A ground-based radar-based airborne debris identification method and device

Abstract

The embodiment of the present application provides a kind of based on ground radar's air float identification method and device, this method includes: establishing Lagrange particle release diffusion model;Obtain the track point information of the high altitude target to be identified;Using Lagrange particle release diffusion model predicts the track of the high altitude target to be identified;According to track point similarity algorithm, identify whether high altitude target is high altitude balloon.In addition, the embodiment of the present application provides a kind of based on ground radar's air float identification device.

Description

Technical Field

[0001] This invention relates to the field of high-altitude target identification, and more specifically, to a method and apparatus for identifying airborne objects based on ground-based radar. Background Technology

[0002] The stratosphere exhibits stable airflow and relatively slow air movement. Particularly within a certain timeframe, the near-zero wind zone at the bottom of the stratosphere can be used for low-dynamic aircraft to remain airborne for extended periods, performing tasks such as high-resolution ground observation and communication relay. Research on stratospheric high-altitude balloons is receiving increasing attention. Compared to long-range aircraft, balloon platforms rely more on buoyancy to maintain suspension, without consuming more energy to overcome their own gravity. This allows balloon platforms to achieve longer periods of sustained flight at high altitudes.

[0003] In the identification phase, commonly used methods include template matching, model-based methods, and machine learning. Template matching identifies targets by calculating the similarity between the target and a template; the result depends on features such as the template's size, orientation, and image elements. To address the computational overhead and inefficiency of template matching and model-based methods, researchers have turned to machine learning algorithms, such as support vector machines, neural networks, and adaptive augmentation, to achieve automatic interpretation of SAR targets. However, these methods still face the problem of enormous computational demands.

[0004] The aforementioned problems are even more pronounced in the identification of specific targets, such as high-altitude balloons. At the same time, these methods also place high demands on radar performance. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method and apparatus for identifying airborne objects, so as to at least solve the technical problem that existing high-altitude balloon identification methods cannot simultaneously meet the requirements of fast and high-accuracy identification, as well as the problem of high requirements for radar performance.

[0006] According to one aspect of the present invention, a method for identifying airborne objects is provided, comprising:

[0007] A Lagrange particle release and diffusion model is established. This model, based on turbulence statistics theory, simulates particle diffusion in the atmosphere by tracking the motion of a large number of particles. Meteorological data, obtained from conventional numerical weather prediction models or short-term forecasts, are used as input to the model. Specifically, meteorological data includes, but is not limited to, air temperature, dew point temperature, total precipitation, mean sea level pressure, surface pressure, and wind speed at different times, locations, and altitudes. The output of the Lagrange particle release and diffusion model is the spatial location information of the particles at different times.

[0008] Acquire the trajectory information of the high-altitude target to be identified. Utilize radar to detect the trajectory information of the high-altitude target. This trajectory information includes: the time the high-altitude target was detected, the target's longitude and latitude coordinates, and its altitude.

[0009] The trajectory of an upper-altitude target to be identified is predicted using a Lagrange particle release and diffusion model. The trajectory point information of the upper-altitude target to be identified is input into the Lagrange particle release and diffusion model, and after calculation, the predicted trajectory points of the upper-altitude target to be identified are obtained.

[0010] The algorithm uses trajectory point similarity to identify whether a high-altitude target is a high-altitude balloon. This algorithm measures the similarity between corresponding points on two trajectories. Then, based on the similarity value and a similarity threshold, it determines whether the target is indeed a high-altitude balloon.

[0011] This invention also provides a high-altitude balloon identification device based on ground radar. The device includes a central processing unit (CPU) capable of performing various appropriate actions and processes based on data and programs stored in a memory. The CPU, memory, input / output section, external storage section, and network section are interconnected via a bus. Attached Figure Description

[0012] Figure 1 flow chart

[0013] Figure 2 Device schematic diagram Detailed Implementation

[0014] Example 1

[0015] According to an embodiment of the present invention, an embodiment of a method for identifying airborne objects is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0016] Figure 1 This is a flowchart of a high-altitude balloon identification method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0017] Step S101: Establish a Lagrange particle release and diffusion model. This model is based on turbulence statistics theory and simulates the diffusion of pollutants in the atmosphere by tracking the motion of a large number of particles. Meteorological data is obtained from conventional numerical weather prediction models or short-term forecasts, and is used as input to the Lagrange particle release and diffusion model. Specifically, meteorological data includes, but is not limited to, air temperature, dew point temperature, total precipitation, mean sea level pressure, surface pressure, and wind speed at different times, locations, and altitudes.

[0018] The output of the Lagrange particle release-diffusion model is the spatial position information of the particle at different times. Specifically, the particle trajectory is calculated by averaging the three-dimensional velocity V of the particle's initial position P(t) and its first guessed position P′(t+Δt). The expression for P′(t+Δt) is: P′(t+Δt)=P(t)+V(P,t)Δt The final position P(t+Δt) obtained from this is: P(t+Δt)=P(t)+0.5[V(P,t)+V(P′,t+Δt)]

[0019] During calculation, the product of V(P,t) and Δt must be set to less than 0.75 times the grid resolution to meet the requirements of computational stability. The three dimensional components of velocity V are the velocity parallel to the X-axis (i.e., longitude), the velocity parallel to the Y-axis (i.e., latitude), and the vertical velocity that keeps the particle on the selected surface.

[0020] Step S102: Obtain the trajectory point information of the high-altitude target to be identified. This is done using the radar's trajectory point information, which includes: the time the high-altitude target was detected, the target's longitude coordinates, latitude coordinates, and altitude. Specifically, at different times (t1, t2, ..., t...) within a time interval of 2T. 2n The coordinate sequences of high-altitude targets were detected respectively. Where X, Y, and H represent the longitude, latitude, and altitude of the target, respectively.

[0021] Step S103: Predict the trajectory of the high-altitude target to be identified using the Lagrange particle release and diffusion model. Input the trajectory point information of the high-altitude target to be identified from step S102 into the model established in step S101. After calculation, the predicted trajectory points of the high-altitude target to be identified are obtained. Specifically, the trajectory point information of the high-altitude target to be identified in step S102 within the time period [0, T) is... Input the model established in step S101, and select prediction step size as T. After model calculation, the predicted trajectory points of the high-altitude target to be identified within the time interval [T, 2T) can be obtained, i.e.

[0022] Step S104: Based on the trajectory point similarity algorithm, identify whether the high-altitude target is a high-altitude balloon. The trajectory point similarity algorithm measures the similarity between two trajectories by the distance between corresponding trajectory points. Then, based on the similarity value and the similarity judgment threshold, determine whether the high-altitude target to be identified is a high-altitude balloon. Specifically, take the LCSS algorithm (Longest Common Subsequence) as an example. Let lcss[i][j] represent the sequence of trajectory point information of the detected high-altitude target within the time interval [T, 2T). and predicted trajectory point information The longest common subsequence, dis[i][j] represents Given the distance between them, we can obtain the following recurrence relation: The final calculated lcss[i][j] is the length of the longest sequence.

[0023] Using the method above, we can calculate the longest common subsequence between paths. For longer paths, the longest common subsequence might be numerically large, but the actual fit might not be so good. Therefore, we usually divide the result by the length of the shorter path, i.e.;

[0024] The values ​​obtained in this way have better measurability. Assuming the similarity threshold is θ, when the similarity measure Similarity(O, O') > θ, we consider trajectories O and O' to be similar.

[0025] The embodiments of this invention are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0026] Example 2

[0027] According to an embodiment of the present invention, an embodiment of a high-altitude balloon identification device is provided.

[0028] refer to Figure 2 It shows a schematic diagram of the structure of a computer system suitable for implementing the terminal device / server of the present application.

[0029] Figure 2 The terminal device / server shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments in this application. Figure 2 As shown, the device includes a central processing unit 201, which can perform various appropriate actions and processes based on data and programs stored in a memory 202. The central processing unit 201, the memory 202, the input / output section 204, the external storage section 205, and the network section 206 are interconnected via a bus 203.

[0030] The apparatus described above is used to implement the corresponding methods in the foregoing embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0031] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in the details for the sake of brevity.

[0032] The embodiments of this invention are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for identifying airborne objects based on ground-based radar, characterized in that... include: A Lagrange particle release and diffusion model is established, which is a diffusion model obtained based on turbulence statistical theory. The trajectory point information of the high-altitude target to be identified is obtained using ground-based radar detection. The trajectory of the high-altitude target to be identified is predicted using the Lagrange particle release and diffusion model; The algorithm uses trajectory point similarity to identify whether a high-altitude target is a high-altitude balloon. The trajectory point similarity algorithm measures the similarity between two trajectories by the distance between corresponding trajectory points.

2. The identification method according to claim 1, establishing a Lagrange particle release and diffusion model, characterized in that... include: The model is based on turbulence statistics theory and simulates particle diffusion by tracking the motion of a large number of particles in the atmosphere. The input to the model is meteorological data, which is analysis data or short-term forecast data generated by conventional numerical weather prediction models, covering information such as air temperature, dew point temperature, total precipitation, mean sea level pressure, surface pressure and wind speed at different times, locations and altitudes. The model outputs the spatial position information of the particles at different times.

3. The identification method according to claims 1-2, wherein trajectory point information of the high-altitude target to be identified is obtained, characterized in that... include: The trajectory point information includes: the time when the high-altitude target was detected, the longitude coordinates, latitude coordinates, and altitude of the high-altitude target.

4. The identification method according to claims 1-3, wherein the trajectory of the high-altitude target to be identified is predicted using a Lagrange particle release and diffusion model, characterized in that... include: The trajectory point information of the high-altitude target to be identified within the time period [0, T) is input into the established model, and the prediction step size is selected as T. After model calculation, the predicted trajectory point information of the high-altitude target to be identified within the time period [T, 2T) can be obtained.

5. A high-altitude balloon identification device based on ground radar, characterized in that... include: The central processing unit (CPU), memory, input / output section, external storage section, and network section are interconnected via a bus. The CPU can perform various appropriate actions and processes based on the data and programs stored in memory.

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