Aerial target flight prediction method and system combining ADS-B equipment and radar

Abstract

The invention belongs to the technical field of aircraft positioning, and discloses an aerial target flight prediction method and system combining ADS-B equipment and radar, and the method comprises the steps: carrying out the matching of data collected by a radar system and a ground receiver ADS-B, and judging whether to carry out the data collection of a same target or not; if yes, the detection performance of the radar system is evaluated; and based on historical flight data of the air target and real-time flight data of the air target acquired by the optimized radar system, pre-judging a motion track of the air target, further judging whether the motion track of the air target crosses a boundary line or not, and displaying the motion track on an electronic map in real time. By integrating the data of the radar system and the data of the ground receiver ADS-B, accurate acquisition and processing of the flight data of the air target are realized, the detection precision is improved, the flight path of the air target is accurately pre-judged, the decision-making efficiency is enhanced through visual display, and the airspace and border safety is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft positioning, and relates to a method and system for predicting the flight of an airborne target by combining an ADS-B device and a radar. Background Art

[0002] With the rapid progress of aviation technology, the number and types of airborne targets are increasing day by day, and the importance of air situation monitoring and early warning has been increasingly emphasized by people. Under this background, accurately and real-time obtaining and analyzing the flight data of airborne targets is of crucial significance for formulating effective defense strategies, optimizing combat plans, and enhancing airspace management capabilities.

[0003] Traditional airborne target monitoring mainly relies on radar systems, which can provide long-distance and all-weather detection capabilities and play a key role in the identification and tracking of airborne targets. However, with the changes in the form of modern warfare and the continuous development of aviation technology, the detection performance of radar systems has been severely challenged in scenarios such as complex electromagnetic environments, terrain occlusion, and low-altitude penetration. In addition, there are certain limitations in the data update frequency, detection accuracy, and target recognition ability of radar systems, making it difficult to meet the growing airspace management requirements. To make up for the deficiencies of radar systems, the ground receiver ADS-B technology has emerged. ADS-B broadcasts the flight information such as its position, speed, and heading in real time through the transmitter equipped on the airborne target, and the ground receiver can receive and process this information to achieve precise monitoring of airborne targets. With its advantages of high-precision and high-frequency data update capabilities, and being unaffected by terrain and weather conditions, ADS-B technology has become an important means to enhance airspace monitoring capabilities.

[0004] However, in practical applications, how to integrate radar systems and ADS-B technology to accurately predict the movement trajectory of airborne targets and timely identify potential safety risks is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem of how to integrate radar systems and ADS-B technology in the prior art to accurately predict the movement trajectory of airborne targets and timely identify potential safety risks, and to provide a method and system for predicting the flight of an airborne target by combining an ADS-B device and a radar.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for predicting the flight of an airborne target by combining an ADS-B device and a radar, comprising:

[0008] Based on the flight data of airborne targets collected by a radar system and a ground receiver ADS-B respectively;

[0009] Clean and preprocess the collected flight data.

[0010] Match the data collected by both the radar system and the ground receiver ADS-B, and determine whether the radar and the ground receiver ADS-B collect data on the same target. If so, evaluate the detection performance of the radar system based on the data collected by the ground receiver ADS-B.

[0011] Predict the movement trajectory of the airborne target based on the historical flight data of the airborne target and the real-time flight data of the airborne target collected by the optimized radar system.

[0012] Based on the predicted movement trajectory of the airborne target, determine whether the movement trajectory of the airborne target crosses the border line. If so, trigger the warning mechanism and, after visualization processing, display it in real time on the electronic map.

[0013] Preferably, in the above method for predicting the flight of an airborne target by combining an ADS-B device and a radar, the cleaning and preprocessing of the collected flight data specifically includes: detecting whether there are incorrect data, abnormal data, and data missing in the collected flight data. If so, delete, correct, and interpolate the data; and normalize the flight data after the cleaning process to facilitate subsequent data analysis and processing.

[0014] Preferably, in the above method for predicting the flight of an airborne target by combining an ADS-B device and a radar, the matching of the data collected by both the radar system and the ground receiver ADS-B, and the determination of whether the radar and the ground receiver ADS-B collect data on the same target specifically include:

[0015] Extract the position information and speed information from the data collected by the radar system and the ADS-B.

[0016] Compare the target positions of the radar system and the ADS-B at the same timestamp or similar timestamps based on the spatial distance metric.

[0017] Compare the speed information in the radar system and ADS-B data, and respectively compare the direction and flight speed of the airborne target at the same timestamp or similar timestamps.

[0018] If the target positions of the radar and the ADS-B at the same timestamp or similar timestamps are less than the preset threshold, and the directions are similar and the difference in flight speeds is less than the set threshold difference, it is considered that the two data points correspond to the same target.

[0019] Preferably, in the above-mentioned method for predicting the flight of an airborne target by combining an ADS-B device and a radar, before matching the data collected by the radar system and the ground receiver ADS-B, it further includes: calibrating the content clocks of the radar system and ADS-B to ensure the consistency of the timestamps of the radar and ADS-B; determining the moment when the flight data is captured based on the timestamps of the flight data collected by the radar system and ADS-B; if there is a deviation in the timestamps of the flight data collected by the radar system and ADS-B, then perform an optimal matching of the two time series on the time axis based on the dynamic time warping algorithm DTW.

[0020] Preferably, in the above-mentioned method for predicting the flight of an airborne target by combining an ADS-B device and a radar, evaluating the detection performance of the radar system based on the data collected by the ground receiver ADS-B specifically includes: comparing the data collected by the ground receiver ADS-B and the radar system, and fitting the flight data collected by the radar system and ADS-B based on the least squares fitting algorithm; the smaller the fitting error, the closer the detection performance of the radar data is to the benchmark of the ADS-B data.

[0021] Preferably, in the above-mentioned method for predicting the flight of an airborne target by combining an ADS-B device and a radar, the optimized radar system specifically is: optimizing the radar parameters based on the genetic algorithm to obtain the optimized radar system, specifically:

[0022] Encoding and initializing the parameters of the radar system, and setting the population size and iteration times parameters of the genetic algorithm;

[0023] Searching and optimizing based on the genetic algorithm, and recording the optimal solution and fitness value of each iteration;

[0024] When the termination condition is reached, output the optimal solution and decode it into radar parameters;

[0025] Applying the optimized radar parameters to the radar system to obtain the optimized radar system.

[0026] Preferably, in the above-mentioned method for predicting the flight of an airborne target by combining an ADS-B device and a radar, predicting the movement trajectory of the airborne target based on the historical flight data of the airborne target and the real-time flight data of the airborne target collected by the optimized radar system specifically includes:

[0027] Extracting the speed, heading and altitude characteristics of the airborne target based on the historical flight data;

[0028] Normalizing or standardizing the extracted characteristics;

[0029] Training the random forest algorithm based on the normalized data to obtain a trained prediction model;

[0030] Input the current real-time data of the radar system into the trained prediction model to obtain the predicted flight trajectory of the airborne target.

[0031] An airborne target flight prediction system combining an ADS-B device and a radar, comprising:

[0032] An acquisition module, which acquires the flight data of the airborne target respectively based on the radar system and the ground receiver ADS-B;

[0033] A preprocessing module, which cleans and preprocesses the collected flight data;

[0034] A judgment module, which matches the data collected by the radar system and the ground receiver ADS-B, and judges whether the radar and the ground receiver ADS-B collect data on the same target; if so, the detection performance of the radar system is evaluated based on the data collected by the ground receiver ADS-B;

[0035] A pre-judgment module, which pre-judges the movement trajectory of the airborne target based on the historical flight data of the airborne target and the real-time flight data of the airborne target collected by the optimized radar system;

[0036] A visualization module, which judges whether the movement trajectory of the airborne target crosses the border line based on the predicted movement trajectory of the airborne target; if so, triggers an early warning mechanism, and after visualization processing, is displayed in real time on the electronic map.

[0037] A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the airborne target flight prediction method combining an ADS-B device and a radar are performed.

[0038] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the airborne target flight prediction method combining an ADS-B device and a radar are implemented.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] By integrating the data of the radar system and the ground receiver ADS-B, the present invention realizes the accurate acquisition and processing of the flight data of aerial targets. Through data matching and performance evaluation, the detection accuracy of the radar system is effectively improved. At the same time, by combining historical and real-time data to predict the trajectories of aerial targets, cross-border behaviors can be detected and warned in a timely manner, enhancing the border monitoring ability. The present invention not only improves the data processing efficiency, but also realizes the intuitive presentation of information through visual display, providing strong technical support for the monitoring of aerial targets and border security management. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 It is a schematic flowchart of the method for predicting the flight of aerial targets by combining the ADS-B device and the radar of the present invention;

[0043] Figure 2 It is a schematic structural diagram of the system for predicting the flight of aerial targets by combining the ADS-B device and the radar of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0045] 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 present invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0046] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0047] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper", "lower", "horizontal", "inner", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the invention product is usually placed during use. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0048] In addition, if the term "horizontal" appears, it does not mean that the component is required to be absolutely horizontal, but it can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and does not mean that the structure must be completely horizontal, but it can be slightly inclined.

[0049] In the description of the embodiments of the present invention, it should also be noted that unless otherwise clearly specified and limited, if terms such as "set", "installed", "connected", "linked" are used, they should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] The following further describes the present invention in detail with reference to the drawings:

[0051] The present invention discloses an air target flight prediction method combining an ADS-B device and a radar, including:

[0052] S101, based on the flight data of air targets respectively collected by a radar system and a ground receiver ADS-B;

[0053] S102, cleaning and preprocessing the collected flight data;

[0054] Detect whether there are error data, abnormal data and data missing in the collected flight data; if so, delete, correct and interpolate the data; and normalize the flight data after cleaning processing to facilitate subsequent data analysis and processing.

[0055] S103, matching the data collected by the radar system and the ground receiver ADS-B, and judging whether the radar and the ground receiver ADS-B collect data on the same target; if so, taking the data collected by the ground receiver ADS-B as a reference to evaluate the detection performance of the radar system;

[0056] Match the data collected by both the ground receiver ADS-B to determine whether the radar and the ground receiver ADS-B collect data on the same target. Specifically:

[0057] Extract the position information and speed information from the data collected by the radar system and ADS-B;

[0058] Compare the target positions of the radar system and ADS-B at the same timestamp or similar timestamps based on spatial distance metrics;

[0059] Compare the speed information in the radar system and ADS-B data, and respectively compare the directions and flight speeds of airborne targets at the same timestamp or similar timestamps;

[0060] If the target positions of the radar and ADS-B at the same timestamp or similar timestamps are less than a preset threshold, and the directions are similar and the difference in flight speeds is less than the set threshold difference, then the two data points are considered to correspond to the same target.

[0061] Before matching the data collected by both the radar system and the ground receiver ADS-B, it also includes: calibrating the content clocks of the radar system and ADS-B to ensure the consistency of the timestamps of the radar and ADS-B; determining the moment when the flight data is captured based on the timestamps of the flight data collected by the radar system and ADS-B; if there is a deviation in the timestamps of the flight data collected by the radar system and ADS-B, then perform optimal matching on the two time series on the time axis based on the dynamic time warping algorithm DTW.

[0062] Evaluate the detection performance of the radar system based on the data collected by the ground receiver ADS-B. Specifically: compare the data collected by the ground receiver ADS-B and the radar system, and fit the flight data collected by the radar system and ADS-B based on the least squares fitting algorithm; the smaller the fitting error, the closer the detection performance of the radar data is to the benchmark of the ADS-B data.

[0063] S104, Predict the movement trajectory of the airborne target based on the historical flight data of the airborne target and the flight data of the real-time airborne target collected by the optimized radar system;

[0064] The optimized radar system, specifically: optimize the radar parameters based on the genetic algorithm to obtain the optimized radar system, specifically:

[0065] Encode and initialize the parameters of the radar system, and set the population size and iteration times parameters of the genetic algorithm;

[0066] Perform search and optimization based on the genetic algorithm, and record the optimal solution and fitness value of each iteration;

[0067] When the termination condition is reached, output the optimal solution and decode it into radar parameters;

[0068] Apply the optimized radar parameters to the radar system to obtain the optimized radar system.

[0069] Based on the historical flight data of the airborne target and the flight data of the real-time airborne target collected by the optimized radar system, predict the movement trajectory of the airborne target, specifically:

[0070] Extract the speed, heading, and altitude characteristics of the airborne target based on the historical flight data;

[0071] Perform standardization or normalization processing on the extracted characteristics;

[0072] Train the random forest algorithm based on the normalized data to obtain a trained prediction model;

[0073] Input the current real-time data of the radar system into the trained prediction model to obtain the predicted flight trajectory of the airborne target.

[0074] Among them, training the random forest algorithm based on the normalized data to obtain a trained prediction model, specifically:

[0075] Divide the normalized data into a training set and a test set;

[0076] Configure the parameters of the random forest, such as the number of trees, maximum depth, minimum sample split number, etc.;

[0077] Train the random forest model based on the training set data. When the preset number of splits is reached, the random forest stops splitting;

[0078] Evaluate the performance of the model based on the test set data, such as accuracy, recall rate, F1 score. If the preset effect is achieved, obtain the optimized random forest model.

[0079] S105. Based on the predicted movement trajectory of the airborne target, determine whether the movement trajectory of the airborne target crosses the border line; if so, trigger the warning mechanism and, after visualization processing, display it on the electronic map in real time.

[0080] See Figure 2 , the present invention discloses an airborne target flight prediction system combining an ADS-B device and a radar, including:

[0081] A collection module, where the collection module collects the flight data of the airborne target based on the radar system and the ground receiver ADS-B respectively;

[0082] A preprocessing module that cleans and preprocesses the collected flight data.

[0083] A judgment module that matches the data collected by both the radar system and the ground receiver ADS-B, and determines whether the radar and the ground receiver ADS-B collect data on the same target. If so, it evaluates the detection performance of the radar system based on the data collected by the ground receiver ADS-B.

[0084] A pre-judgment module that pre-judges the movement trajectory of an airborne target based on the historical flight data of the airborne target and the real-time flight data of the airborne target collected by the optimized radar system.

[0085] A visualization module that, based on the predicted movement trajectory of the airborne target, determines whether the movement trajectory of the airborne target crosses the border line. If so, it triggers an early warning mechanism and, through visualization processing, displays it in real time on an electronic map.

[0086] The terminal device provided by the embodiment of the present invention. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above-mentioned method embodiments. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-mentioned device embodiments.

[0087] The computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention.

[0088] The terminal device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory.

[0089] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0090] The memory can be used to store the computer program and / or module. By running or executing the computer program and / or module stored in the memory, and invoking the data stored in the memory, the processor realizes various functions of the terminal device.

[0091] If the module / unit integrated in the terminal device 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 such an understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above various method embodiments can be realized. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included 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, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0092] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for predicting aerial target flight by combining ADS-B equipment and radar, characterized in that: include: Flight data of air targets collected by radar systems and ground receivers ADS-B respectively; Clean and pre-process the collected flight data; Match the data collected by the radar system and the ground receiver ADS-B to determine whether the radar and the ground receiver ADS-B are collecting data on the same target; if so, use the data collected by the ground receiver ADS-B as a benchmark to evaluate the detection performance of the radar system; Predict the movement trajectory of air targets based on their historical flight data and real-time flight data collected by the optimized radar system; Based on the predicted trajectory of the aerial target, determine whether the trajectory of the aerial target crosses the border line; If so, the early warning mechanism is triggered and, after visualization, is displayed in real time on an electronic map.

2. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 1, characterized in that: The collected flight data is cleaned and preprocessed, specifically: the collected flight data is checked for erroneous data, abnormal data, and missing data; If it exists, the data will be deleted, corrected and interpolated; and the cleaned flight data will be normalized to facilitate subsequent data analysis and processing.

3. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 2, characterized in that: The data collected by the radar system and the ground receiver ADS-B are matched to determine whether the radar and the ground receiver ADS-B collect data for the same target, specifically: Extract position and speed information based on data collected by radar systems and ADS-B; Compare the radar system and ADS-B target positions at the same or close timestamps based on spatial distance metrics; Compare the speed information in the radar system and ADS-B data, and compare the direction and flight speed of the air targets with the same or similar timestamps; If the radar and ADS-B target positions at the same or similar timestamps are less than the preset threshold, and the directions are similar and the difference in flight speed is less than the set threshold difference, then the two data points are considered to correspond to the same target.

4. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 3, characterized in that: Before matching the data collected by the radar system and the ground receiver ADS-B, it also includes: calibrating the content clocks of the radar system and ADS-B to ensure the consistency of the timestamps of the radar and ADS-B; determining the time when the flight data is captured based on the timestamp of the flight data collected by the radar system and ADS-B; if there is a deviation in the timestamps of the flight data collected by the radar system and ADS-B, optimally matching the two time series on the time axis based on the dynamic time warping algorithm DTW.

5. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 4, characterized in that: The detection performance of the radar system is evaluated based on the data collected by the ground receiver ADS-B, specifically: comparison is made based on the data collected by the ground receiver ADS-B and the radar system, and the flight data collected by the radar system and ADS-B are fitted based on a minimum fitting algorithm; the smaller the fitting error, the closer the detection performance of the radar data is to the benchmark of the ADS-B data.

6. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 5, characterized in that: The optimized radar system is specifically: radar parameters are optimized based on a genetic algorithm to obtain an optimized radar system, specifically: Encode and initialize the parameters of the radar system, and set the population size and number of iterations of the genetic algorithm; Search and optimize based on genetic algorithms, and record the optimal solution and fitness value of each iteration; When the termination condition is reached, the optimal solution is output and decoded into radar parameters; The optimized radar parameters are applied to the radar system to obtain an optimized radar system.

7. The method for predicting aerial targets in flight by combining ADS-B equipment and radar according to claim 6, characterized in that: The prediction of the movement trajectory of the aerial target based on the historical flight data of the aerial target and the real-time flight data of the aerial target collected by the optimized radar system is specifically as follows: Extract the speed, heading and altitude characteristics of air targets based on historical flight data; Standardize or normalize the extracted features; The random forest algorithm is trained based on the normalized data to obtain a trained prediction model; The current real-time data of the radar system is input into the trained prediction model to obtain the predicted flight trajectory of the aerial target.

8. An aerial target flight prediction system combining ADS-B equipment and radar, characterized in that: include: A collection module, wherein the collection module is based on the flight data of the air target collected by the radar system and the ground receiver ADS-B respectively; A preprocessing module, wherein the preprocessing module cleans and preprocesses the collected flight data; A determination module, wherein the determination module matches the data collected by the radar system and the ground receiver ADS-B to determine whether the radar and the ground receiver ADS-B collect data for the same target; if so, the detection performance of the radar system is evaluated based on the data collected by the ground receiver ADS-B; A prediction module, which predicts the motion trajectory of the aerial target based on the historical flight data of the aerial target and the real-time flight data of the aerial target collected by the optimized radar system; A visualization module, wherein the visualization module determines whether the movement trajectory of the aerial target crosses the border line based on the predicted movement trajectory of the aerial target; If so, the early warning mechanism is triggered and, after visualization, is displayed in real time on an electronic map.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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