GNSS (Global Navigation Satellite System) suppressing multi-interference source positioning method and system based on ADS-B data

Abstract

The invention discloses a GNSS (Global Navigation Satellite System) suppressing multi-interference source positioning method and system based on ADS-B (Automatic Dependent Surveillance-Broadcast) data. The method comprises the following steps of: extracting a breaking point and a recovery point from a flight path in a monitoring area; noise points in the breaking points and the recovery points are eliminated by using a clustering algorithm; dividing point sets of the breaking points and the recovery points by using a circle fitting method, separating the breaking points and the recovery points caused by different interference sources, and preliminarily solving the number of the interference sources and the initial positions of the interference sources by using the breaking points and the recovery points; when the interference sources obtained by solving the breaking point and the recovery point are the same interference source, merging is completed, and the final number of the interference sources and the final position of the interference sources are obtained. According to the invention, interference source detection and positioning when a plurality of interference sources exist at the same time are realized, and the problem that only single-interference-source positioning can be carried out in the prior art is solved.

Description

Background Art

[0002] The full name of GNSS is Global Navigation Satellite System, which includes GPS of the United States, GLONASS of Russia, GALILEO of Europe, Beidou satellite navigation of China and other systems. GNSS is widely used in research fields such as industry, agriculture, military and science, and has become an indispensable part of people's daily and industrial activities. However, due to the low landing power of GNSS signals, GNSS terminals are susceptible to intentional or unintentional interference, which makes the terminals unable to work normally, leading to serious consequences. Therefore, more requirements and challenges are put forward for the monitoring and positioning of GNSS interference. Automatic Dependent Surveillance-Broadcast (ADS-B) is a new generation of monitoring technology that obtains parameters through the Global Navigation Satellite System (GNSS) and related airborne equipment, and broadcasts the position, speed, heading, identification number and other information of the aircraft to other aircraft or ground base stations. The ADS-B system obtains the flight information of the aircraft through the GNSS system, so the impact of GNSS interference sources on the GNSS receiving signal will eventually be mapped to the ADS-B data, causing data loss, data errors, integrity parameter fluctuations, etc. in the ADS-B system. Therefore, the GNSS interference source can be monitored and located through the big data analysis data of ADS-B.

[0003] As a new generation of surveillance technology, ADS-B has the advantages of high accuracy, high efficiency, high reliability and low cost. Therefore, using ADS-B data for GNSS interference positioning can not only quickly find the interference source, but also greatly improve the monitoring capability of the air traffic control system and ensure aviation safety. When GNSS interference exists, the data reported by the ADS-B system will be lost, wrong, and the integrity parameter fluctuates. The characteristics of a series of changes can be used to monitor the interference source. At present, some papers have proposed to use the characteristics of position loss in the ADS-B data of the interfered flight to monitor GNSS interference. Zixi Liu et al. assumed that the position loss of ADS-B data caused the aircraft to have a track gap as a direct result of entering the affected area, and the interference signal of the interference source was not blocked by buildings. The starting points of these gaps were used as the input data set, and the convex cost function was minimized to locate the interference source. Petr Jonáš*† et al. used the starting and end points of the track gap to define the "Apollonius circle" of the possible RFI source location, combined multiple track gaps, and used the grid probability calculation method to create a heat map of the probability of occurrence of the suppression interference source location to find the most likely location of the interference source.

[0004] Although there are many methods that use the characteristics of trajectory breaks in ADS-B data under GNSS suppression interference to locate interference sources, the current methods are still at the stage of locating a single interference source, and no good method has been proposed for locating multiple interference sources. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a GNSS suppressed multi-interference source positioning method and system based on ADS-B data in response to the deficiencies in the above-mentioned prior art, and to separate the broken breakpoints and recovery points under the influence of different interference sources by using methods such as DBSCAN clustering and circle fitting clustering, so as to realize interference source detection and positioning when multiple interference sources exist at the same time, so as to solve the technical problem that only single interference source positioning can be performed at present.

[0006] The present invention adopts the following technical solutions: A GNSS suppression multi-interference source positioning method based on ADS-B data comprises the following steps: Extract breakpoints and recovery points from flight tracks within the monitoring area; Use clustering algorithm to exclude noise points in breakpoints and recovery points; The breakpoints and recovery points are divided into point sets using the circle fitting method, the breakpoints and recovery points caused by different interference sources are separated, and the number and initial position of the interference sources are preliminarily solved using the breakpoints and recovery points; When the interference sources solved at the breakpoint and the recovery point are the same interference source, the merging is completed to obtain the final number and position of the interference sources.

[0007] Preferably, the breakpoints and recovery points are extracted from the flight tracks within the monitoring area as follows: The location data is obtained from the ADS-B data. After the monitoring area is selected, the location data is converted into the location coordinate system. The location coordinate unit is converted from longitude and latitude to kilometers. The trajectory gap is extracted and the starting and ending points of the trajectory gap are found. When the time difference between two adjacent points on the trajectory is greater than 3 minutes and the distance between the two points is greater than 10 km, a trajectory gap is considered to occur, and the two points are used as the break point and recovery point of the trajectory respectively.

[0008] Preferably, the location data in units of longitude and latitude are first converted into location data in units of kilometers, where X is the horizontal coordinate of the location data in units of kilometers, and Y is the vertical coordinate of the location data in units of kilometers. X and Y are calculated as follows:

[0009]

[0010] in, is the minimum longitude of the selected area, is the minimum latitude of the selected area, is the longitude of the corresponding point, is the latitude of the corresponding point.

[0011] Preferably, for the collected breakpoints and recovery points, the sample point area radius parameter and the minimum number of points within the radius of the DBSCAN clustering are adjusted, and the clustering of the breakpoints and recovery points is completed using the DBSCAN clustering method.

[0012] Preferably, the point set division using the circle fitting method is specifically as follows: Use N breakpoint data in the point set ( x i , y i ), i =1,2,3,...,N, according to the principle of least squares method, the objective function is obtained F ( a,b,c ) minimum value; let F ( a,b,c ) respectively a,b,c Find the partial derivative and set it equal to 0 to get the extreme point. Compare the function values ​​of all extreme points to get the minimum value of the objective function, and then solve a,b,c An estimated value of Finally, the fitting circle center (A, B), fitting radius R, and fitting error absolute value of the point set are obtained. .

[0013] Preferably, the absolute value of the fitting error is:

[0014] in, is the absolute value of the fitting error, ( x i ,y i ) is the ADS-B data location coordinate, ( a,b ) is the coordinate of the center of the fitted circle, r is the radius of the fitted circle, N is the total number of ADS-B data.

[0015] Preferably, the center coordinates (A, B) and radius R are:

[0016] Preferably, the arc segmentation is specifically as follows: Solve for the center point of the point set ( x 0 ,y 0 ), find the center point ( x 0 ,y 0 ) to the azimuth of each point in the point set, and arrange the points in the point set counterclockwise starting from 0° according to the azimuth; like ≤ ε 1 , the fitting arc satisfies the consistent approximation condition, that is, all plane points are replaced by a fitting arc; if > ε 1 If the fitting arc cannot contain all plane points, the method of deleting the last point in turn is used to satisfy ≤ ε 1 Conditional fitting arc; exist ≤ ε 1 Conditionally, the first N 1 points can be fitted with an arc, then the method for finding the second arc is to take the latter (NN 1 +1) points and repeat the above steps to obtain the coordinates of the center of the circle (A 2 ,B 2 ) and radius R 2 ; And so on, the coordinates and radii of all fitted circles are obtained.

[0017] Preferably, the center distance threshold ξ is set to 10. 1 <ξ, the points on the two circles are caused by the same interference source, and the interference source is merged. The position of the interference source after merging is ; After the merging is completed, the final number and location of the interference sources are obtained.

[0018] In a second aspect, an embodiment of the present invention provides a GNSS suppression type multi-interference source positioning system based on ADS-B data, comprising: An extraction module extracts breakpoints and recovery points from flight tracks within the monitoring area; Noise module, which uses clustering algorithm to eliminate noise points in breakpoints and recovery points; The division module uses the circle fitting method to divide the point set for the breakpoints and recovery points respectively, separates the breakpoints and recovery points caused by different interference sources, and uses the breakpoints and recovery points to preliminarily solve the number and initial position of the interference sources; In the positioning module, when the interference sources solved at the breakpoint and the recovery point are the same interference source, the merging is completed to obtain the final number and position of the interference sources.

[0019] In a third aspect, a computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned GNSS suppressed multi-interference source positioning method based on ADS-B data when executing the computer program.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned GNSS suppressed multi-interference source positioning method based on ADS-B data.

[0021] Compared with the prior art, the present invention has at least the following beneficial effects: The present invention is centered around the big data analysis of ADS-B to complete the research of satellite navigation interference monitoring method. Compared with the traditional method of using direction finding equipment to cross-locate the interference source, the use of ADS-B big data analysis is cheaper and more convenient. Because when the approximate location of the interference source is unclear, it is very difficult to find and locate it using the cross-location method, and it will also consume a lot of manpower and material resources. The use of ADS-B data to complete the preliminary positioning of the interference source provides a rough position for the traditional cross-location method based on the direction finding device, which will greatly improve the efficiency of cross-location and reduce the cost of cross-location; the present invention first extracts the breakpoints and recovery points of the flight trajectory from the ADS-B data of the monitoring area, and then uses a clustering algorithm to exclude the noise points in the breakpoints and recovery points. This step helps to improve the positioning accuracy of the interference source and exclude the breakpoints and recovery points of the trajectory caused by non-interference source factors. Then, the breakpoints and recovery points are divided into point sets by the circle fitting algorithm, which can separate the breakpoints and recovery points under the influence of different interference sources, and then the interference source positioning under multiple interference source scenarios can be realized. Finally, by merging the positioning results, the positioning accuracy is improved and the false detection rate is reduced.

[0022] Furthermore, due to the influence of GNSS suppression interference sources, ADS-B data may be lost.

[0023] For the same type of receiver, the interference power at the ADS-B data loss point is constant, and the interference power at the data recovery point is also constant. Assuming that the interference power decays along the free path, the data loss point, i.e., the trajectory break point, is distributed on a circle centered on the interference source, and the data recovery point, i.e., the trajectory recovery point, is also distributed on a circle centered on the interference source. Therefore, by extracting the break point and recovery point of the trajectory and finding the location of the interference source through the circle fitting method, only the location information of the aircraft in the ADS-B data is involved, so the acquisition and positioning cost is low, and positioning is more timely and convenient.

[0024] Furthermore, in real situations, not only the existence of interference sources will cause the loss of aircraft position information, but there will also be various other reasons that cause the loss of aircraft position, such as the obstruction of mountains, receiver abnormalities, etc. However, the loss of position information caused by other reasons is often accidental, so the trajectory breakpoints and recovery points caused are not concentrated in one area, and these points are considered noise points. The trajectory breakpoints and recovery points caused by stable radiation interference sources are often clustered around the interference sources. In order to eliminate the loss of position information caused by non-interference source factors, this paper uses a density-based clustering algorithm DBSCAN to eliminate these noise points, thereby improving the accuracy of positioning; at the same time, the DBSCAN algorithm can simply distinguish the trajectory breakpoints and recovery points under the influence of different interference sources through clustering, which is convenient for locating interference sources in multi-interference source scenarios.

[0025] Furthermore, in order to further distinguish the trajectory breakpoints and recovery points under the influence of different interference sources, that is, to distinguish the points located on different arcs, the circle fitting method is used to divide the breakpoint and recovery point sets. For the data in the point set, the least squares-based circle fitting method is used to obtain the fitting circle center (A, B), fitting radius R, and the absolute value of the fitting error at the same time. . The absolute value of the fitting error To determine whether the points in the point set are roughly located on the arc of a circle. If not, the absolute value of the fitting error is used To continuously adjust the division of points in the point set, so that the large point set is divided into multiple small point sets. The points in each small point set after division are roughly located on the arc of a circle; since the breakpoints and recovery points are roughly distributed on the circle centered on the interference source, the use of the circle fitting method to divide the point set can more finely distinguish the breakpoints and recovery points under the influence of different interference sources, thereby completing the interference source monitoring and positioning under the condition of multiple interference sources.

[0026] Furthermore, since the breakpoint and recovery point are used for positioning respectively, the same interference source may have two different positioning results. Therefore, the two positioning results that are too close are considered to be the positioning results of the same interference source, and the two positioning results are merged by averaging. This step can combine the breakpoint and recovery point for positioning at the same time, further improving the positioning accuracy.

[0027] It can be understood that the beneficial effects of the second aspect mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0028] In summary, the present invention completes the positioning of GNSS interference sources through big data analysis of ADS-B data. Compared with the traditional method of cross-positioning interference sources using direction-finding equipment, the use of ADS-B big data analysis not only reduces costs, but is also more convenient and quick. By combining the DBSCAN clustering algorithm to exclude noise points, the division of trajectory breakpoints and recovery point sets is preliminarily completed, and the positioning accuracy of interference sources can be improved. Through the least squares-based circle fitting algorithm, it is possible to separate the trajectory breakpoints and recovery points under the influence of different interference sources, thereby realizing interference source monitoring and positioning under multiple interference sources.

[0029] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 Schematic diagram of fracture trajectory; Figure 3 It is a schematic diagram of the trajectory in the interference area; FIG4 is a schematic diagram of the clustering results of the breakpoints collected under the interference conditions, wherein (a) is the clustering result of the breakpoints, and (b) is the result after excluding the noise points; Figure 5 Flowchart of arc segmentation algorithm; Figure 6 is the error curve of 50 experiments, where (a) is the error curve of 50 experiments when the Gaussian noise variance is 100m, (b) is the error curve of 50 experiments when the Gaussian noise variance is 200m, (c) is the error curve of 50 experiments when the Gaussian noise variance is 300m, (d) is the error curve of 50 experiments when the Gaussian noise variance is 400m, (e) is the error curve of 50 experiments when the Gaussian noise variance is 500m; Figure 7 is the average error curve of 50 experiments; Figure 8 A schematic diagram of a computer device provided by an embodiment of the present invention; Fig. 9 The present invention is a block diagram of an electronic device provided according to an embodiment. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0033] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0034] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0035] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0036] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0037] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0038] The present invention provides a GNSS suppression type multi-interference source positioning method based on ADS-B data, involving big data analysis, GNSS interference monitoring and positioning, clustering, least squares circle fitting and other methods. Under GNSS suppression interference, the broadcast type automatic dependent surveillance system (ADS-B) that obtains information through GNSS will experience data fluctuation and loss. The changes of ADS-B data in this process are mainly used to realize GNSS suppression interference monitoring and positioning.

[0039] Since the various existing methods of locating GNSS suppression interference sources using ADS-B data can only locate a single interference source, when there are multiple interference sources and the interference areas of the interference sources overlap, it is impossible to distinguish the influence ranges of different interference sources to achieve positioning. The present invention separates the track gap starting point and track gap end point under the influence of different interference sources by designing a data point set partitioning algorithm based on circle fitting, thereby achieving interference source positioning under the condition of multiple interference sources overlapping.

[0040] When GNSS suppression interference occurs, the flight entering the interference area will lose its position, and the position will be restored after leaving the interference area. This will cause the trajectory to be broken, with trajectory break points and recovery points. Figure 2 The figure shows a flight trajectory that flies over a GNSS interference area. Point M1 is the break point of the trajectory, and point M2 is the recovery point of the trajectory.

[0041] Assume that the location of the interference source in a certain area is fixed, such as Figure 3 As shown in the figure, the trajectory loses its position after entering the interfered area and recovers its position when leaving the interfered area. In general, the interference power ratio of the GNSS receiver losing its position and recovering its position is constant, that is, under the condition of free space path loss, the radius ratio of losing its position and recovering its position is constant. Under the condition that the interference source is fixed, omnidirectional and the interference source power is attenuated according to the free space path loss, the breakpoints of the trajectory are distributed on a circle centered on the interference source, and the trajectory recovery points are also distributed on a circle centered on the interference source. Using this feature, the circle fitting algorithm is used to identify the breakpoints and recovery points of the trajectory caused by different interference sources.

[0042] The present invention first extracts breakpoints and recovery points from a large number of flight tracks in a monitoring area, and then uses a clustering algorithm to exclude noise points therein, that is, excludes some track breakpoints and recovery points that have no clustering characteristics and are caused by accidental situations; uses a circle fitting method to divide the point set for the breakpoints, separates the breakpoints caused by different interference sources, and uses the breakpoints to preliminarily solve the number of interference sources and the initial positions of the interference sources; uses the same circle fitting method to divide the point set for the recovery points, separates the recovery points caused by different interference sources, and uses the recovery points to solve the number of interference sources and the initial positions of the interference sources at the same time; and at the same time, judges whether some of the interference sources respectively solved by the breakpoints and the recovery points are the same interference source, and if so, completes merging, and if not, does not merge.

[0043] See also Figure 1 The present invention provides a GNSS suppression type multi-interference source positioning method based on ADS-B data, comprising the following steps: S1. Acquire and collect ADS-B data and pre-process ADS-B data; extract trajectory gaps through big data analysis of trajectory data and find the starting and ending points of trajectory gaps; The location data obtained by the ADS-B system is in longitude and latitude (°). In order to facilitate subsequent processing and calculation, after selecting the target area, the location coordinate system must be converted first, converting the location coordinate unit from longitude and latitude (°) to kilometers (KM). The conversion formula is as follows (X, Y units: KM): (1) (2) in, is the minimum longitude of the selected area, is the minimum latitude of the selected area, is the longitude of the corresponding point, is the latitude of the corresponding point.

[0044] S2, using the DBSCAN clustering method to exclude trajectory breakpoints and recovery points that have no clustering characteristics and are caused by accidental circumstances; Under the influence of GNSS suppression interference, the trajectory reported by the aircraft to the ADS-B system will be broken, with trajectory break points and recovery points. However, there are many reasons for the aircraft trajectory breakage. In addition to the influence of GNSS suppression interference, other accidental factors such as receiver noise can also cause track breakage. Therefore, clustering is needed to eliminate track breakage caused by other accidental factors.

[0045] The DBSCAN clustering method is used to complete clustering. For the collected breakpoints and recovery points, two clustering parameters of DBSCAN clustering are adjusted: the sample point area radius parameter and the minimum number of points within the radius. Clustering is completed and noise points are deleted.

[0046] Please refer to FIG. 4 , which is the clustering result of the breakpoints collected under a certain interference situation, and finally the noise points can be eliminated.

[0047] S3. Use the circle fitting method to divide the point set for the breakpoints, separate the breakpoints caused by different interference sources, and use the breakpoints to preliminarily solve the number of interference sources and the initial position of the interference sources; use the same circle fitting method to divide the point set for the recovery points, separate the recovery points caused by different interference sources, and use the recovery points to solve the number of interference sources and the initial position of the interference sources at the same time; S301, using N breakpoint data in the point set ( x i , y i ), i =1,2,3,...,N, according to the principle of least squares method, the objective function is obtained F ( a,b,c ) minimum value; Objective Function F ( a,b,c ) is calculated as follows: (3) S302, let F ( a,b,c ) respectively a,b,c By finding the partial derivative and setting it equal to 0, we can get the extreme point. By comparing the function values ​​of all extreme points, we can get the minimum value of the objective function, and then we can get a,b,c An estimated value of (4) Among them, (A, B) is the coordinate of the center of the circle, and R is the radius.

[0048] S303, find the center (A, B) of the fitting circle of the point set, the fitting radius R, and the maximum absolute value of the fitting error .

[0049] The absolute value of the fitting error is: (5) See also Figure 5 , for the point series ( x i , y i ), i =1,2,3,...,N, and define the fitting allowable error as ε 1 , the error of each point is Δm; the steps of arc segmentation are as follows: S3031, sorting of points in the point set; Solve the center point of the point set, and set the coordinates of the center point to ( x 0 ,y 0 ), then: (6) (7) In formula (6), x i is the longitude coordinate of each point, n is the number of points in the point set. In formula (7), y i is the latitude coordinate of each point, n is the number of points in the point set.

[0050] Find the center point ( x 0 ,y 0 ) to the azimuth of each point in the point set (i.e. the angle with the x-axis), and arrange the points in the point set counterclockwise starting from 0° according to the azimuth.

[0051] S3032, find the first segment of the fitted arc; For all points in the point set, according to the principle of least squares method, the fitting circle center (A, B), fitting radius R, and the maximum absolute value of the fitting error are obtained. ;like ≤ ε 1 , indicating that the above fitting arc meets the consistent approximation condition, that is, all plane points can be replaced by a fitting arc; if > ε 1 , indicating that the above fitting arc cannot contain all plane points, so the method of deleting the last point in turn is used to satisfy ≤ ε 1 Conditional arc fit.

[0052] S3033, find the second and subsequent arc segments; exist ≤ ε 1 Conditionally, the first N 1 points can be fitted with an arc, then the method for finding the second arc is to take the latter (NN 1 +1) points and repeat step S3022 to obtain the coordinates of the center of the circle (A 2,B 2 ) and radius R 2 ; And so on, the coordinates and radii of all fitted circles are obtained.

[0053] S4. Calculate the distance D between the break point fitting parameters and the recovery point fitting parameters 1 ,When the points on the two circles are caused by the same interference source, the ,interference sources are merged to obtain the final number of interference sources and ,the final positions of the interference sources.

[0054] Assume that the center and radius of a fitting circle at the break point are ( A 1 ,B 1 )and R 1 , the center and radius of a fitting circle at the recovery point are ( A 2 ,B 2 )and R 2 , define the center distance as: (10) Set the center distance threshold ξ=10, when D 1 <ξ, it is considered that the points on the two circles are caused by the same interference source, and the interference source is merged. The position of the interference source after merging is ; After the merging is completed, the final number and location of the interference sources are obtained.

[0055] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "platform".

[0056] In another embodiment of the present invention, a GNSS suppression type multi-interference source positioning system based on ADS-B data is provided. The system can be used to implement the above-mentioned GNSS suppression type multi-interference source positioning method based on ADS-B data. Specifically, the GNSS suppression type multi-interference source positioning system based on ADS-B data includes an extraction module, a noise module, a division module and a positioning module.

[0057] Among them, the extraction module extracts the breakpoints and recovery points from the flight tracks within the monitoring area; Noise module, which uses clustering algorithm to eliminate noise points in breakpoints and recovery points; The division module uses the circle fitting method to divide the point set for the breakpoints and recovery points respectively, separates the breakpoints and recovery points caused by different interference sources, and uses the breakpoints and recovery points to preliminarily solve the number and initial position of the interference sources; In the positioning module, when the interference sources solved at the breakpoint and the recovery point are the same interference source, the merging is completed to obtain the final number and position of the interference sources.

[0058] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the GNSS suppression multi-interference source positioning method based on ADS-B data, including: Extract breakpoints and recovery points from the flight tracks within the monitoring area; use clustering algorithm to eliminate noise points in breakpoints and recovery points; use circle fitting method to divide the point sets for breakpoints and recovery points respectively, separate breakpoints and recovery points caused by different interference sources, and use breakpoints and recovery points to preliminarily solve the number and initial positions of interference sources; when the interference sources solved for breakpoints and recovery points are the same, complete the merger to obtain the final number and final positions of interference sources.

[0059] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0060] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0061] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0062] One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the GNSS suppression multi-interference source positioning method based on ADS-B data in the above embodiment; one or more instructions in the computer-readable storage medium are loaded and executed by the processor as follows: Extract breakpoints and recovery points from the flight tracks within the monitoring area; use clustering algorithm to eliminate noise points in breakpoints and recovery points; use circle fitting method to divide the point sets for breakpoints and recovery points respectively, separate breakpoints and recovery points caused by different interference sources, and use breakpoints and recovery points to preliminarily solve the number and initial positions of interference sources; when the interference sources solved for breakpoints and recovery points are the same, complete the merger to obtain the final number and final positions of interference sources.

[0063] See also Figure 8 , the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the method for calculating the composition of fluid in the reservoir transformation wellbore in the embodiment is realized. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the calculation system for the composition of fluid in the reservoir transformation wellbore in the embodiment are realized. To avoid repetition, it is not described one by one here.

[0064] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 8 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0065] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, central processing units, graphics processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, data processing logic based on quantum computing, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0066] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0067] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0068] Any reference to a memory, database or other medium used in the embodiments provided in the present application may include at least one of a non-volatile and a volatile memory. Non-volatile memory may include a read-only memory (ROM), a magnetic tape, a floppy disk, a flash memory, an optical memory, a high-density embedded non-volatile memory, a resistive random access memory (ReRAM), a magnetic random access memory (MRAM), a ferroelectric random access memory (FRAM), a phase change memory (PCM), a graphene memory, etc. Volatile memory may include a random access memory (RAM) or an external cache memory, etc. As an illustration and not limitation, RAM may be in various forms, such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), etc.

[0069] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0070] See also Fig. 9 The terminal device 600 is an electronic device, and the electronic device is in the form of a general computing device. The components of the electronic device may include but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0071] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 1 Follow the steps shown in .

[0072] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0073] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0074] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0075] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0076] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0077] The ADS-B EXCHANGE website provides free ADS-B data on the first day of each month around the world. Download the data for August 1, 2023 from the ADS-B EXCHANGE website. The downloaded data file is in json format. After parsing the json format data file, consider the integrity of the data and the possibility of interference, and select the research area: longitude -116°~-113°, latitude 43°~46°. Extract the data content of interest, including timestamp, flight registration number, longitude and latitude, navigation integrity category, etc. The extracted data content is shown in Table 1: Table 1 Data name abbreviation Timestamp time ICAO24 icao24 Flight registration number hex latitude lat longitude lon speed gs Geometric height geo_altitude Track Angle heading Navigational integrity categories NIC Geometric height NAC_v The original data downloaded from the website is interference-free, so interference simulation needs to be added. When the aircraft enters the GNSS interference area, the track will be broken, and the track will be restored when leaving the interference area. The above characteristics can be used to simulate GNSS suppression interference. During the simulation process, the interference source is randomly placed and the interference radius of the interference source is determined. The influence range of the interference source cannot be a circle in the ideal case, so Gaussian noise with a mean of 0 and a variance of non-0 is added to the influence range of the interference source, and finally the data value in the interference area is set to empty.

[0078] For the collected ADS-B data, the above scheme is used to extract the start and end points of the flight track gap and locate the interference source; the premise of implementing this scheme is that there must be enough flight data in the detection area to extract a certain number of flight track gap start points and track gap end points. The larger the amount of data extracted and the higher the data quality, the higher the positioning accuracy of the scheme.

[0079] Experimental simulation results During the simulation, the number of interference sources is set to 2, the interference radius is 40KM, the interference ranges of the two interference sources overlap, that is, the distance between the two interference sources is <40KM, and the number of simulations is 50, that is, 50 interference source simulations are performed.

[0080] When the variance of the added Gaussian noise is 100m, 200m, 300m, 400m, and 500m respectively, the error curves of 50 experiments are shown in Figure 6.

[0081] The experimental results show that among the 50 simulations with Gaussian noise variance ranging from 100m to 500m, there are 5 experiments with large errors, reaching more than 20km. This may be due to the misdetection of interference sources caused by accidental circumstances such as insufficient experimental data or uneven distribution of experimental data. Except for this, the errors of other experiments are all within 5km. When the Gaussian noise variance is 500m, there are several experiments with errors >5km.

[0082] Calculate the average error of 50 experiments as Figure 7 As shown in the figure, the experimental results show that as the variance of the added Gaussian noise increases, the positioning error increases, which is consistent with the objective facts. When the Gaussian noise variance is 100m, the minimum positioning error is 4KM, and when the Gaussian noise variance is 500, the maximum positioning error is 6KM.

[0083] The simulation experiment verification of the present invention uses the free ADS-B data downloaded from the ADS-BEXCHANGE website on August 1, 2023. Table 2 shows the specific form and content of the ADS-B data used in the present invention.

[0084] Table 2 ADS-B data format used in the present invention Data name Chinese meaning Data Format unit time Timestamp int Second hex Flight registration number String none lat latitude double Degree (°) lon longitude double Degree (°) gs speed double KM / h geo_altitude Geometric height double foot NIC Navigational integrity categories int none The original data downloaded from the website is data without interference, so in order to verify the solution, interference simulation should be added to the real data. When the aircraft enters the GNSS interference area, the track will be broken, and the track will be restored when leaving the interference area. The above characteristics can be used to simulate GNSS suppression interference; during the simulation process, the interference source is randomly placed, and the interference radius of the interference source is determined. Under normal circumstances, the interference radius of the suppression interference source is 30~60KM. In the present invention, the interference radius of the interference source is set to 40KM. After the interference source is placed and the interference radius is determined, Gaussian noise with a mean of 0 and a non-zero variance is added to the interference radius. Finally, the flight trajectory data in the interference area is deleted to complete the interference simulation.

[0085] In summary, the present invention provides a GNSS suppression type multi-interference source positioning method and system based on ADS-B data, which can complete interference monitoring and positioning in GNSS suppression type single interference source and multiple interference source cases through big data analysis of ADS-B data.

[0086] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0087] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0088] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0089] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0092] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0093] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0094] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0096] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A GNSS suppression multi-interference source positioning method based on ADS-B data, characterized in that: The following steps are involved: Extract breakpoints and recovery points from flight tracks within the monitoring area; Use clustering algorithm to exclude noise points in breakpoints and recovery points; The breakpoints and recovery points are divided into point sets using the circle fitting method, the breakpoints and recovery points caused by different interference sources are separated, and the number and initial position of the interference sources are preliminarily solved using the breakpoints and recovery points; When the interference sources solved at the breakpoint and the recovery point are the same interference source, the merging is completed to obtain the final number and position of the interference sources.

2. The GNSS suppression multi-interference source positioning method based on ADS-B data according to claim 1 is characterized in that: The specific breakpoints and recovery points extracted from the flight tracks within the monitoring area are: The location data is obtained from the ADS-B data. After the monitoring area is selected, the location data is converted into the location coordinate system. The location coordinate unit is converted from longitude and latitude to kilometers. The trajectory gap is extracted and the starting and ending points of the trajectory gap are found. When the time difference between two adjacent points on the trajectory is greater than 3 minutes and the distance between the two points is greater than 10 km, a trajectory gap is considered to occur, and the two points are used as the break point and recovery point of the trajectory respectively.

3. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 2 is characterized in that: First, convert the location data in latitude and longitude into location data in KM. X is the horizontal coordinate of the location data in KM, and Y is the vertical coordinate of the location data in KM. X and Y are calculated as follows: in, is the minimum longitude of the selected area, is the minimum latitude of the selected area, is the longitude of the corresponding point, is the latitude of the corresponding point.

4. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 1 is characterized in that: According to the collected breakpoints and recovery points, the sample point area radius parameters and the minimum number of points within the radius of DBSCAN clustering are adjusted, and the clustering of breakpoints and recovery points is completed using the DBSCAN clustering method.

5. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 1, characterized in that: The point set division using the circle fitting method is as follows: Use N breakpoint data in the point set ( x i , y i ), i =1,2,3,...,N, according to the principle of least squares method, the objective function is obtained F ( a,b,c ) minimum value; let F ( a,b,c ) respectively a,b,c Find the partial derivative and set it equal to 0 to get the extreme point. Compare the function values ​​of all extreme points to get the minimum value of the objective function, and then solve a,b,c An estimated value of Finally, the fitting circle center (A, B), fitting radius R, and fitting error absolute value of the point set are obtained. .

6. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 5 is characterized in that: The absolute value of the fitting error is: in, is the absolute value of the fitting error, ( x i ,y i ) is the ADS-B data location coordinate, ( a,b ) is the coordinate of the center of the fitted circle, r is the radius of the fitted circle, N is the total number of ADS-B data.

7. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 5 is characterized in that: The coordinates of the center (A, B) and the radius R are: 。 8. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 5, characterized in that: The arc segmentation is specifically as follows: Solve for the center point of the point set ( x 0 ,y 0), find the center point ( x 0 ,y 0) The azimuth to each point in the point set. The points in the point set are arranged counterclockwise starting from 0° according to the azimuth; like ≤ ε 1. The fitting arc satisfies the consistent approximation condition, that is, all plane points are replaced by a fitting arc; if > ε 1. If the fitted arc cannot contain all plane points, the method of deleting the last point in sequence is used to satisfy the requirement. ≤ ε 1 condition fitting arc; exist ≤ ε 1, the first N1 points can be fitted with an arc. Then the method for finding the second arc is to take the next (N-N1+1) points and repeat the above steps to solve for the center coordinates (A2, B2) and radius R2; and so on, to obtain the coordinates and radii of all fitted circles.

9. The GNSS suppression type multi-interference source positioning method based on ADS-B data according to claim 1, characterized in that: Set the circle center distance threshold ξ=10. When D1<ξ, the points on the two circles are caused by the same interference source. The interference source is merged. The position of the interference source after merging is ; After the merging is completed, the final number and location of the interference sources are obtained.

10. A GNSS suppression multi-interference source positioning system based on ADS-B data, characterized in that: include: An extraction module extracts breakpoints and recovery points from flight tracks within the monitoring area; Noise module, which uses clustering algorithm to eliminate noise points in breakpoints and recovery points; The division module uses the circle fitting method to divide the point set for the breakpoints and recovery points respectively, separates the breakpoints and recovery points caused by different interference sources, and uses the breakpoints and recovery points to preliminarily solve the number and initial position of the interference sources; In the positioning module, when the interference sources solved at the breakpoint and the recovery point are the same interference source, the merging is completed to obtain the final number and position of the interference sources.

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