampling track points; determine the position information and geomagnetic field strength of each track point in the interpolated flight sampling trajectory based on the position information and geomagnetic field strength of each sampling track point, as well as the position information and geomagnetic field strength of each first interpolation point.

[0144] In some embodiments, the search unit 103 may be specifically used to determine the sequence of reference track points under different sliding windows based on the standard reference trajectory in the standard route geomagnetic fingerprint template library;

[0145] Based on the position information of each trackpoint in the flight trackpoint sequence and the position information of each reference trackpoint in the reference trackpoint sequence under different sliding windows, the reference trackpoint sequence closest to the flight trackpoint sequence is determined; the reference trackpoint sequence closest to the flight trackpoint sequence is determined as the reference trackpoint sequence corresponding to the flight trackpoint sequence.

[0146] In some embodiments, the calculation unit 104 may be specifically used to calculate the average Euclidean distance between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence; and determine the similarity between the flight track point sequence and the reference track point sequence based on the average Euclidean distance.

[0147] In some embodiments, the calculation unit 104 may also be specifically used to calculate the correlation coefficient between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence; and determine the similarity between the flight track point sequence and the reference track point sequence based on the correlation coefficient.

[0148] In some embodiments, the determination unit 105 may be specifically used to calculate a distance anomaly threshold based on the standard deviation of the geomagnetic field strength of each reference track point in the reference track point sequence corresponding to the flight track point sequence; if the average Euclidean distance is greater than the distance anomaly threshold, then it is determined that the aircraft has exhibited abnormal behavior of track deviation in the corresponding sliding window.

[0149] In some embodiments, the determination unit 105 may also be specifically used to determine that the aircraft exhibits abnormal behavior of trajectory deviation in the corresponding sliding window if the correlation coefficient is less than or equal to a preset correlation coefficient.

[0150] In some embodiments, the apparatus further includes a construction unit.

[0151] The construction unit can be used to collect the position information and geomagnetic field intensity of each initial track point on the target route; generate an initial standard reference trajectory based on the position information and geomagnetic field intensity of each initial track point; interpolate the initial standard reference trajectory based on the position information of each initial track point to obtain the position information of each second interpolation point; for any one of the second interpolation points, determine several initial track points closest to the arbitrary second interpolation point from among the initial track points; and calculate the position information of the arbitrary second interpolation point based on the geomagnetic field intensity corresponding to the several initial track points. The geomagnetic field strength at the two interpolation points; based on the geomagnetic field strength of each initial track point and the geomagnetic field strength of each second interpolation point, the standard deviation of the geomagnetic field strength of each initial track point and the standard deviation of the geomagnetic field strength of each second interpolation point are calculated respectively; based on the location information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each initial track point, and the location information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each second interpolation point, the standard reference trajectory corresponding to the target route is determined; based on the standard reference trajectory corresponding to the target route, a standard route geomagnetic fingerprint template library corresponding to the target route is constructed.

[0152] It should be noted that other corresponding descriptions of the functional units involved in the low-altitude flight path monitoring device provided in this embodiment can be found in [reference]. Figure 1 and Figure 2 The corresponding descriptions in [the document] will not be repeated here.

[0153] Based on the above, Figure 1 and Figure 2 Accordingly, this embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the above-described method. Figure 1 and Figure 2 The method for regulating low-altitude air routes is shown.

[0154] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause an electronic device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0155] Based on the above, Figure 1 and Figure 2 The method shown, and Figure 24To achieve the above objectives, the present application also provides an electronic device, specifically a personal computer, tablet computer, server, or other network device, as shown in the virtual device embodiment. This device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figure 1 and Figure 2 The method for regulating low-altitude air routes is shown.

[0156] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0157] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0158] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0159] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platform, or it can be implemented by hardware.

[0160] This invention can acquire flight track point sequences of an aircraft flying along a target route under different sliding windows. By comparing these sequences with reference track point sequences in a pre-configured standard route geomagnetic fingerprint template library, it can identify changes in geomagnetic features within the geomagnetic fence in real time. This allows for timely detection of abnormal behaviors such as GNSS spoofing and track deviation, effectively addressing the problems of monitoring gaps and delays in GNSS spoofing and track deviation scenarios. Furthermore, compared to existing technologies, this invention can reduce the number of monitoring devices on the flight route, thereby reducing deployment costs and improving monitoring efficiency.

[0161] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0162] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A method for monitoring low-altitude flight paths, characterized in that, include: Acquire the location information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route; Based on the location information and geomagnetic field strength of each sampled track point, a sequence of flight track points for the aircraft under different sliding windows is generated; Based on the position information of each track point in the flight track point sequence, the reference track point sequence corresponding to the flight track point sequence is searched from the standard route geomagnetic fingerprint template library. The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route. The standard reference trajectory includes the position information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength. Based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence, the similarity between the flight track point sequence and the reference track point sequence is calculated. Based on the similarity, it is determined in real time whether the aircraft exhibits any abnormal behavior while flying along the target route; The step of calculating the similarity between the flight waypoint sequence and the reference waypoint sequence based on the geomagnetic field strength of each waypoint in the flight waypoint sequence and the geomagnetic field strength of each reference waypoint in the reference waypoint sequence includes: Based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence, the average Euclidean distance between the flight track point sequence and the reference track point sequence is calculated. Based on the average Euclidean distance, determine the similarity between the flight waypoint sequence and the reference waypoint sequence; or Based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence, the correlation coefficient between the flight track point sequence and the reference track point sequence is calculated. Based on the correlation coefficient, the similarity between the flight waypoint sequence and the reference waypoint sequence is determined; The step of determining in real time whether the aircraft exhibits abnormal behavior while flying along the target route based on the similarity includes: The distance anomaly threshold is calculated based on the standard deviation of the geomagnetic field strength of each reference track point in the reference track point sequence corresponding to the flight track point sequence. If the average Euclidean distance is greater than the distance anomaly threshold, then it is determined that the aircraft exhibits abnormal behavior of deviating from its flight path within the corresponding sliding window; or If the correlation coefficient is less than or equal to the preset correlation coefficient, then it is determined that the aircraft exhibits abnormal behavior of deviating from its flight path in the corresponding sliding window.

2. The method according to claim 1, characterized in that, The step of generating a sequence of flight waypoints for the aircraft under different sliding windows based on the location information and geomagnetic field strength of each sampled waypoint includes: Based on the location information of each sampling track point and the geomagnetic field strength, a flight sampling trajectory is generated; The flight sampling trajectory is interpolated to obtain the interpolated flight sampling trajectory; Based on the interpolated flight sampling trajectory, the sequence of flight track points of the aircraft under different sliding windows is determined.

3. The method according to claim 2, characterized in that, The step of interpolating the flight sampling trajectory to obtain the interpolated flight sampling trajectory includes: Based on the position information of each sampled track point, the flight sampling trajectory is interpolated to obtain the position information of each first interpolation point; For any one of the first interpolation points, determine several sampling track points that are closest to any one of the first interpolation points from among the sampling track points; Calculate the geomagnetic field strength of any first interpolation point based on the geomagnetic field strength corresponding to the plurality of sampling track points; Based on the location information and geomagnetic field strength of each sampled track point, as well as the location information and geomagnetic field strength of each first interpolation point, the location information and geomagnetic field strength of each track point in the interpolated flight sampling trajectory are determined.

4. The method according to claim 1, characterized in that, The step of searching for the reference trackpoint sequence corresponding to the flight trackpoint sequence from the standard route geomagnetic fingerprint template library based on the position information of each trackpoint in the flight trackpoint sequence includes: Based on the standard reference trajectory in the standard route geomagnetic fingerprint template library, determine the reference track point sequence under different sliding windows; Based on the position information of each waypoint in the flight waypoint sequence and the position information of each reference waypoint in the reference waypoint sequence under different sliding windows, determine the reference waypoint sequence that is closest to the flight waypoint sequence; The reference waypoint sequence that is closest to the flight waypoint sequence is determined as the reference waypoint sequence corresponding to the flight waypoint sequence.

5. The method according to any one of claims 1-4, characterized in that, Before searching for the reference trackpoint sequence corresponding to the flight trackpoint sequence from the standard route geomagnetic fingerprint template library based on the position information of each trackpoint in the flight trackpoint sequence, the method further includes: Collect the location information and geomagnetic field intensity of each initial track point on the target route; Based on the location information of each initial track point and the intensity of the geomagnetic field, an initial standard reference trajectory is generated; Based on the position information of each initial track point, the initial standard reference trajectory is interpolated to obtain the position information of each second interpolation point; For any one of the second interpolation points, determine several initial track points that are closest to any one of the second interpolation points from among the initial track points; Calculate the geomagnetic field intensity of any second interpolation point based on the geomagnetic field intensity corresponding to the initial track points; Based on the geomagnetic field strength of each initial track point and the geomagnetic field strength of each second interpolation point, calculate the standard deviation of the geomagnetic field strength of each initial track point and the standard deviation of the geomagnetic field strength of each second interpolation point respectively. Based on the location information, geomagnetic field strength, and standard deviation of each initial track point, as well as the location information, geomagnetic field strength, and standard deviation of each second interpolation point, the standard reference trajectory corresponding to the target route is determined. Based on the standard reference trajectory corresponding to the target route, a standard route geomagnetic fingerprint template library corresponding to the target route is constructed.

6. A low-altitude flight path monitoring device, characterized in that, include: The acquisition unit is used to acquire the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route. The generation unit is used to generate a sequence of flight track points of the aircraft under different sliding windows based on the position information of each sampled track point and the geomagnetic field strength. The search unit is used to search for the reference track point sequence corresponding to the flight track point sequence from the standard route geomagnetic fingerprint template library based on the position information of each track point in the flight track point sequence. The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route. The standard reference trajectory includes the position information of each reference track point, the geomagnetic field strength, and the standard deviation of the geomagnetic field strength. The calculation unit is used to calculate the similarity between the flight track point sequence and the reference track point sequence based on the geomagnetic field strength of each track point in the flight track point sequence and the geomagnetic field strength of each reference track point in the reference track point sequence; The determination unit is used to determine in real time whether there is any abnormal behavior when the aircraft flies along the target route based on the similarity. The calculation unit is specifically configured to: calculate the average Euclidean distance between the flight waypoint sequence and the reference waypoint sequence based on the geomagnetic field strength of each waypoint in the flight waypoint sequence and the geomagnetic field strength of each reference waypoint in the reference waypoint sequence; determine the similarity between the flight waypoint sequence and the reference waypoint sequence based on the average Euclidean distance; or calculate the correlation coefficient between the flight waypoint sequence and the reference waypoint sequence based on the geomagnetic field strength of each waypoint in the flight waypoint sequence and the geomagnetic field strength of each reference waypoint in the reference waypoint sequence; and determine the similarity between the flight waypoint sequence and the reference waypoint sequence based on the correlation coefficient. The determination unit is specifically used to calculate a distance anomaly threshold based on the standard deviation of the geomagnetic field strength of each reference track point in the reference track point sequence corresponding to the flight track point sequence; if the average Euclidean distance is greater than the distance anomaly threshold, then it is determined that the aircraft has exhibited abnormal behavior of track deviation in the corresponding sliding window; or if the correlation coefficient is less than or equal to a preset correlation coefficient, then it is determined that the aircraft has exhibited abnormal behavior of track deviation in the corresponding sliding window.

7. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

8. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

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