Space surveillance and tracking radar, and analyzing method of space surveillance and tracking radar

Abstract

To provide a space surveillance and tracking radar that can analyze a risk of collision between space objects and a risk of falling of space objects and that can list the space objects.SOLUTION: The present disclosure provides a pulse integration method suitable for detection of a space object, a tracking method reflecting orbital dynamic characteristics in a tracking method, and a resource management technology suitable for space surveillance, in relation to a detection / tracking function. The present disclosure provides a method that considers both a relative range and dispersion (or standard deviation) instead of the method of a relative range among identification methods using orbital correlation, in relation to an identification function. The present disclosure provides a method of determining an orbit by utilizing the law of the areal velocity schedule using time between ranges for initial orbit determination, in relation to the initial orbit determination. The present disclosure provides a space surveillance and tracking radar that performs Doppler estimation by a Doppler filter bank method, in relation to a Doppler estimation function. The present disclosure provides an effective visualization method suitable for space surveillance, in relation to a visualization function.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a space surveillance and tracking radar for monitoring and tracking space objects for listing space objects, and an analysis method of the space surveillance and tracking radar.

Background Art

[0002] A space surveillance and tracking radar means a radar that monitors and tracks space objects for the purpose of listing space objects. The space surveillance and tracking radar provides data for analyzing the collision risk between space objects and the risk of space object fall.

[0003] When broadly classifying the functions performed by a space surveillance and tracking radar, they can be divided into detection / tracking, identification, initial orbit determination, Doppler estimation, and visualization. Briefly explaining each function, it is as follows.

[0004] ■ Detection / Tracking As a detection method, a statistical method using a detection law, a method using an adaptive detector CFAR, etc. are used. Also, as a method for improving the detection rate, improving the antenna size (or increasing the number of elements), using a high-power amplifier, a pulse superposition method, etc. are used. The pulse superposition method includes non-coherent pulse superposition and coherent pulse superposition. Non-coherent pulse superposition is a method of superposing only the signal size, and coherent pulse superposition is a method of compensating the phase and superposing.

[0005] As tracking methods, there are various trackers such as GNN, JPDA, MHT, PHD, etc., and all such trackers have two functions of data association and predict.

[0006] Since detection and tracking each require a load for their respective operations, a radar that uses detection and tracking simultaneously requires resource management technology.

[0007] ■ Identification Refer to the existing well-known orbit list and perform identification using orbit correlation.

[0008] ■ Initial Orbit Determination As methods for performing initial orbit determination via radar, there are methods for determining the initial orbit using only the range, methods for determining the initial orbit using range and angle information, methods for determining the initial orbit using range, doppler, and angle, methods for determining the initial orbit using range and doppler, etc.

[0009] ■ Doppler Estimation Perform Doppler estimation based on the change in time of the interval between pulses.

[0010] ■ Visualization Visualize the current state and operation status of the space surveillance and tracking radar.

[0011] In the actual realization of the space surveillance and tracking radar, conventionally, military long-range radars have been utilized for space surveillance. However, recently, more advanced technologies have been introduced, and in some countries such as the United States and Germany, radars dedicated to space surveillance and tracking are under development in a form more suitable for the space environment. In such a process, it has been pointed out that there are the following problems for each function of the space surveillance and tracking radar.

[0012] ■ Detection / Tracking Regarding detection, the conventional method of improving the detection rate by utilizing pulse superposition has limitations for objects moving at high speeds. First, there is a problem that it is difficult to perform fast arithmetic pulse superposition in near real-time. Also, it is necessary to compensate for the influence of movement (maneuvering), but superposition is difficult in a state where the movement is not well understood. Furthermore, neither non-coherent / coherent pulse superposition can be used for fast-moving space objects.

[0013] Regarding tracking, in the case of conventional long-range radars, much research has been conducted to track aircraft flying within the Earth. However, unlike such aircraft, cosmic objects perform orbital motion and do not undergo sudden orbital changes. Therefore, when performing data association, there is a high possibility of errors when directly applying conventional radars due to problems where the motion in the form of the orbital motion of cosmic objects has not been considered.

[0014] In addition, radars for cosmic objects have a long pulse interval, which is inconvenient for resource management.

[0015] ■ Identification When performing orbital correlation only based on the position of cosmic objects, if the distance error increases due to frequent recent orbital adjustments, the possibility of successful identification decreases.

[0016] ■ Initial orbit determination It is inappropriate to apply the initial orbit determination method used in long-range radars developed for the Earth's environment to space surveillance and tracking. Substantially, currently, no appropriate initial orbit determination method for space surveillance and tracking is known.

[0017] ■ Doppler estimation In the case of space surveillance and tracking, since the pulse interval is too long and the Doppler accuracy is poor, almost no Doppler information is used.

[0018] ■ Visualization The visualization method is also not known.

Summary of the invention

Problems to be solved by the invention

[0019] The present invention has been derived to solve the problems of the prior art as described above. The present invention aims to provide a space surveillance and tracking radar specialized for monitoring and tracking space objects, which can analyze the collision risk between space objects and the risk of space object fall, and can list space objects, that is. More specifically, the objectives of the space surveillance and tracking radar provided by the present invention for each function are as follows.

[0020] Regarding the detection / tracking function, the present invention aims to provide a pulse superposition method suitable for detecting space objects, a tracking method that reflects orbital dynamics characteristics in the tracking method, and a resource management technology suitable for space surveillance.

[0021] Regarding the identification function, the present invention aims to provide a method that takes into account both relative distance and dispersion (or standard deviation) instead of the method regarding relative distance among the identification methods using orbital correlation.

[0022] Regarding the initial orbit determination function, the present invention aims to provide a method for determining an orbit by repeatedly using range information and range and angle information for initial orbit determination (recursive).

[0023] Regarding the Doppler estimation function, the present invention aims to provide a space surveillance and tracking radar that performs Doppler estimation by a split match filtering method using one pulse.

[0024] Regarding the visualization function, the present invention aims to provide a visualization method that is suitably effective for space surveillance.

Means for Solving the Problems

[0025] To achieve the above object, the space surveillance and tracking radar of the present invention includes a radar antenna 100 for transmitting and receiving radar signals for detecting space objects, an RF transceiver module 200 connected to the radar antenna 100 for converting radar signals into RF signals for transmission and reception, a D / A conversion chip 300 connected to the RF transceiver module 200 for converting digital signals and analog signals into each other, a NIC (Network Interface Card, 400) connected to the D / A conversion chip 300 for transmitting information, a CPU and a memory 510, and a GPU 520 including a GPU processing unit 521 and a GPU memory 522, and a data processing server 500 for detecting, tracking, and identifying and analyzing space objects, a visualization server 600 connected to the data processing server 500 for receiving the transmission of the detection, tracking, and identification and analysis results of space objects and processing them into visualization information, and a monitoring device 700 connected to the visualization server 600 for outputting visualization information. The NIC 400 can be configured to directly access the GPU memory 522 to record information, and the GPU processing unit 521 processes the information stored in the GPU memory 522 and transmits it to the CPU and the memory 510.

[0026] In addition, the method for analyzing a space surveillance and tracking radar according to the present invention is a method for analyzing a space surveillance and tracking radar in which analysis including detection, tracking, and identification of space objects is performed by the space surveillance and tracking radar as described above. The method includes a signal reception step (S1100) in which a radar signal transmitted from the space surveillance and tracking radar and reflected by a space object is received by the space surveillance and tracking radar, a data generation step (S1200) in which radar data D(t, r) shown as a function value of time t and distance r is generated based on the received radar signal, a detection step (S1300) in which a space object is detected by cumulatively analyzing the radar data, a tracking step (S1400) in which radar data related to the space object detected in the detection step (S1300) is data associated, an orbit determination step (S1500) in which an orbit of the space object tracked in the tracking step (S1400) is calculated, an identification step (S1600) in which the space object whose orbit is determined in the orbit determination step (S1500) is identified, and a listing step (S1700) in which the space objects identified in the identification step (S1600) are listed.

[0027] Here, the detection step (S1300) includes a step (S1310) in which M (M = natural number) received radar data are cumulatively stored (D(t1, r1), …, D(t m , r m )); a step (S1320) in which N (N = natural number) radar data having a size equal to or greater than a predetermined boundary value γ are selected, and vectors each composed of time t and distance r are generated; and among the N time and distance vectors, any three samples [t a , t b , t c , [r a , r b , r cis selected (S1331), and as shown in Equation 1, the coefficient set a0, a1, a2 of the governing equation in the form of a quadratic polynomial is calculated (S1332), and the number k of radar data within a distance value (inlier) determined in advance from the governing equation function is counted (S1333). This process is repeated multiple times (step S1330),

Number

Number

Number

[0028] Or in the detection step (S1300), the M received (M = natural number) radar data are cumulatively stored (D(t1, r1), …, D(t m , r m)(Step S1310 to be performed), a step (S1320) in which N pieces of radar data (N = natural number) having a size equal to or greater than a predetermined boundary value γ are selected, and vectors each composed of time t and distance r are generated, and among the N time and distance vectors, any three samples [t a t b t c , [r a r b r c are selected (S1331), and coefficient sets a0, a1, a2 of a governing equation in the form of a quadratic polynomial are calculated as in Equation 4 (S1332), and the number k of radar data whose distance from the governing equation function is within a predetermined distance value (inlier) is counted (S1333). This process is repeatedly performed multiple times (Step S1330), [Number] A single governing equation is determined by the coefficient sets a0, a1, a2 at the time of the maximum value among the plurality of counted k values obtained by repeated execution, or at least one governing equation is determined by the coefficient sets a0, a1, a2 when the counted number k is equal to or greater than a predetermined reference value Thres (Step S1340), and based on the radar data D(t, r) represented by the determined governing equation a0 + a1t[i] + a2t 2 [i]=r, after the size d of the N radar data is phase-compensated for each pulse according to Equation 5 for a specific time t, coherent pulse superposition in which all are added is performed (Step S1352), [Number] [Number] Here, Equation 6 is the compensation phase, ΔR: resolution of one cell, λ: wavelength of the radar center frequency. It is determined whether the absolute value of the result value obtained by superposition is greater than a predetermined detection threshold and satisfies Equation 7 (Step S1360), [Number] When the absolute value of the result value obtained by superposition is greater than a predetermined detection threshold, it is determined that the detection is successful, and the distance r value from the result value determined to be a successful detection to the cosmic object at a specific time t can be determined.

[0029] In addition, the analysis method of the cosmic surveillance and tracking radar further includes a Doppler estimation step in which one radar signal is divided into a plurality of signals and Doppler estimation for one signal is performed before the data-related operation of the tracking step (S1400). The Doppler estimation step includes steps in which the received radar signal s(t) and the divided matched filters (mf1(t), ···, mf n (t)) are calculated according to Equation 8 to obtain N compressed signals, [Number] Steps in which Doppler estimation for the detected distance is performed on N signals by the STFT (Short Time Furier Transform) method or the periodogram method according to Equation 9, [Number] can be included.

[0030] In addition, the tracking step (S1400) performs data-related operations on cosmic objects that are close to within a predetermined reference in a plane so as to satisfy the condition that the movement of the orbit exists on one plane in the inertial coordinate system. Cosmic objects with the same moving direction of the cosmic object and cosmic objects whose distance does not change rapidly within a predetermined reference are classified. If the unconfirmed cosmic object is observed two or more times as a classification result, the orbit determination step (S1500) is performed, and it can be formed so as to be incorporated into a new cosmic object and the tracking step (S1400) is performed.

[0031] Also, the orbit determination step (S1500) can be formed to determine an orbit by recursively using range information and range and angle information for initial orbit determination.

[0032] The method for analyzing the space surveillance and tracking radar further includes a step of determining an operation range of a detection or tracking beam, a step of determining the number of beams that can be operated within the operation range, and a step of determining a scan time obtained by dividing the number of operations by a PRI (Pulse Repetition Interval). When determining the scan time, the angular velocity at which an arbitrarily selected space object passes through the ceiling is measured, and the beam passing time is determined as a value larger than a comparison time obtained by dividing the measured angular velocity by the beam width. The maximum tracking time is determined such that the sum of the scan time and the tracking time is smaller than the beam passing time. When determining the number of beam operations, based on the number of tracking beams determined in advance, the number of maximum simultaneous tracking beams is determined using the ratio of the beams that can be operated only for the tracking time. When there is no operation of the tracking beam, it can be determined to continue operating the search beam.

[0033] Also, the identification step (S1600) includes a step of converting the acquired data into an inertial coordinate system, a step of propagating conventional data regarding space objects existing in a conventional list with respect to the observation vision and converting it into observation data in the inertial coordinate system, a step of calculating the relative distance and dispersion between the acquired data and the observation data, and a step of identifying space objects having relative distance and dispersion values within a predetermined criterion and classifying the space objects of the observation data, based on the acquired data obtained for one space object by the detection step (S1300) and the tracking step (S1400), such that identification using orbit correlation considering relative distance and dispersion is performed.

[0034] Moreover, the visualization method of the space surveillance and tracking radar of the present invention is a visualization method of a space surveillance and tracking radar that visualizes the analysis results of space objects by the space surveillance and tracking radar as described above. It includes an object data storage step in which detection, tracking, and identification analysis results of a plurality of distinguishable space objects transmitted from the data processing server 600 are stored in the memory of the visualization server 600; a shape and trajectory calculation step in which 2D and 3D shapes and trajectories for each space object are calculated by the processing unit of the visualization server 600; a selection system calculation step in which detection status, object type, and RCS (Radar Cross Section) size information for each space object are calculated by the processing unit of the visualization server 600; a selective visualization step in which the shape and trajectory of a space object are visualized and output according to at least one selection system selected from the detection status, object type, and RCS size to the monitoring device 700 by the processing unit of the visualization server 600; and an additional information display step in which the radar status and observation statistics are displayed together with the space object information on the monitoring device 700 by the processing unit of the visualization server 600.

[0035] Here, in the selective visualization step, the detection status of a space object is classified into classification items including {detected space object, tracked space object, space object detected but not in the list, space object detected but not listed, space object in the list but detected}, and different colors or shapes are output according to the detection status or visualization is made such that the displayability can be selected. The object type of a space object is classified into classification items including {operating satellite, satellite with ended operation, launcher debris, space debris, CubeSat, Earth observation satellite, communication satellite, constellation satellite}, and different colors or shapes are output according to the object type or visualization is made such that the displayability can be selected. According to the RCS size of a space object, it can be visualized such that the size of the visualized shape is different.

[0036] In addition, the correction method of the space surveillance and tracking radar of the present invention is a correction method of the space surveillance and tracking radar for correcting the analysis result of a space object by the space surveillance and tracking radar as described above. By means of a correction tower provided outside the space surveillance and tracking radar, physical errors δx, δy, and δz, which are the differences between the physical positions x, y, and z of the transmitter element and the receiver element respectively and the theoretical positions, are calculated to correct the physical positions. Geometric verification and correction are performed by calculating the visual delay (τ) of each of the transmitter element and the receiver element to find the visual synchronization error. For the correction of the receiver element, a sine wave set having at least two frequencies close to each other is generated by the correction tower, received by the receiver element, and a reception correction preparation step in which the phase is measured. For the correction of the transmitter element, a sine wave set having at least two frequencies close to each other is generated by the transmitter element, received by the correction tower, and a transmission correction preparation step in which the phase is measured. By performing a plurality of calculations so as to minimize the error in the relative distance R relational expression of Equation 10 using the ambiguity up to the least common multiple of two wavelengths and a generally known relative distance value in advance, the unknowns n and m are determined, and a relative distance calculation step for calculating the relative distance,

Number

Number

Advantages of the Invention

[0037] According to the present invention, since it is specialized for monitoring and tracking of space objects, it is possible to correctly and accurately analyze the collision risk between space objects and the risk of falling of space objects, and there is an effect that space objects can be listed.

[0038] Regarding the detection / tracking function, by introducing a detection / tracking / resource management technology suitable for the detection of space objects, there is an effect of improving the detection / tracking performance and system performance.

[0039] Regarding the identification function, the identification algorithm provided by the present invention has an effect of being stronger in orbit adjustment than the conventional method.

[0040] Regarding the initial orbit determination function, conventionally, no initial orbit determination method suitable for space monitoring and tracking has been known, but the present invention newly presents this.

[0041] Regarding the Doppler estimation function, in the conventional long-distance radar, it was difficult to estimate the Doppler regarding space objects, whereas in the present invention, by introducing a new method, there is an effect that Doppler estimation becomes possible. <000026>

[0042] Regarding the visualization function, there is an effect that an effective visualization method suitable for space monitoring can be realized.

Brief Description of the Drawings

[0043]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Modes for Carrying Out the Invention

[0044] Hereinafter, the space monitoring and tracking radar according to the present invention having the above configuration and the analysis method of the space monitoring and tracking radar will be described in detail with reference to the accompanying drawings.

[0045] [1] Space monitoring and tracking radar FIG. 1 is a configuration diagram of the space monitoring and tracking radar of the present invention. As shown, the space monitoring and tracking radar of the present invention, first, from the perspective of the hardware configuration, includes a radar antenna 100, an RF transceiver module 200, a D / A conversion chip 300, a NIC (Network Interface Card) 400, a data processing server 500, a visualization server 600, and a monitoring device 700.

[0046] As described above, the space surveillance and tracking radar of the present invention is a device that detects, tracks, identifies the orbits of space objects, determines the orbits, and lists and analyzes space objects in response to the collision risk between space objects and the risk of space object fall.

[0047] The radar antenna 100 serves to transmit and receive radar signals for detecting space objects. When a radar signal is transmitted from the radar antenna 100 towards space, if a space object exists, the radar signal is reflected back by the space object. In the radar antenna 100, this reflected radar signal is received and used as basic information for detecting, tracking, and identifying space objects.

[0048] The RF transceiver module 200 is connected to the radar antenna 100 and serves to convert radar signals into RF signals for transmission and reception. Thereby, the radar signals can be standardized for general use.

[0049] The D / A conversion chip 300 is connected to the RF transceiver module 200 and serves to convert digital signals and analog signals into each other. Since radar signals and the converted RF signals are analog signals, it is not easy to directly use them for analysis, so they are converted into more convenient digital signals for analysis. If necessary, it can also serve to convert analog signals into digital signals. Specifically, for example, by including an ADC (Rx) and a DAC (Tx) in a SoC (System on Chip) module, it can be composed of a digital up converter and a digital down converter.

[0050] The NIC 400 is connected to the D / A conversion chip 300 and serves to transmit information.

[0051] The data processing server 500 can include a CPU and a memory 510, and a GPU 520 including a GPU processing unit 521 and a GPU memory 522. In the data processing server 500, analysis for detecting, tracking, and identifying substantial cosmic objects is performed.

[0052] The visualization server 600 is connected to the data processing server 500, receives the transmission of the analysis results of detecting, tracking, and identifying cosmic objects, and plays a role of processing them as visualization information.

[0053] The monitoring device 700 is connected to the visualization server 600 and plays a role of outputting visualization information.

[0054] In a general radar, information analysis is performed by a CPU which is a component of the CPU and the memory 510 of the data processing server 500. However, since the CPU has to perform not only operations for information analysis but also operations for overall device control, commands, etc., in this case, an excessive load is imposed on the CPU, resulting in a problem that resource management becomes difficult.

[0055] In the present invention, in order to solve such a problem, the NIC 400 is formed to directly access the GPU memory 522 to record information, and the GPU processing unit 521 processes the information stored in the GPU memory 522 and transmits it to the CPU and the memory 510. When actually realizing this, a GPU RDMA technology that directly connects the received signal to the memory of the GPU via an optical port can be applied. That is, in the present invention, information is first stored in the GPU memory 522 of the GPU 520, and after the GPU processing unit 521 performs analysis such as detection, tracking, and identification, that is, signal processing, it is transmitted to the CPU and the memory 510, thereby realizing large-capacity communication with less delay and no load on the CPU.

[0056] [2] Analysis method of the space surveillance and tracking radar The analysis such as detection, tracking, and identification actually performed by the data processing server 500 is carried out software-wise. The results of such analysis are stored in the storage unit of the CPU and memory 510 of the data processing server 500, and are also transferred to the memory of the visualization server 600, where they can be visualized and output to the monitoring device 700. Below, the analysis such as detection, tracking, and identification performed by the data processing server 500 will be described in more detail.

[0057] FIG. 2 is a diagram simply illustrating the analysis method of the space surveillance and tracking radar of the present invention as a flowchart. The analysis method of the space surveillance and tracking radar of the present invention can include a signal reception step (S1100), a data generation step (S1200), a detection step (S1300), a tracking step (S1400), an orbit determination step (S1500), an identification step (S1600), and a listing step (S1700). First, a brief explanation of each step is as follows.

[0058] In the signal reception step (S1100), a radar signal transmitted from the space surveillance and tracking radar and reflected by a space object is received by the space surveillance and tracking radar. Specifically, when a radar signal beam is irradiated into space from the transmitter element of the radar antenna 100, in a space with nothing, it only proceeds as it is, but when it contacts a space object, it is reflected and returns. That is, when the reflected signal is captured by the receiver element of the radar antenna 100, it can be known that a space object exists.

[0059] In the data generation step (S1200), radar data D(t, r) represented by function values of time t and distance r is generated based on the received radar signal. Although the radar signal itself is an analog signal, after digitizing it into radar data and performing calculations, it can be analyzed more easily.

[0060] In the detection step (S1300), a cosmic object is detected by accumulating and analyzing the radar data. Here, in terms of accumulating and analyzing the radar data, the present invention can significantly increase the SNR (signal-to-noise ratio), and can obtain a great effect of improving the accuracy and reliability of detection.

[0061] In the tracking step (S1400), the radar data related to the cosmic object detected in the detection step (S1300) is data-associated. Here, in the present invention, by further introducing a new Doppler estimation method, the tracking accuracy and reliability are improved, and the tracking step (S1400) itself also reflects the orbital dynamics characteristics, which is much more suitable for tracking the behavior of cosmic objects than in the prior art.

[0062] In the orbit determination step (S1500), the orbit of the cosmic object tracked in the tracking step (S1400) is calculated. Also in the present invention, the result of the initial orbit determination is preferably utilized for tracking for a cosmic object moving in an orbit.

[0063] In the identification step (S1600), the cosmic object whose orbit is determined in the orbit determination step (S1500) is identified. In particular, in the present invention, although orbit correlation is used, it is more effective to identify a cosmic object moving in an orbit by considering both the relative distance and the dispersion.

[0064] In the listing step (S1700), the cosmic objects identified in the identification step (S1600) are listed.

[0065] Hereinafter, each step of the analysis method of the present invention will be described in more detail and specifically.

[0066] 2-1. Detection step As a general radar detection method, there are methods such as detecting signals above a threshold defined by the user according to the detection law, and CFAR (constant false alarm rate), that is, a method of detecting a signal when the average of the test target cell is larger than the average of appropriate (adaptive) peripheral cells.

[0067] In addition, in order to improve the detection performance, a method of overlapping various pulses is widely used so that the SNR (signal-to-noise ratio) can be increased. However, when the target object is moving, if the pulses are overlapped without considering the movement, errors may occur. Conventionally, in the case of military radars for detecting aircraft, since the movement of the target object is relatively slow and the radar pulse interval is relatively fast, even if the movement of the target object is ignored, there is not much problem. However, when detecting cosmic objects, since the speed of the target object is much faster and the radar pulse interval is relatively large, compensation is essential.

[0068] When using various pulses, the beam may be transmitted several times to the same position for accumulation, or during that time, the target may move and deviate from the beam. Therefore, other beams may be transmitted between the first beam and the second beam. Figure 3 is a diagram illustrating various examples of beam operation scenarios. The upper left diagram in Figure 3 shows the case of operating so that the beams do not overlap, and the upper right diagram in Figure 3 shows a method of operating so that they overlap by about half. Also, the lower diagram in Figure 3 shows a method of operating by transmitting the beam several times to the same position for accumulation. Such beam operation determines how many pulses are irradiated to one beam in consideration of the moving speed of the cosmic object and the width of the beam (this will be explained in more detail below).

[0069] In the detection step (S1300), as described above, the radar signal that has been transmitted into space, has come into contact with a cosmic object, and has been reflected and returned (moreover, for ease of analysis, the radar data obtained by processing and digitizing this signal) is finally used to derive the relative distance of the cosmic object. FIG. 4 is a diagram illustrating, as a flowchart, the detection step of the cosmic surveillance and tracking radar of the present invention divided into more detailed steps, and based on this, the detection step (S1300) will be described in more detail.

[0070] First, the received M (M = natural number) pieces of radar data are cumulatively stored (D(t1, r1), …, D(t m , r m )) (S1310). Among this radar data, not only signals that have actually been reflected by cosmic objects but also noise are mixed. First, in order to remove certain noise, signals with a size smaller than a predetermined threshold value γ are classified as noise and ignored, and the remaining signal data is used for analysis.

[0071] Next, N (N = natural number) pieces of radar data having a size equal to or greater than the predetermined threshold value γ are selected, and vectors each composed of time t and distance r are generated (S1320). That is, the vectors formed here are the time vector [t1, …, t n and the distance vector [r1, …, r n .

[0072] Next, a process of selecting three samples from such data and obtaining a governing equation using these samples is repeatedly performed (S1330). Describing this process in more detailed steps is as follows.

[0073] First, arbitrarily three samples [t a , t b , t c , [r a , r b , r c(S1331). With the sample time vector and distance vector selected in this way, coefficient sets a0, a1, and a2 of the governing equation in the form of a quadratic polynomial are calculated as shown in Equation 12 (S1332). That is, when initially constructing the governing equation, the coefficient sets a0, a1, and a2 are in an unknown state. However, by substituting the values of the sample time vector and distance vector into the quadratic polynomial and solving it, the solutions for the coefficient sets a0, a1, and a2 can be obtained.

[0074] [Number]

[0075] FIG. 5 is an example in which a function graph represented by the above-derived governing equation is drawn and displayed on a graph that accumulatively displays radar data with the pulse order (slow-time) on the horizontal axis and the distance (fast-time) on the vertical axis. Thus, when the governing equation function is drawn, the points indicating each radar data may overlap with the governing equation function or may be slightly separated. Here, when most of the points overlap or are close to the governing equation function, it is considered that the governing equation is very well obtained. Conversely, when there are many points far from the governing equation, it is considered that the governing equation is inappropriately obtained. Quantitatively expressing the calculation for enabling such a determination is as follows. The number k of radar data within a predetermined distance value (inlier) from the governing equation function is counted (S1333).

[0076] As described above, when the step of obtaining the governing equation is performed once, one k value will be obtained. That is, when the above steps are performed multiple times, multiple k values will be obtained. With the k values obtained in this way, it is necessary to determine and decide whether the governing equations obtained in each step are suitable.

[0077] Specifically, a single governing equation is determined by the coefficient set a0, a1, a2 when it is the maximum value among a plurality of counted k values obtained by repeated execution, or at least one governing equation is determined by the coefficient set a0, a1, a2 when the counted number k is equal to or greater than a predetermined reference value Thres (S1340). When a plurality of governing equations are determined, by superimposing them, finally, one governing equation can be obtained.

[0078] When expressing the above process by an algorithm, it can be shown as in Equation 13.

[0079]

Number

[0080] Based on the radar data D(t, r) represented by the thus determined governing equation a0 + a1t[i] + a2t 2 [i] = r, a process of performing pulse superposition from now on to improve the SNR is carried out. As the pulse superposition method, as described above, one of non-coherent pulse superposition or coherent pulse superposition can be selectively used.

[0081] In the case of non-coherent pulse superposition, according to Equation 14, the sizes d of N radar data are all added for a specific time t (S1351). The result value obtained in this way becomes a one-dimensional real number.

[0082]

Number

[0083] In the case of coherent pulse superposition, for a specific time t, after the size d of N radar data is phase-compensated for each pulse according to Equation 15, all are added together (S1352). The resulting value obtained in this way becomes a one-dimensional complex number.

[0084]

Number

[0085] Here, Equation 16 is the compensation phase,

Number

[0086] Finally, it is determined whether the absolute value of the resulting value obtained by superposition is greater than a predetermined detection threshold, that is, whether Equation 17 is satisfied (S1360).

[0087]

Number

[0088] If the absolute value of the resulting value obtained by superposition is greater than the predetermined detection threshold (S1360-Yes), it is determined that the detection is successful, and the value of the distance r from the cosmic object at a specific time t is determined from the resulting value for which the detection is successful. If the resulting value is smaller than the detection threshold (S1360-No), the result is deleted, and the process starts again from the step of selecting N radar data (S1320).

[0089] FIG. 6 is a diagram that visually and intuitively shows an actual example of pulse superposition. The upper diagram of FIG. 6 shows the observed values before range cell migration correction, and a plurality of pulse values are displayed along the time on the vertical axis. As described above, since cosmic objects move considerably faster compared to the pulse interval, as shown in the upper diagram of FIG. 6, the pulse values are not aligned in a row but are shown in a curved shape. Compensating for the movement of such an object, that is, range cell compensation, converts the observed values that were in a curved shape into a straight line in a row as shown in the lower diagram of FIG. 6. In the state of being made straight like this, the sum of the absolute values, that is, non-coherent pulse superposition, and as described above, the result value obtained in this way becomes a one-dimensional real number. Or, in the state of being made straight like this, different phases are compensated and added, that is, coherent pulse superposition, and as described above, the result value obtained in this way becomes a one-dimensional complex number. When the result (that is, k) added in this way becomes a value equal to or greater than a predetermined size, it is determined that the detection has been successful.

[0090] 2-2. Doppler Estimation As described above, when the detection step (S1330) is completed, data-related calculations in the subsequent tracking step (S1340) must be performed. Before that, however, Doppler estimation can be performed. Conventionally, data associated with one target object was collected, and Doppler estimation was performed using the phase difference between them. However, as described above, the conventional method has a problem that the pulse interval is too long to track cosmic objects and the Doppler accuracy is poor, and it could not be practically used.

[0091] In the present invention, in order to solve such a problem, in the Doppler estimation step, one radar signal is divided into a plurality of signals so that Doppler estimation for one signal is performed. Such a process can also be said to be for improving the SNR. The Doppler estimation step in the present invention will be specifically described as follows.

[0092] Figure 7 is an illustration for explaining the Doppler estimation of the present invention. When applying a matched filter mf(t) to the received radar signal s(t), a signal s c (t) in the form shown in the upper diagram of Figure 7 can be obtained. Here, in the present invention, the matched filter is divided into N divided matched filters, and each divided matched filter is applied to the radar signal respectively. That is, the received radar signal s(t) and the N divided matched filters mf1(t), ···, mf n (t) are calculated according to Equation 18, and N compressed signals are obtained.

[0093]

Equation

[0094] The Doppler estimation for the detected distance with respect to the N compressed signals thus obtained is performed by combining them, and here too, an appropriate method among two methods can be selected and used. As the first method, the STFT (Short Time Fourier Transform) method can be used, and in this case, Equation 19 is used.

[0095]

Equation

[0096] As the second method, the periodogram method can be used, and in this case, Equation 20 is used.

[0097]

Equation

[0098] When expressing the above process in an algorithm, it can be shown as in Equation 21.

[0099]

Number

[0100] 2 - 3. Tracking As described above, in the tracking step (S1400), the radar data related to the celestial object detected in the detection step (S1300) is data - associated. Here, different from the case where the target object is an aircraft such as a fighter plane in a conventional radar, since the celestial object to be observed in the present invention undergoes orbital motion, there is a problem that it is not suitable to perform calculations by conventional methods.

[0101] In the present invention, in order to solve such a problem, an assumption is introduced that the orbital motion in the inertial coordinate system exists on one plane, and a tracking calculation is performed so as to satisfy this condition. More specifically, data association is performed on celestial objects that are close within a predetermined reference in the plane. Also, celestial objects with the same moving direction of the celestial object and celestial objects whose distance does not change rapidly within a predetermined reference are classified and tracked. Here, as a result of classification, if an unconfirmed celestial object is observed two or more times, the orbit determination step (S1500) is performed, incorporated into a new celestial object, and the tracking step (S1400) is performed.

[0102] More specifically, the tracking step (S1400) is as follows. FIG. 8 is a flowchart showing the detailed steps of the tracking step (S1400) and its association with other steps (detection step, orbit determination step). Referring to FIG. 8, first, the positions, velocities, and covariances of the celestial objects in the celestial object list are propagated, and tracks of celestial objects passing through the field of view (FOV) of the space surveillance and tracking radar are generated. Here, through resource management, detection beams and tracking beams are allocated and beam operation is performed (this will be described in more detail below). When a celestial object is detected in such a process, the celestial object is detected by the detection step (S1300) as described above.

[0103] In this way, the celestial object detected in the detection step (S1300) is identified by correlation in the list of unconfirmed candidates on the conventional orbit. When the detected celestial object is identified as an unconfirmed object, the orbit determination step (1500) is performed using at least two detection results, enabling the determination of an initial orbit. If the observation values of conventional unconfirmed celestial objects and the initial orbit determination are successful, they are added to the celestial object list, a celestial object candidate track is generated, accumulated in the celestial object candidates, and a recursive initial orbit determination is performed.

[0104] On the other hand, if the celestial object candidate track is no longer observed, after determining the precise orbit using the final initial orbit determination value as the initial value, it is registered in the celestial object list and the celestial object candidate track is removed. If the precise orbit determination fails, an attempt is made for the next observation (i.e., the track when an unconfirmed object enters the FOV after orbit propagation) while maintaining the celestial object candidate track. When identifying in this way, for an object with conventional information, after observing several times through the process as described above, the track is terminated, and the precise orbit can be determined using the terminated track.

[0105] When expressing the above process as an algorithm, it can be shown as in Equation 22.

[0106]

Number

[0107] 2-4. Initial Orbit Determination As described above, in the orbit determination step (S1500), the orbit of the celestial object tracked in the tracking step (S1400) is calculated. In the present invention, the orbit is determined by repeatedly (recursive) using range information and range and angle information for initial orbit determination. By doing so, different from the prior art, since observation information is added, precise orbit information can be ensured, and because angle information that is less precise than the range is desired to be used, an initial orbit determination more suitable for the celestial object can be performed.

[0108] More specifically, the initial orbit determination is as follows. Using two or more observation points arbitrarily selected from unconfirmed space objects, initial orbit determination is performed to generate an unconfirmed track. When one piece of observation information is added to such an unconfirmed track and the initial orbit determination converges without divergence and the covariance is within a value determined by the user, the added unconfirmed observation is classified into the unconfirmed track. Otherwise, it is regarded as an unconfirmed space object and the above process is repeated.

[0109] There are two methods for initial orbit determination: a method using distance and angle information and a method using only distance information. When using distance and angle information, different methods can be used according to the cases of using two, three, four or more observation points. Also, according to the number of observation points, vector analysis using polynomials or orbit element analysis can be used for determination.

[0110] When the above process is expressed by an algorithm, it can be shown as in Formulas 23 to 27.

[0111] ■Initial orbit determination using distance and angle information: Vector analysis of polynomial expansion

[0112]

Number

[0113]

Number

[0114]

Number

[0115] ■Initial orbit determination using distance and angle information: Orbit element analysis

[0116]

Number

[0117]

Number

[0118] After that, if the observation points of the unconfirmed track gather more than six and no more observed values are added, the initial orbit determination can be performed again using only the distance information. Also, when the initial orbit determination using only the distance information derives a value with a small covariance, the initial orbit determination value using only the distance information is used; otherwise, the result used above is used for listing in the space object list.

[0119] When expressing the above process by an algorithm, it can be shown as in Formula 28 and Formula 29.

[0120] ■Initial orbit determination using only distance information: Vector analysis of polynomial expansion

[0121]

Number

[0122] ■Initial orbit determination using only distance information: Orbit element analysis

[0123]

Number

[0124] 2-5. Resource management As described above, in order to perform various operations, a calculation load equivalent to hardware is required, and therefore, it is necessary to introduce an appropriate resource management method. In the present invention, resource management is performed including steps of determining an operation range of a detection or tracking beam, determining an operation number of beams operable within the operation range, and determining a scan time obtained by dividing the operation number by a PRI (Pulse Repetition Interval).

[0125] Here, when determining the scan time, the angular velocity at which an arbitrarily selected celestial object passes through the ceiling is measured, and the beam passing time is determined as a value greater than the comparison time obtained by dividing the measured angular velocity by the beam width. The maximum tracking time is determined such that the sum of the scan time and the tracking time is smaller than the beam passing time. On the other hand, since the number of beams used for tracking is determined in advance, when determining the number of beams in operation, the number of beams in operation for maximum simultaneous tracking is determined using the ratio of the beams that can be operated only for the tracking time. Furthermore, when there is no operation of the tracking beam, it is determined to continue operating the search beam.

[0126] By operating while performing resource management in such a manner, the arithmetic load of the hardware can be effectively reduced.

[0127] 2-6. Identification As described above, in the identification step (S1600), the celestial object whose orbit is determined in the orbit determination step (S1500) is identified. Here, conventionally, a method of estimating only the relative distance has been used. In this case, however, there is a problem that it is difficult to identify a celestial object having a bias error due to maneuvering.

[0128] In the present invention, in order to solve such a problem, identification is performed considering both the relative distance and the dispersion. The detailed steps of the identification step (S1600) will be specifically described as follows.

[0129] First, based on the acquired data obtained for one celestial object by the detection step (S1300) and the tracking step (S1400), the acquired data is converted into an inertial coordinate system. Next, the conventional data regarding the celestial objects existing in the conventional list is propagated with respect to the observation vision and converted into the observation data in the inertial coordinate system.

[0130] The relative distance and variance between the acquired data and the observation data obtained in this way are calculated. Based on such calculation results, celestial objects having a relative distance and variance value within a predetermined standard are identified so that the celestial objects of the observation data can be classified.

[0131] Here, celestial objects having a difference in distance within a predetermined value determined by the user and a variance value within a predetermined value determined by the user are identified to classify the celestial objects. If it cannot fall within the predetermined value, it is classified as an unconfirmed celestial object, and the unconfirmed celestial objects are collected and used for determining the initial orbit.

[0132] [3] Visualization method of space surveillance and tracking radar Most of the objects tracked by conventional military radars are targeted flying objects, which are very different in nature from the celestial objects considered in the present invention. Therefore, it is difficult to visualize appropriate information about celestial objects with the analysis results provided by conventional radars. Accordingly, the present invention presents a visualization method in a manner suitable for celestial objects.

[0133] In the visualization method of the space surveillance and tracking radar of the present invention, a visualization method is presented that visualizes the analysis results of celestial objects in a manner optimized for celestial objects through an object data storage step, a shape trajectory calculation step, a selection system calculation step, a selective visualization step, and an additional information display step. Specific explanations for each step are as follows.

[0134] In the object data storage step, analysis results of detection, tracking, and identification of a plurality of distinguishable celestial objects transmitted from the data processing server 600 are stored in the memory of the visualization server 600. Since a considerable computational load is also required for visualization itself, the data processing server 600 only performs calculations up to the analysis results. Further, by dividing the work so that the visualization server 600 performs the calculations necessary for visualization, the useless load on the data processing server 600 can be reduced, and resources can be concentrated only on analysis.

[0135] In the shape trajectory calculation step, the processing unit of the visualization server 600 calculates the 2D and 3D shapes and trajectories for each celestial object. Although it is possible to display all the shapes and trajectories calculated in this way on a single screen, if this is done, there is a possibility that an excessive number of celestial objects will be displayed simultaneously, making it difficult to observe them properly. Therefore, it can be said that the methodology regarding how to better visualize the analysis results such as the shapes and trajectories of celestial objects so that they can be optimally utilized for practical observations is the step described immediately below.

[0136] In the selection system calculation step, the processing unit of the visualization server 600 calculates the detection status, object type, and RCS (Radar Cross Section) size information for each celestial object. (The selection system will be described in more detail in the following steps.)

[0137] In the selective visualization step, the processing unit of the visualization server 600 visualizes and outputs the shapes and trajectories of celestial objects according to at least one selection system selected from the detection status, object type, and RCS size to the monitoring device 700. That is, instead of displaying a large number of celestial objects simultaneously, after appropriately labeling each celestial object according to the selection system, it is made to be displayed differently or the displayability is determined separately for each item of the selection system. More specifically, it is as follows.

[0138] First, the detection status of celestial objects can be classified into classification items including {detected celestial objects, tracked celestial objects, celestial objects detected but not on the list, celestial objects detected but unable to be listed, celestial objects on the list but detected}. Also, according to the detection status, different colors or shapes can be output, or the displayability can be made selectable and visualized. To give a simple example, only {detected celestial objects} may be selected and shown, or two of {detected celestial objects} / {tracked celestial objects} may be selected and shown, and they may be shown in red / blue so that they can be distinguished from each other.

[0139] In addition, the object types of space objects can be classified into classification items including {operating satellites, decommissioned satellites, launcher debris, space debris, CubeSats, Earth observation satellites, communication satellites, constellation satellites}. Also, different colors or shapes can be output according to the object type, or visualization can be made such that the displayability is selectable. Similar to the above example, only {communication satellites} may be selected and shown, or several desired items may be selected and shown separately by colors, shapes, etc.

[0140] Also, visualization can be made such that the size of the visualized shape changes according to the Radar Cross Section (RCS) size of the space object. RCS means the radar cross-sectional area, and it is a measure indicating the degree of reflection of a radar target shown by the ratio of the intensity of the received scattered electric field to the intensity of the incident electric field at a long distance. RCS is independent of the physical size and is expressed as a function of external shape, structure, material, frequency, polarization, and observation direction.

[0141] In the additional information display step, the processing unit of the visualization server 600 can display radar status and observation statistics together with space object information on the monitoring device 700. By doing so, the surrounding environmental conditions at the time of observation can be grasped at a glance, and analysis regarding the behavior of space objects can be performed more smoothly.

[0142] [4] Correction Method for Space Surveillance and Tracking Radar As described above, the behavior of space objects is observed and analyzed by a space surveillance and tracking radar. However, if there are errors in the space surveillance and tracking radar itself, errors may occur in such analysis results. In order to prevent such errors, means for correction are necessary. Hardware-wise, a plurality of correction towers are provided outside the space surveillance and tracking radar. The correction towers are responsible for correction for each of the transmitter element and the receiver element of the space surveillance and tracking radar. To explain collectively, the correction towers calculate the physical errors δx, δy, δz, which are the differences between the physical positions x, y, z and the theoretical positions of the transmitter element and the receiver element respectively, to correct the physical positions, and calculate the visual delay τ of each of the transmitter element and the receiver element to find the visual synchronization error, so that geometric verification and correction are performed.

[0143] Such a correction method can include a reception correction preparation step, a transmission correction preparation step, a relative distance calculation step, and a geometric verification and correction step. Hereinafter, each step will be described more specifically.

[0144] In the reception correction preparation step, for the correction of the receiver element, a sine wave set having at least two mutually adjacent frequencies is generated by the correction tower, received by the receiver element, and the phase is measured. In the transmission correction preparation step, for the correction of the transmitter element, a sine wave set having at least two mutually adjacent frequencies is generated by the transmitter element, received by the correction tower, and the phase is measured. Here, the reception / transmission correction preparation steps are performed separately for each of the receiver element / transmitter element, and each step may be performed simultaneously. Also, each step is considered to be performed in substantially the same manner, differing only in the transmission / reception direction regardless of the element - correction tower.

[0145] In the relative distance calculation step, the relational expression of the relative distance R in Equation 30 is calculated multiple times so as to minimize the error by using the ambiguity up to the least common multiple of the two wavelengths and a generally known approximate relative distance value, thereby determining the unknowns n and m and calculating the relative distance.

[0146]

Number

[0147] (Here, f1, f2: Two frequencies used for an arbitrary sine wave set, φ1, φ2: The phase difference between the phase generated at the correction tower and the measured phase at f1 and f2 respectively, c: Light beam, n, m: Arbitrary integers)

[0148] Regarding the method for determining the unknowns n and m in more detail, it is as follows. Applying the general relationship between frequency f, wavelength λ, and velocity v (f = v / λ) and arranging the terms consisting of complex variables with p, the above equation can be more simply arranged in the form of Equation 31.

[0149]

Number

[0150] Here, ambiguity occurs only up to the distance of the least common multiple of the two wavelengths λ1 and λ2, and since the approximate relative distance is already known, the values of the unknowns n and m can be determined by calculating the above equation several times so as to minimize the error. Furthermore, by performing phase measurement using such a sine wave set several times at different frequencies, the accuracy can be further improved.

[0151] In the geometric verification and correction step, at least four times (since there are four unknowns of physical error and visual delay) of the reception correction preparation step - relative distance calculation step or transmission correction preparation step - relative distance calculation step performed in different environments are used to calculate and correct the physical errors δx, δy, δz and visual delay τ of the receiver element or the transmitter element using the relative distance result R and the formula of Formula 32.

[0152]

Number

[0153] (R cnnm : Relative distance between the antenna element at n×m and the correction tower, x c 、y c 、z c : Absolute position of the antenna element, n, m: Arbitrary positions of the antenna array as arbitrary integers, dx, dy: Intervals of the arrays separated on the x-axis and y-axis, δx nm 、δy nm 、δz nm : Displacements of the antenna element on the x, y, and z axes, bias: System bias with respect to distance)

[0154] By moving the correction tower and measuring several times to numerically calculate δx nm 、δy nm 、δz nm and bias, the error of the space surveillance and tracking radar can be corrected more accurately.

[0155] The present invention is not limited to the above-described embodiments. Needless to say, the applicable distances are diverse, and without departing from the gist of the present invention claimed within the claimed distance, it goes without saying that anyone with ordinary knowledge in the field to which the present invention pertains can perform various modifications.

Explanation of Signs

[0156] 100 Radar antenna 200 RF transceiver module 300 D / A conversion chip 400 NIC 500 Data processing server[[ID=IO]] 510 CPU and memory 520 GPU 521 GPU processing unit 522 GPU memory 600 Visualization server 700 Monitoring device

Claims

1. A radar antenna (100) for transmitting and receiving radar signals for detecting cosmic objects, an RF transceiver module (200) connected to the radar antenna (100) for converting radar signals into RF signals and transmitting and receiving them, a D / A conversion chip (300) connected to the RF transceiver module (200) for converting digital signals and analog signals into each other, a NIC (Network Interface Card, 400) connected to the D / A conversion chip 300 for transmitting information, a data processing server (500) including a CPU and a memory (510), and a GPU (520) including a GPU processing unit (521) and a GPU memory (522), for detecting, tracking, and identifying and analyzing cosmic objects, a visualization server (600) connected to the data processing server (500) for receiving the transmission of the detection, tracking, and identification and analysis results of cosmic objects and processing them as visualization information, and a monitoring device (700) connected to the visualization server (600) for outputting visualization information. The NIC (400) is configured to directly access the GPU memory (522) to record information, and the GPU processing unit (5 ​ ​ ​ ​ ​ ​ ​ ​ A method for analyzing a space surveillance and tracking radar, comprising: a listing step (S1700) in which the space objects identified in the identification step (S1600) are listed.

3. The detection step (S1300) The step (S1310) in which the received M (M = natural number) radar data are cumulatively stored (D(t １ , r １ ), …, D(t ｍ , r ｍ )); and includes a step (S'1320) of selecting N radar data (N = natural number) having a size equal to or greater than a predetermined boundary value (γ), and generating vectors each composed of time (t) and distance (r); Among the N time and distance vectors, any three samples ([t ａ , t ｂ , t ｃ , [r ａ , r ｂ , r ｃ ) are selected (S1331), and as in Equation 33, a coefficient set (a ０ , a １ , a ２ ) of the governing equation in the form of a quadratic polynomial is calculated (S1332), and the number (k) of radar data within a distance from the governing equation function within a predetermined distance value (inlier) is counted (S1333). The process is repeatedly performed a plurality of times (step S1330), and 【Number 33】 Among the plurality of counted number (k) values obtained by repeated execution, when it is the maximum value, a single governing equation is determined by the coefficient set (a ０ , a １ , a ２ ), or when the counted number (k) is equal to or greater than a predetermined reference value (Thres), at least one governing equation is determined by the coefficient set (a ０ , a １ , a ２ ), step (S1340), Based on the radar data (D(t, r)) represented by the determined governing equation (a ０ + a １ t[i] + a ２ t ２ [i] = r), a step (S1351) of performing non - coherent pulse superposition in which the sizes (d) of N radar data are all added for a specific time (t) according to Equation 34 is performed; 【Number 34】 a step (S1360) of determining whether or not the absolute value of the resultant value obtained by superposition satisfies Equation 35, where the absolute value of the resultant value obtained by superposition is greater than a predetermined detection threshold; 【Number 35】 The method for analyzing a space surveillance and tracking radar according to claim 2, further comprising: when it is determined that the absolute value of the resultant value obtained by superposition is greater than a predetermined detection threshold, determining that detection is successful, and determining a distance (r) value from the resultant value determined to be a successful detection to a space object at a specific time (t).

4. The detection step (S1300) The step (S1310) in which the received M (M = natural number) radar data are cumulatively stored (D(t １ , r １ ), …, D(t ｍ , r ｍ )); includes a step (S1320) of selecting N radar data (N = natural number) having a size equal to or greater than a predetermined boundary value (γ), and generating vectors each composed of time (t) and distance (r); Among the N time and distance vectors, any three samples ([t ａ , t ｂ , t ｃ , [r ａ , r ｂ , r ｃ ) are selected (S1331), and as in Equation 36, a coefficient set (a ０ , a １ , a ２ ) of the governing equation in the form of a quadratic polynomial is calculated (S1332), and the number (k) of radar data within a distance from the governing equation function within a predetermined distance value (inlier) is counted (S1333). The process is repeatedly performed multiple times (step S1330), and 【Number 36】 Among a plurality of counted number (k) values obtained by repeated execution, when it is the maximum value, a single governing equation is determined with a coefficient set (a ０ , a １ , a ２ ), or when the counted number (k) is equal to or greater than a predetermined reference value (Thres), at least one governing equation is determined with a coefficient set (a ０ , a １ , a ２ ), step (S1340); Based on the determined governing equation (a ０ + a １ t[i] + a ２ t ２ [i] = r), after the size (d) of N radar data for a specific time (t) is phase-compensated for each pulse according to Equation 37 and then all added together, a step (S1352) of coherent pulse superposition is performed, 【Number 37】 where Equation 38 is the compensation phase, 【Number 38】 ΔR: resolution of one cell, λ: wavelength of the radar center frequency. a step (S1360) of determining whether or not the absolute value of the resultant value obtained by superposition satisfies Equation 39, where the absolute value of the resultant value obtained by superposition is greater than a predetermined detection threshold; 【Number 39】 The method for analyzing a space surveillance and tracking radar according to claim 2, further comprising: when it is determined that the absolute value of the resultant value obtained by superposition is greater than a predetermined detection threshold, determining that detection is successful, and determining a distance (r) value from the resultant value determined to be a successful detection to a space object at a specific time (t).

5. The method for analyzing a space surveillance and tracking radar further includes a Doppler estimation step of dividing one radar signal into a plurality of signals and performing Doppler estimation on one signal before the data-related operation in the tracking step (S1400), the Doppler estimation step The received radar signal (s(t)) and the partitioned matched filters (mf １ (t),..., mf ｎ (t)) are calculated according to Equation 40 to obtain N compressed signals, 【Number 40】 including a step of performing Doppler estimation on the distances detected for N signals by a STFT (Short Time Fourier Transform) method or a periodogram method according to Equation 41; 【Number 41】 The method for analyzing a space surveillance and tracking radar according to claim 2, characterized by including the above.

6. The tracking step (S1400) is such that, for a celestial object that is close to within a predetermined standard in a plane, data association is performed on the movement of the orbit in the inertial coordinate system satisfying the condition that it exists on one plane. However, celestial objects whose traveling directions coincide and celestial objects whose distances do not change rapidly within a predetermined standard are classified. When an unconfirmed celestial object is observed two or more times as a classification result, the orbit determination step (S1500) is performed, incorporated into a new celestial object, and the tracking step (S1400) is performed. The method for analyzing a space surveillance and tracking radar according to claim 2, characterized in that

7. The orbit determination step (S1500) is characterized in that an orbit is determined by repeatedly (recursively) using distance (range) information for initial orbit determination and distance and angle information. The method for analyzing a space surveillance and tracking radar according to claim 2.

8. For resource management, the method for analyzing a space surveillance and tracking radar further includes steps of determining an operation range of a detection or tracking beam, determining the number of operable beams within the operation range, and determining a scan time obtained by dividing the number of operations by a PRI (Pulse Repetition Interval). When determining the scan time, the angular velocity at which an arbitrarily selected celestial object passes through the ceiling is measured, and the beam passing time is determined as a value larger than a comparison time obtained by dividing the measured angular velocity by the beam width. The maximum tracking time is determined such that the sum of the scan time and the tracking time is smaller than the beam passing time. When determining the number of beam operations, the number of operable beams for only the tracking time is used based on the predetermined number of tracking beams, and the number of maximum simultaneous tracking beams is determined. When there is no operation of the tracking beam, it is determined to continuously operate the search beam. The method for analyzing a space surveillance and tracking radar according to claim 2, characterized in that

9. The identification step (S1600) is such that identification using orbit correlation considering relative distance and dispersion is performed, and based on the acquired data obtained for one celestial object by the detection step (S1300) and the tracking step (S1400), the acquired data is converted into the inertial coordinate system. ​ ​ ​ ​ The step of propagating conventional data regarding cosmic objects existing in a conventional list to the observation vision and converting it into observation data in an inertial coordinate system; The step of calculating the relative distance and variance between the acquired data and the observation data; The method for analyzing a space surveillance and tracking radar according to claim 2, characterized by including the step of identifying cosmic objects having relative distances and variance values within a predetermined criterion and classifying the cosmic objects of the observation data.

10. A visualization method for a space surveillance and tracking radar that visualizes the analysis results of cosmic objects by the space surveillance and tracking radar according to claim 1, An object data storage step of storing in the memory of the visualization server 600 the detection, tracking, and identification analysis results of a plurality of distinguishable cosmic objects transmitted from the data processing server 600; A shape and trajectory calculation step of calculating 2D and 3D shapes and trajectories for each cosmic object by the processing unit of the visualization server 600; A selection system calculation step of calculating the detection state, object type, and RCS (Radar Cross Section) size information for each cosmic object by the processing unit of the visualization server 600; A selective visualization step of visualizing and outputting the shape and trajectory of a cosmic object according to at least one selection system selected from the detection state, object type, and RCS size to the monitoring device 700 by the processing unit of the visualization server 600; The visualization method of a space surveillance and tracking radar, characterized by including an additional information display step of displaying the radar state and observation statistics together with the cosmic object information on the monitoring device 700 by the processing unit of the visualization server 600.

11. In the selective visualization step, The detection state of the cosmic object is classified into classification items including {detected cosmic object, tracked cosmic object, cosmic object detected but not in the list, cosmic object detected but not listed, cosmic object in the list but detected}, and different colors or shapes are output according to the detection state or the displayability is selectably visualized. The object types of cosmic objects are classified into classification items including (operating satellites, satellites that have ended operations, launcher debris, space debris, CubeSats, Earth observation satellites, communication satellites, constellation satellites), and different colors or shapes are output according to the object type, or the displayability is selectably visualized. The visualization method of the space surveillance and tracking radar according to claim 10, characterized in that the size of the visualized shape is variably visualized according to the RCS size of the cosmic object.

12. A correction method for a space surveillance and tracking radar that corrects the analysis result of a cosmic object by the space surveillance and tracking radar according to claim 1, A correction tower provided outside the space surveillance and tracking radar calculates physical errors (δx, δy, δz), which are the differences between the physical positions (x, y, z) of the transmitter element and the receiver element and their theoretical positions, to correct the physical positions, and calculates the visual delay (τ) of the transmitter element and the receiver element respectively to find the visual synchronization error, so that geometric verification and correction are performed. For the correction of the receiver element, a reception correction preparation step in which a sine wave set having at least two mutually adjacent frequencies is generated by the correction tower, received by the receiver element, and the phase is measured. For the correction of the transmitter element, a transmission correction preparation step in which a sine wave set having at least two mutually adjacent frequencies is generated by the transmitter element, received by the correction tower, and the phase is measured. Using the ambiguity up to the least common multiple of two wavelengths and a pre-known approximate relative distance value, the relational expression of the relative distance (R) in Equation 42 is calculated multiple times to minimize the error, thereby determining the unknowns n and m and calculating the relative distance in a relative distance calculation step. 【Number 42】 (where f １ 、 f ２ : Two frequencies used for any set of sine waves, φ １ and φ ２ : f １ and f ２ respectively, the phase difference between the phase generated and the phase measured in the correction tower c: light beam, n, m: arbitrary integers), Using the relative distance results (R) obtained by performing at least four reception correction preparation steps - relative distance calculation steps or transmission correction preparation steps - relative distance calculation steps performed in different environments and Equation 43, the physical errors (δx, δy, δz) and visual delay (τ) of the receiver element or the transmitter element are calculated and corrected in a geometric verification and correction step. 【Number 43】 (R ｃｎｎｍ : The relative distance between the antenna element and the correction tower at n×m, x ｃ 、 y ｃ 、 z ｃ : The absolute position of the antenna element, n, m: arbitrary integers, at any position of the antenna array, dx, dy: intervals of the array separated in the x-axis and y-axis directions, δx ｎｍ , δy ｎｍ , δz ｎｍ : Displacements of the antenna element in the x, y, and z axes, bias (system bias with respect to distance), A method for correcting a space surveillance and tracking radar, characterized by including

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