Low-altitude airline supervision method and device, storage medium and electronic equipment

Abstract

The invention discloses a low-altitude airline supervision method and device, a storage medium and electronic equipment, and relates to the technical field of information. The method comprises the following steps: acquiring position information and geomagnetic field intensity of each sampling track point when the aircraft flies along a target route; according to the position information of each sampling track point and the geomagnetic field intensity, generating a flight track point sequence of the aircraft under different sliding windows; searching a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library according to 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 intensity of each track point in the flight track point sequence and the geomagnetic field intensity of each reference track point in the reference track point sequence; and according to the similarity, determining whether an abnormal behavior exists when the aircraft flies along the target route in real time. According to the invention, the method can effectively cope with the abnormal behaviors such as GNSS decoy and track deviation.

Description

Technical Field

[0001] The present application relates to the field of information technology, and in particular to a method, device, storage medium and electronic equipment for monitoring low-altitude flight routes. Background Art

[0002] As an emerging industry, the low-altitude economy is experiencing a golden period of rapid development. With the continuous advancement of science and technology, the technology of low-altitude aircraft such as drones and electric vertical take-off and landing aircraft is becoming increasingly mature, providing solid technical support for the development of the low-altitude economy.

[0003] High-precision navigation and positioning are the primary support for route planning and regulation in the low-altitude sector. Most existing low-altitude aircraft rely on GNSS (Global Navigation Satellite System) positioning methods, such as GPS (Global Positioning System) and Beidou, for navigation support. However, it is important to note that because GNSS positioning faces the risk of location denial in some environments (typically urban canyons), navigation and positioning methods solely based on GNSS cannot meet the rapidly developing needs of the low-altitude sector. Furthermore, the sole use of GNSS positioning for route regulation carries risks such as GNSS spoofing. Because aircraft lack effective means to distinguish valid from spoofed GNSS messages, GNSS spoofing can easily lead to flight deviation, uncontrollable flight, and difficulty tracing the standard reference trajectory, among other dangers.

[0004] Currently, to address the shortcomings of GNSS positioning, existing route monitoring methods typically require the deployment of radar and telemetry equipment along pre-configured routes. However, this passive monitoring approach, limited by the processing power of the equipment, can lead to monitoring gaps and lags when there are a large number of aircraft on a route, which can easily lead to flight accidents. Furthermore, the installation of a large number of devices also incurs high deployment costs. Summary of the Invention

[0005] In view of this, the present application provides a low-altitude route supervision method, device, storage medium and electronic equipment, which are mainly capable of solving problems such as lack of supervision and lag in GNSS spoofing and track deviation scenarios, effectively responding to abnormal behaviors such as GNSS spoofing and track deviation, and reducing deployment costs.

[0006] According to a first aspect of the present application, a low-altitude route supervision method is provided, the method comprising: Obtain the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route; Generating a flight track point sequence of the aircraft under different sliding windows according to the position information of each sampled track point and the geomagnetic field strength; According to the position information of each track point in the flight track point sequence, searching for a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library, wherein the standard route geomagnetic fingerprint template library records a standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength, and standard deviation of geomagnetic field strength of each reference track point; 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; Based on the similarity, it is determined in real time whether the aircraft has abnormal behavior when flying along the target route.

[0007] According to a second aspect of the present application, a low-altitude route monitoring device is provided, comprising: An acquisition unit, used to obtain the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route; a generating unit, configured to generate a flight track point sequence of the aircraft in different sliding windows according to the position information of each sampled track point and the geomagnetic field strength; a search unit, configured to search, based on the position information of each track point in the flight track point sequence, for a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library, wherein the standard route geomagnetic fingerprint template library records a standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength, and standard deviation of geomagnetic field strength of each reference track point; a calculation unit, configured to calculate a 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 configured to determine in real time, based on the similarity, whether the aircraft has any abnormal behavior when flying along the target route.

[0008] According to a third aspect of the present application, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned low-altitude route supervision method is implemented.

[0009] According to the fourth aspect of the present application, an electronic device is provided, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the above-mentioned low-altitude route supervision method when executing the program.

[0010] By means of the above technical solution, the present application provides a low-altitude route supervision method, device, storage medium and electronic device. Compared with the existing route supervision method, it can obtain the flight track point sequence under different sliding windows when the aircraft flies along the target route, and by comparing it with the reference track point sequence in the pre-configured standard route geomagnetic fingerprint template library, it can identify the changes in the magnetic characteristics within the geomagnetic fence in real time, so as to timely detect abnormal behaviors such as GNSS spoofing and track deviation, and effectively solve the problems of lack of supervision and lag in GNSS spoofing and track deviation scenarios. In addition, compared with the existing technology, the present application can also reduce the number of supervision equipment on the route, thereby reducing deployment costs and improving supervision efficiency.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A schematic diagram of a low-altitude flight path supervision method provided in an embodiment of the present application is shown; Figure 2 A schematic diagram of a process for constructing a standard route geomagnetic fingerprint template library provided in an embodiment of the present application is shown; Figure 3 A schematic diagram of a satellite map of route 1 provided in an embodiment of the present application is shown; Figure 4 A schematic diagram of a satellite map of route 2 provided in an embodiment of the present application is shown; Figure 5 A schematic diagram of a satellite map of route 3 provided in an embodiment of the present application is shown; Figure 6 Schematic diagrams of three initial standard reference trajectories provided in an embodiment of the present application are shown; Figure 7 A schematic diagram of a geomagnetic field intensity variation curve of an initial standard reference trajectory provided by an embodiment of the present application is shown; Figure 8 A schematic diagram of a standard reference trajectory provided by an embodiment of the present application is shown; Figure 9 A schematic diagram of a curve showing a change in the geomagnetic field intensity of a standard reference trajectory provided in an embodiment of the present application is shown; Figure 10A schematic diagram of a geomagnetic field intensity variation curve of a decoy trajectory provided by an embodiment of the present application is shown; Figure 11 A schematic diagram of the actual flight path of the decoy trajectory provided by an embodiment of the present application is shown; Figure 12 A schematic diagram of the trajectory of a drone provided by an embodiment of the present application after being deceived based on erroneous positioning is shown; Figure 13 Schematic diagram showing the determination result for track 0 provided in an embodiment of the present application; Figure 14 A schematic diagram of the determination result for track 1 provided in an embodiment of the present application is shown; Figure 15 A schematic diagram of the determination result for track 2 provided in an embodiment of the present application is shown; Figure 16 A schematic diagram of the determination result for track 3 provided in an embodiment of the present application is shown; Figure 17 A schematic diagram of the determination result for track 4 provided in an embodiment of the present application is shown; Figure 18 A schematic diagram of the determination result for track 5 provided in an embodiment of the present application is shown; Figure 19 A schematic diagram of the determination result for track 6 provided in an embodiment of the present application is shown; Figure 20 A schematic diagram of the determination result for track 7 provided in an embodiment of the present application is shown; Figure 21 A schematic diagram of the determination result for track 8 provided in an embodiment of the present application is shown; Figure 22 A schematic diagram of the determination result for track 9 provided in an embodiment of the present application is shown; Figure 23 A schematic diagram of the determination result for track 10 provided in an embodiment of the present application is shown; Figure 24 A schematic structural diagram of a low-altitude route monitoring device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0013] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0014] The existing regulatory methods have problems such as lack of supervision and lags, which can easily lead to flight accidents and have high deployment costs.

[0015] In order to solve the above problems, an embodiment of the present invention designs a system architecture for low-altitude route supervision, which mainly includes three parts: construction of a standard route geomagnetic fingerprint template library, pre-installation of a quasi-route geomagnetic fingerprint template library, and identification of changes in magnetic characteristics within the geomagnetic fence.

[0016] Among them, for the construction of the standard route geomagnetic fingerprint template library, after the route planning is completed, a low-altitude aircraft equipped with a geomagnetic sensing unit is first allowed to fly within the route. During the flight, the geomagnetic field strength data is collected in real time to complete the construction of the standard route geomagnetic fingerprint template library. The standard route geomagnetic fingerprint template library records the standard reference trajectory for the route. The standard reference trajectory includes the position coordinates and geomagnetic field strength of all position points, which can be specifically expressed as ,in, Indicates the first i The position coordinates of the location points, Indicates the first i The geomagnetic field strength at a location.

[0017] For the pre-installation of the standard route geomagnetic fingerprint template library, after the standard route geomagnetic fingerprint template library is built, during the take-off phase of the low-altitude aircraft, the standard route geomagnetic fingerprint template library is pre-configured through remote or manual connection to provide support for subsequent geomagnetic-based route supervision.

[0018] To identify changes in magnetic characteristics within the geomagnetic fence, the aircraft monitors changes in the geomagnetic field in real time while flying along the designated route. If abnormal behaviors such as GNSS spoofing and track deviation are detected, the alarm function will be activated to ensure that the aircraft flies in accordance with regulations on the designated route.

[0019] The embodiment of the present invention provides a low-altitude route supervision method, which is mainly used to identify abnormal behaviors such as GNSS deception and track deviation of an aircraft during the flight phase of a designated route. Figure 1 As shown, the method includes: Step 10: Obtain the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route.

[0020] Among them, aircraft mainly include drones, small light helicopters, electric vertical take-off and landing aircraft, airships, rotorcraft, etc. The target route is any route planned for the aircraft. The sampling track points are the location points where the geomagnetic sensing unit collects information when the aircraft flies along the target route. The location information of the sampling track points includes longitude, latitude and height relative to the ground.

[0021] For the embodiment of the present invention, before the aircraft takes off, it is necessary to set a designated route (target route) for the aircraft and load the pre-built standard route geomagnetic fingerprint template library. Since the aircraft may be deceived by GNSS during flight, it is impossible to determine whether there is abnormal behavior of track deviation through longitude and latitude. For this purpose, the route supervision method based on geomagnetism in the embodiment of the present invention can be adopted.

[0022] Specifically, during the flight of the aircraft, the geomagnetic sensing unit is used to collect the geomagnetic field intensity of each sampling track point in real time. , and collect the location information of each sampling track point at the same time , so as to be based on the position information of each sampling track point and the strength of the Earth's magnetic field , to determine the changes in magnetic characteristics within the geomagnetic fence, and thus identify abnormal behaviors such as aircraft track deviation.

[0023] Step 20: Generate a flight track point sequence of the aircraft in different sliding windows based on the position information of each sampled track point and the geomagnetic field strength.

[0024] The flight track point sequence includes the location information and geomagnetic field strength of multiple track points, and the size of the sliding window can be set according to actual business needs.

[0025] For an embodiment of the present 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. For this process, step 20 specifically 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.

[0026] 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 first interpolation point among the first interpolation points, several sampling track points closest to the any first interpolation point are determined from the sampling track points; the geomagnetic field intensity of the any first interpolation point is calculated based on the geomagnetic field intensity corresponding to the several sampling track points; and the position information and geomagnetic field intensity of each track point in the interpolated flight sampling trajectory are determined based on the position information and geomagnetic field intensity of each sampling track point, as well as the position information and geomagnetic field intensity of each first interpolation point.

[0027] The sampling track point and the first interpolation point together constitute a track point in the flight track point sequence, and the position information of the first interpolation point includes longitude, latitude, and height relative to the ground.

[0028] Specifically, according to the location information of each sampling track point and the strength of the Earth's magnetic field , generate flight sampling trajectory ,in, L Represents the trajectory sampling length. Then set the interpolation interval 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 sampling track point. The first interpolation point and the sampling track point are collectively referred to as track points. When calculating the position information of the first interpolation point, the position information of each sampling track point and the interpolation interval can be used. d Calculation is performed. When calculating the geomagnetic field strength of the first interpolation point, for any first interpolation point, several sampling track points closest to the first interpolation point are determined from the sampling track points, and then the geomagnetic field strength of the first interpolation point is calculated based on the geomagnetic field strength of the several sampling track points, such as taking the average of the geomagnetic field strengths of the several sampling track points, or performing weighted summation of the geomagnetic field strengths of the several sampling track points. The weight coefficients of the several sampling track points can be determined by inverse distance weight or Gaussian kernel function. After calculating the position information and geomagnetic field strength of each first interpolation point, the interpolated flight sampling trajectory is determined based on the position information and geomagnetic field strength of each first interpolation point, as well as the position information and geomagnetic field strength of each sampling track point.

[0029] Furthermore, based on the interpolated flight sampling trajectory, the flight track point sequences under different sliding windows are defined, specifically: .

[0030] By comparing the flight track point sequence with the standard route geomagnetic fingerprint template library, it is possible to determine whether the aircraft has abnormal behaviors such as GNSS spoofing and track deviation when flying along the target route.

[0031] Step 30: According to the position information of each track point in the flight track point sequence, a reference track point sequence corresponding to the flight track point sequence is searched from a standard route geomagnetic fingerprint template library.

[0032] The standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength and geomagnetic field strength standard deviation of each reference track point.

[0033] For the embodiment of the present invention, in order 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 the 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.

[0034] Specifically, based on the standard reference trajectory in the standard route geomagnetic fingerprint template library, the reference track point sequences under different sliding windows are defined as follows: .

[0035] For any flight track point sequence under a sliding window , respectively calculate the reference track point sequence under different sliding windows The average Euclidean distance between , the specific formula is as follows: .

[0036] Then, based on the calculated average Euclidean distance, find Reference track point sequence under the minimum corresponding time window Therefore, according to the above method, the reference track point sequence corresponding to the flight track point sequence in different time windows can be determined from the standard route geomagnetic fingerprint template library.

[0037] 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.

[0038] In this embodiment of the present invention, after determining the reference track point sequence corresponding to the flight track point sequence, the similarity between the geomagnetic field strengths of the two sequences is calculated. Regarding this process, step 40 specifically includes: calculating 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 determining the similarity between the flight track point sequence and the reference track point sequence based on the average Euclidean distance.

[0039] Specifically, according to the geomagnetic field strength of each track point in the flight track point sequence, a first geomagnetic field strength sequence is determined. At the same time, according to the geomagnetic field strength of each reference track point in the reference track point sequence, the second geomagnetic field strength sequence is determined , then calculate the first geomagnetic field strength sequence The second geomagnetic field strength series The average Euclidean distance between , the specific formula is as follows: .

[0040] After the average Euclidean distance is calculated, the average Euclidean distance can be used to represent the similarity between the flight track point sequence and the reference track point sequence.

[0041] In addition to using the average Euclidean distance to represent the similarity between two sequences, the embodiment of the present 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 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 the similarity between the flight track point sequence and the reference track point sequence based on the correlation coefficient. Wherein, the correlation coefficient The specific calculation formula is as follows: , in, Reference track point sequence The mean geomagnetic intensity, ; Flight track point sequence The mean geomagnetic intensity, .

[0042] After the correlation coefficient is calculated, the correlation coefficient can be used to represent the similarity between the flight track point sequence and the reference track point sequence.

[0043] Step 50: Based on the similarity, determine in real time whether the aircraft has any abnormal behavior when flying along the target route.

[0044] Corresponding to the above two implementations, when the average Euclidean distance is used as the similarity indicator, the distance anomaly threshold is calculated based on the standard deviation of the geomagnetic field intensity 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 has exhibited abnormal track deviation behavior in the corresponding sliding window. The specific calculation formula for the distance anomaly threshold is as follows: , in, , Reference track point sequence The standard deviation of the geomagnetic field intensity at each reference track point in .

[0045] When a correlation coefficient is used as the similarity indicator, if the correlation coefficient is less than or equal to a preset correlation coefficient, it is determined that the aircraft has exhibited abnormal track deviation behavior in the corresponding sliding window. The preset correlation coefficient can be set according to actual business needs.

[0046] Furthermore, the embodiment of the present invention also provides a method for constructing a standard route geomagnetic fingerprint template library, such as Figure 2 As shown, the method includes: Step 60: Collect the position information and geomagnetic field strength of each initial track point on the target route, and generate an initial standard reference trajectory based on the position information and geomagnetic field strength of each initial track point.

[0047] In the embodiment of the present invention, when constructing the standard route geomagnetic fingerprint template library, an aircraft equipped with a geomagnetic sensing unit is allowed to fly along the target route to obtain at least one initial standard reference trajectory. The initial standard reference trajectory consists of multiple initial track points and flight segments. A flight segment is between any two initial track points. During the flight of the aircraft, the position information and geomagnetic field strength of each initial track point are collected. The initial track point sequence is defined as ,in, Indicates the k The location information of the initial track point includes the longitude, latitude and height relative to the ground.

[0048] In addition, define the initial standard reference trajectory set , the mth initial standard reference trajectory is: , in, For the m The sampling length of the initial standard reference trajectory, For the m The first of the initial standard reference trajectories t The position information of the initial track points, For the m The first of the initial standard reference trajectories t The geomagnetic field strength at the initial track point. Initial standard reference trajectories are used to build a standard route geomagnetic fingerprint template library.

[0049] 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.

[0050] For the embodiment of the present invention, at the initial track point and The longitude and latitude interpolation is performed between d , in meters, thus generating a sequence of intermediate track points, recorded as: .

[0051] Then, all interpolated trajectories of the flight segments are combined to obtain the standard reference trajectory corresponding to the target route, which is recorded as: , in, Indicates the latitude and longitude coordinates of the nth track point after interpolation, N The coordinates of the second interpolation point can be calculated based on the position information of each initial track point and the interpolation interval. d calculate.

[0052] Step 80: For any one of the second interpolation points, determine several initial track points closest to the any one second interpolation point from the initial track points, and calculate the geomagnetic field strength of the any one second interpolation point based on the geomagnetic field strengths corresponding to the several initial track points.

[0053] In the embodiment of the present invention, when calculating any second interpolation point When the magnetic field strength is Initial track points, and The geomagnetic field strength at the initial track point Perform weighted averaging, the geomagnetic field strength at the nth second interpolation point The specific calculation formula is as follows: , in, Represents The nearest A set of initial track points, Represents the weighting coefficient, which satisfies The weighting coefficient can be selected by using inverse distance weight or Gaussian kernel function. The inverse distance weight is based on the inverse power relationship of the distance to determine the weight. The closer the distance, the higher the weight. The Gaussian kernel function dynamically allocates weights through the exponential attenuation of the distance. The weight decreases exponentially with the increase of distance.

[0054] Step 90: Calculate the standard deviation of the geomagnetic field intensity at each initial track point and the standard deviation of the geomagnetic field intensity at each second interpolation point based on the geomagnetic field intensity at each initial track point and the geomagnetic field intensity at each second interpolation point.

[0055] In the embodiment of the present invention, the initial track point and the second interpolation point on the standard reference trajectory are collectively referred to as reference track points. , and the corresponding calculation formula for the standard deviation of the geomagnetic field intensity is: .

[0056] It should be noted that a geomagnetic field strength standard may be preset, and the geomagnetic field strength of the reference track point may be compared with the geomagnetic field strength standard to calculate the standard deviation of the geomagnetic field strength corresponding to each reference track point.

[0057] Step 100: Determine the standard reference trajectory corresponding to the target route based on the position information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each initial track point, as well as the position information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each second interpolation point, and construct a standard route geomagnetic fingerprint template library corresponding to the target route based on the standard reference trajectory corresponding to the target route.

[0058] Among them, the standard route geomagnetic fingerprint template libraries corresponding to different routes are different.

[0059] For the embodiment of the present invention, the standard reference trajectory recorded in the standard route geomagnetic fingerprint template library can be specifically expressed as: , in, Indicates the location information of the nth reference track point, Indicates the geomagnetic field strength at the nth reference track point, Indicates the standard deviation of the geomagnetic field strength at the nth reference track point.

[0060] In order to verify the reliability of the low-altitude route monitoring method described above in the embodiment of the present invention, the embodiment of the present invention conducted flight tests at a test site with airspace use permission. During the flight, the system synchronously recorded the UAV's latitude and longitude information, altitude information, three-axis geomagnetic field strength data, and key parameters such as the inertial measurement unit. The embodiment of the present invention designed three routes, namely Route 1, Route 2, and Route 3. The satellite maps of the three routes are as follows: Figure 3 、 Figure 4 and Figure 5 shown.

[0061] The following describes the specific process of building a standard route geomagnetic fingerprint template library based on the actual route geomagnetic field intensity data. Taking route 3 as an example, route 3 consists of three initial track points and two flight segments. For route 3, three initial standard reference trajectories were collected. The sampling position coordinates of these trajectories and the corresponding geomagnetic field intensity are as follows: Figure 6 and Figure 7 As shown, Figure 6Three initial standard reference trajectories are shown. Figure 7 The curve of the change of the Earth's magnetic field strength is shown.

[0062] For the geomagnetic field intensity at the same position on the three initial standard reference trajectories, the average value of the three acquisition results 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, the inverse distance weight is used to calculate the geomagnetic field strength and the standard deviation of the geomagnetic field strength at the nth second interpolation point, thereby constructing the standard route geomagnetic fingerprint template library , the visual interface of the fingerprint template library is as follows Figure 8 As shown, Figure 8 The three initial standard reference tracks Projected_0, Projected_1 and Projected_2 are shown, as well as the standard reference track Fused_Mg in the standard route geomagnetic fingerprint template library. Figure 9 is the curve of the change of the Earth's magnetic field intensity, Figure 9 The upper and lower three times standard deviation range is further drawn to reflect the variation range and stability of the geomagnetic characteristics of the route.

[0063] The following is a verification of the track deviation determination method based on the difference in real geomagnetic field characteristics in the embodiment of the present invention. First, a GNSS decoy trajectory is created so that the drone cannot determine whether it has deviated from the track based on its longitude and latitude. The specific implementation process is as follows: (1) The UAV performs a flight mission along route 3, actively deviates from the established track during the flight, and continuously collects geomagnetic field intensity data; (2) The latitude and longitude information of the deviated track is projected onto route 3 to form a track that pretends to be on the same route, simulating the scenario where the drone cannot detect its own deviation through longitude and latitude under GNSS spoofing.

[0064] Thus, the geomagnetic field strength data of a total of 11 decoy trajectories were obtained, 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 tracks are shown. Figure 12 The trajectory of the UAV after being deceived is shown based on the incorrect positioning solution.

[0065] According to the track deviation judgment method provided by the embodiment 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 c=3. When the magnitude of the geomagnetic field intensity within the sliding window deviates from the standard reference trajectory by more than three standard deviations, it is considered a deviation point. Under the above settings, deviation detection is performed on each of the eleven trajectories. To specifically quantify the degree of deviation, the embodiment of the present invention defines the deviation rate as the ratio of the number of points in the trajectory that are identified as deviation points to the total number of track points. The specific calculation formula is as follows: , in, Indicates the number of points that are judged to be off-track. represents the total number of track points in the trajectory. Furthermore, the confidence level of track deviation is defined as confidence level = 1 - deviation rate. The test results show the deviation rate and confidence level of each trajectory as shown in Table 1.

[0066] Table 1 Track deviation detection results based on geomagnetic characteristics in GNSS spoofing scenario

[0067] The experimental results above demonstrate that the track deviation discrimination method based on geomagnetic feature differences proposed in this embodiment of the present invention can effectively distinguish normal trajectories from abnormal trajectories caused by GNSS spoofing. The detection results in Table 1 show that the normal trajectory has the lowest deviation rate, only 8.66%, corresponding to a confidence level of 91.34%. The deviation rates of the remaining spoofed trajectories are generally above 20%, with significantly lower confidence levels. This fully demonstrates the robustness and practicality of this method in complex environments.

[0068] Table 2 lists the classification performance metrics of the track deviation discrimination method based on geomagnetic feature differences on 11 test trajectories, including accuracy, precision, recall, and F1-score. Overall, most trajectories exhibit high accuracy, particularly trajectories 7, 8, and 9, each exceeding 95%. This demonstrates that the method effectively distinguishes deviating points from normal points. With the exception of trajectory 10, the recall rates of all trajectories reached or approached 100%, indicating that the embodiment of the present invention rarely missed deviating points and possessed strong detection capabilities. There was some fluctuation in the accuracy, with some trajectories (such as trajectories 1, 2, and 3) exhibiting lower accuracy, possibly indicating a certain amount of false positives. Trajectory 10 is a normal trajectory, with both the recall and precision of deviating points being 0, and the F1-score being 0. This is consistent with the actual situation, indicating that the trajectory was not misclassified as a deviation, thus verifying the effectiveness and stability of the method. Based on the above results, the embodiments of the present invention demonstrate good robustness and practicality in distinguishing track deviations in a complex GNSS spoofing environment.

[0069] Table 2 Classification performance evaluation indicators of different trajectories

[0070] The following is a schematic diagram of the test track determination results. Figure 13-Figure 23 As shown in , it shows the distribution of deviation points and normal points of each trajectory in space. Figure 13-Figure 23 In the figure, normal points are gray, and deviating points are highlighted in red, allowing for intuitive visualization of the method's classification performance and the locations of deviating points. The diagram further verifies the method's ability to accurately identify deviating behavior in most trajectories. In particular, in trajectories 7 through 9, the distribution boundaries between deviating points and normal trajectories are clear, and the classification results closely match the actual deviating areas. However, some false positives occur in some trajectories (such as trajectories 2 and 3), reflecting the challenges that remain in areas with drastic magnetic field fluctuations or complex geographical locations. Overall, the results are highly consistent with the classification indicators in the table, further validating the effectiveness of the method.

[0071] The low-altitude route monitoring method provided by an embodiment of the present invention can obtain a sequence of flight track points under different sliding windows when an aircraft flies along a target route. By comparing it with a reference track point sequence in a pre-configured standard route geomagnetic fingerprint template library, it can identify changes in magnetic characteristics within the geomagnetic fence in real time, thereby promptly detecting abnormal behaviors such as GNSS spoofing and track deviation, and effectively solving problems such as lack of supervision and lag in GNSS spoofing and track deviation scenarios. In addition, compared with existing technologies, the embodiment of the present invention can also reduce the number of monitoring devices on the route, thereby reducing deployment costs and improving monitoring efficiency.

[0072] Further, as Figure 1 and Figure 2 The specific implementation of the method shown in this embodiment provides a low-altitude route 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.

[0073] The acquisition unit 101 may be used to acquire the position information and geomagnetic field strength of each sampling track point when the aircraft flies along a target route.

[0074] The generating unit 102 may be configured to generate a sequence of flight track points of the aircraft in different sliding windows according to the position information of each sampled track point and the geomagnetic field strength.

[0075] The search unit 103 can be used to search for a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library based on the position information of each track point in the flight track point sequence, wherein the standard route geomagnetic fingerprint template library records the standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength and standard deviation of geomagnetic field strength of each reference track point.

[0076] The calculation unit 104 may be configured to calculate a 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 105 may be configured to determine in real time, based on the similarity, whether the aircraft has any abnormal behavior while flying along the target route.

[0077] In some embodiments, the generating unit 102 includes: a generating module, an interpolation module and a determining module.

[0078] The generation module can be used to generate a flight sampling trajectory based on the position information of each sampling track point and the geomagnetic field strength.

[0079] The interpolation module can be used to interpolate the flight sampling trajectory to obtain an interpolated flight sampling trajectory.

[0080] The determination module may be configured to determine a sequence of flight track points of the aircraft in different sliding windows based on the interpolated flight sampling trajectory.

[0081] In some embodiments, the interpolation module may be specifically configured to interpolate the flight sampling trajectory 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 any one first interpolation point are determined from the sampling track points; the geomagnetic field intensity of the any one first interpolation point is calculated based on the geomagnetic field intensities corresponding to the several sampling track points; and the position information and geomagnetic field intensity of each track point in the interpolated flight sampling trajectory are determined based on the position information and geomagnetic field intensity of each sampling track point and the position information and geomagnetic field intensity of each first interpolation point.

[0082] In some embodiments, the search unit 103 may be specifically configured to determine a reference track point sequence under different sliding windows based on the standard reference track in the standard route geomagnetic fingerprint template library; Determine 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 the different sliding windows; and determine 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.

[0083] In some embodiments, the calculation unit 104 can 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.

[0084] In some embodiments, the calculation unit 104 can 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.

[0085] In some embodiments, the determination unit 105 can be specifically used to calculate a distance anomaly threshold based on the standard deviation of the geomagnetic field intensity 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 has abnormal track deviation behavior in the corresponding sliding window.

[0086] In some embodiments, the determination unit 105 may be further configured to determine that the aircraft exhibits abnormal track deviation in the corresponding sliding window if the correlation coefficient is less than or equal to a preset correlation coefficient.

[0087] In some embodiments, the device further comprises: a construction unit.

[0088] The construction unit can be used to collect the position information and geomagnetic field strength of each initial track point on the target route; generate an initial standard reference trajectory based on the position information and geomagnetic field strength 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 second interpolation point among the second interpolation points, determine from the initial track points several initial track points that are closest to the any second interpolation point; calculate the position of any first interpolation point according to the geomagnetic field strength corresponding to the several initial track points. The method comprises the following steps: calculating the geomagnetic field strength of the first and second interpolation points; calculating the standard deviation of the geomagnetic field strength of the first and second interpolation points respectively according to the geomagnetic field strength of the first and second interpolation points; determining the standard reference trajectory corresponding to the target route according to the position information, geomagnetic field strength and standard deviation of the geomagnetic field strength of the first and second interpolation points, and constructing a standard route geomagnetic fingerprint template library corresponding to the target route based on the standard reference trajectory corresponding to the target route.

[0089] It should be noted that for other corresponding descriptions of the functional units involved in the low-altitude route monitoring device provided in this embodiment, please refer to Figure 1 and Figure 2 The corresponding description in will not be repeated here.

[0090] Based on the above Figure 1 and Figure 2 The method shown in FIG. 1 is a method for performing the above-mentioned operation. Accordingly, this embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned Figure 1 and Figure 2 The low-altitude route supervision method shown.

[0091] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), and includes a number of instructions for enabling an electronic device (which can be a personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of the present application.

[0092] Based on the above Figure 1 and Figure 2 The method shown, and Figure 24In order to achieve the above-mentioned purpose, the embodiment of the present application further provides an electronic device, which can be a personal computer, a tablet computer, a server, or other network equipment, etc. The device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 and Figure 2 The low-altitude route supervision method shown.

[0093] Optionally, the physical device may also include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a Wi-Fi module, and the like. The user interface may include a display screen and an input unit such as a keyboard. Optional user interfaces may also include a USB interface and a card reader interface. Optionally, the network interface may include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0094] Those skilled in the art will understand that the above-mentioned physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0095] 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 physical device, supporting the execution of information processing programs and other software and / or programs. The network communication module is used to enable communication between components within the storage medium, as well as with other hardware and software within the physical information processing device.

[0096] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or by hardware.

[0097] The embodiments of the present invention can obtain flight track point sequences within different sliding windows as an aircraft flies along a target route. By comparing these sequences with reference track point sequences in a pre-configured standard route geomagnetic fingerprint template library, they can identify changes in magnetic characteristics within the geomagnetic fence in real time, thereby promptly detecting abnormal behaviors such as GNSS spoofing and track deviation, effectively addressing issues such as lack of supervision and lag in GNSS spoofing and track deviation scenarios. Furthermore, compared to existing technologies, the embodiments of the present invention can reduce the number of supervisory devices on the route, thereby reducing deployment costs and improving supervisory efficiency.

[0098] Those skilled in the art will understand that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required to implement the present application. Those skilled in the art will understand that the modules in the devices in the implementation scenario can be distributed in the devices of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more devices different from the implementation scenario. The modules of the above-mentioned implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0099] The serial numbers of the above application are for descriptive purposes only and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosure only discloses several specific implementation scenarios of the present application, but the present application is not limited thereto. Any changes that can be conceived by those skilled in the art should fall within the scope of protection of the present application.

Claims

1. A low-altitude flight route supervision method, characterized in that: include: Obtain the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route; Generating a flight track point sequence of the aircraft under different sliding windows according to the position information of each sampled track point and the geomagnetic field strength; According to the position information of each track point in the flight track point sequence, searching for a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library, wherein the standard route geomagnetic fingerprint template library records a standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength, and standard deviation of geomagnetic field strength of each reference track point; 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; Based on the similarity, it is determined in real time whether the aircraft has abnormal behavior when flying along the target route.

2. The method according to claim 1, characterized in that Generating a flight track point sequence of the aircraft in different sliding windows according to the position information of each sampled track point and the geomagnetic field strength includes: Generate a flight sampling trajectory based on the position information of each sampling track point and the geomagnetic field strength; interpolating the flight sampling trajectory to obtain an interpolated flight sampling trajectory; Based on the interpolated flight sampling trajectory, a flight track point sequence of the aircraft in different sliding windows is determined.

3. The method according to claim 2, characterized in that The interpolating the flight sampling trajectory to obtain an interpolated flight sampling trajectory includes: Based on the position information of each sampling track point, interpolating the flight sampling trajectory to obtain the position information of each first interpolation point; For any one of the first interpolation points, determining, from the sampled track points, a number of sampled track points that are closest to the any one of the first interpolation points; Calculating the geomagnetic field strength of any one of the first interpolation points based on the geomagnetic field strengths corresponding to the plurality of sampling track points; 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 and the position information and geomagnetic field strength of each first interpolation point.

4. The method according to claim 1, wherein The step of searching, based on the position information of each track point in the flight track point sequence, a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library comprises: Determining reference track point sequences under different sliding windows according to the standard reference trajectory in the standard route geomagnetic fingerprint template library; Determining a 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 the different sliding windows; The reference track point sequence closest to the flight track point sequence is determined as the reference track point sequence corresponding to the flight track point sequence.

5. The method according to claim 1, wherein The 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 includes: Calculating an 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; determining, based on the average Euclidean distance, a similarity between the flight track point sequence and the reference track point sequence; or Calculating a 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; The similarity between the flight track point sequence and the reference track point sequence is determined according to the correlation coefficient.

6. The method according to claim 5, characterized in that Determining in real time, based on the similarity, whether the aircraft has abnormal behavior while flying along the target route includes: Calculating a distance anomaly threshold according to a standard deviation of the geomagnetic field intensity of each reference track point in a reference track point sequence corresponding to the flight track point sequence; If the average Euclidean distance is greater than the distance abnormality threshold, it is determined that the aircraft has an abnormal behavior of track deviation in the corresponding sliding window; or If the correlation coefficient is less than or equal to the preset correlation coefficient, it is determined that the aircraft has an abnormal behavior of track deviation in the corresponding sliding window.

7. The method according to any one of claims 1 to 6, characterized in that Before searching, based on the position information of each track point in the flight track point sequence, a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library, the method further includes: Collecting the position information and geomagnetic field strength of each initial track point on the target route; generating an initial standard reference trajectory according to the position information of each initial track point and the geomagnetic field strength; Based on the position information of each initial track point, interpolating the initial standard reference trajectory to obtain position information of each second interpolation point; For any one of the second interpolation points, determining, from the initial track points, a number of initial track points that are closest to the any one of the second interpolation points; Calculating the geomagnetic field strength of any one of the second interpolation points based on the geomagnetic field strengths corresponding to the initial track points; Calculating the standard deviation of the geomagnetic field intensity at each initial track point and the standard deviation of the geomagnetic field intensity at each second interpolation point based on the geomagnetic field intensity at each initial track point and the geomagnetic field intensity at each second interpolation point; Determining a standard reference trajectory corresponding to the target route based on the position information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each initial track point, and the position information, geomagnetic field strength, and standard deviation of the geomagnetic field strength of each second interpolation point; 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.

8. A low-altitude flight path monitoring device, characterized in that: include: An acquisition unit, used to obtain the position information and geomagnetic field strength of each sampling track point when the aircraft flies along the target route; a generating unit, configured to generate a flight track point sequence of the aircraft in different sliding windows according to the position information of each sampled track point and the geomagnetic field strength; a search unit, configured to search, based on the position information of each track point in the flight track point sequence, for a reference track point sequence corresponding to the flight track point sequence from a standard route geomagnetic fingerprint template library, wherein the standard route geomagnetic fingerprint template library records a standard reference trajectory corresponding to the target route, and the standard reference trajectory includes the position information, geomagnetic field strength, and standard deviation of geomagnetic field strength of each reference track point; a calculation unit, configured to calculate a 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; A determination unit is configured to determine in real time, based on the similarity, whether the aircraft has any abnormal behavior when flying along the target route.

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

10. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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