KR102089542B1 - Method for analyzing wave propagation characteristics of long range detection radar according to upper air conditions - Google Patents

Abstract

The present invention relates to a method for analyzing the propagation characteristics of a long-range detection radar corresponding to upper air conditions and, more specifically, to a method for analyzing the propagation characteristics of an active electronically scanned array (AESA) radar after reflecting a domestic downtown topography and an atmospheric characteristic in an air-to-air circumstance to a commercial simulation tool. To this end, according to the method for analyzing the propagation characteristics of a long-range detection radar corresponding to upper air conditions, topographic information of a domestic downtown area and a calibrated air refractive index, which is produced by approximating actual measurement atmospheric characteristics (atmospheric pressure, temperature, dew-point and the like), which are actually measured by a weather station, by using a trilinear model, are reflected to an advanced refractive effects prediction system (AREPS) simulation condition which is a commercial simulation tool. Therefore, the propagation characteristics of a long-range detection radar corresponding to various atmospheric phenomena are analyzed such that the analyzed propagation characteristics of the long-range detection radar can be used in order to analyze target detection performance by analyzing a path loss value with respect to a target location in a front surface direction while changing the height and the thickness of a trap under an atmospheric state of the most serious combined atmospheric conditions.

Description

METHOD FOR ANALYZING WAVE PROPAGATION CHARACTERISTICS OF LONG RANGE DETECTION RADAR ACCORDING TO UPPER AIR CONDITIONS}

The present invention relates to a method for analyzing the propagation characteristics of a long-distance detection radar according to high-rise weather, and more specifically, the propagation of an Active Electronically Scanned Array (AESA) radar by reflecting domestic urban topography and atmospheric characteristics in a commercial simulation tool in an air-to-air situation. It is about how to analyze the characteristics.

In general, Active Electronically Scanned Array (AESA) radar, Synthetic Aperture Radar (SAR), and Digital Airport Surveillance Radar (DASR) are long-range radars used as control radars and multi-function radars in civil and military applications. It requires a high-performance radar to accurately detect them.

However, regardless of the characteristics of the radar, the radio environment such as external noise, clutter, propagation attenuation by atmospheric gas or underwater, polarization change and interference by multipath, atmospheric refractive index depending on temperature, air pressure, dew point temperature, etc. It is causing a decrease in performance.

Particularly, in the case of the atmospheric refractive index, the target position is shown by showing different propagation transmission characteristics such as sub refraction, super refraction, normal, ducting, etc. due to a change in refractive inclination according to altitude. It causes difficulty in detection. Accordingly, in order to accurately predict the propagation direction of the propagation, path loss, and propagation coefficient, it is necessary to model the atmospheric refractive index according to altitude and to calculate the atmospheric refractive index.

For modeling the atmospheric refractive index, methods that predicted the atmospheric refractive index for various duct phenomena through optimization techniques from path loss values or clutter power values measured at low altitudes below 1 km in altitude are 'M Wagner, P Gerstoft and T' Rogers, "Estimating Refractivity from Propagation Loss in Turbulent Media," Radio Sci , Vol 51, no 12, pp 1876-1894, Nov 2016 ',' H Benzon1 and P Hoeg1, "Wave Propagation Simulation of Radio Occultations Based on ECMWF Refractivity Profiles , " Radio Sci , Vol 50, no 8, pp 778-788, Aug 2015 '.

In addition, methods for statistical analysis or mathematically modeling the atmospheric refractive index with altitude in a specific region abroad or in Korea are described in 'A Karimian, C Yardim, P Gerstoft, WS Hodgkiss and AE Barrios, "Refractivity Estimation from Sea Clutter: An Invited Review, " Radio Sci , Vol 46, no 6, pp 1-16, Dec 2011 '. 'H Moon, M Jeon, W Kim, SK Oh, JH Lee, S Kwon and YJ Yoon, "Development of Exponential Model of Korea for Improved Altitude Estimation Performance of High-Altitude Target at Radar System," The Journal of Korean Institute of Electromagnetic Engineering and Science , Vol 23, no 7, pp831-839, Jul 2012 ',' ITU-R P453-9, The Radio Refractive Index: Its Formula and Refractivity Data, 2003 ',' ITU-R P853-3, Reference Standard Atmospheres, 1999 '.

In addition, various studies have been conducted on changes in propagation progress in surface-to-air and surface-to-ground, reflecting the atmospheric characteristics of overseas regions. For example, in several coastal regions such as the United States, Europe, and China, several studies on the analysis of path loss reflecting atmospheric duct characteristics and practical low altitude weather data have been reported as' SM Doss-Hammel, CR Zeisse, AE Barrios, G Leeuw, M Moerman, AN Jong, PA Frederickson and KL Davidson, "Low-altitude Infrared Propagation in a Coastal Zone: Refraction and Scattering," Appl Optics , Vol 41, no 18, pp 3706-3724, June 2002 ',' LT Rogers, "Effects of the Variability of Atmospheric Refractivity on Propagation Estimates," IEEE Trans Antennas Propag , Vol44, no 4, pp 460-465, Apr 2015 ',' I Sirkova, "Brief Review on PE Method Application to Propagation Channel Modeling in Sea Environment, " Cent Eur J Eng , Vol 2, no1, pp 19-38, Sep 2012 ',' S Yang, Y Kun-De, Y Yi-Xin and M Yuan-Liang," Experimental Verification of Effect of Horizontal Inhomogeneity of Evaporation Duct on Electromagnetic Wave Propagation, "Chin Phys B, Vol 24, no 4, pp 19-38, Feb 've been in progress in 2015" .

As described above, various studies have been proposed to predict the propagation direction, path loss, and propagation coefficient of accurate propagation, but most of these studies are limited to topographic information and atmospheric refractive index data for offshore coastal areas. Because of the analysis, there was a lack of research reflecting the topographical information and atmospheric characteristics of downtown areas in Korea.

KR 10-1954283 B1, 2019. 02. 26. KR 10-1902833 B1, 2018. 09. 20. KR 10-1868600 B1, 2018. 06. 11. KR 10-1779900 B1, 2017. 09. 13. KR 10-1979770 B1, 2019. 05. 13.

The present invention analyzes the propagation characteristics of a long-range detection radar for various atmospheric phenomena by reflecting the modified atmospheric index of refraction that approximates the topographic information and actual atmospheric characteristics of a domestic downtown area to a simulation condition in a trilinear model. Provides a method and system for analyzing the propagation characteristics of a long-range detection radar according to high-rise weather that analyzes a path loss value for a duct to analyze target detection performance.

The present invention according to an aspect for achieving the above object is to determine the atmospheric index of refraction according to the atmospheric condition of the specific urban area in Korea, including the actual measured air pressure, temperature and dew point temperature in a specific domestic urban area to be measured. Modeling through a trilinear model using two linear lines; Modeling a radiation pattern of an antenna for a long range detection radar; Dividing the modified atmospheric refractive index modeled through the trilinear model into four scenarios; And modeling and analyzing the propagation characteristics of the long-distance detection radar by inputting the topographic information of the specific urban area in Korea, the radiation pattern of the antenna for the long-distance detection radar, and the modified atmospheric refractive index for the four scenarios into a commercial simulation tool. It provides a method for analyzing the propagation characteristics of a long-range detection radar according to high-rise weather, including the steps of.

In addition, in the step of classifying the modified atmospheric refractive index modeled through the trilinear model into four scenarios, the modified atmospheric refractive index modeled through the trilinear model is normal atmospheric, surface duct, and upper duct ( There are four scenarios for elevated duct and combined atmospheric conditions.

In addition, the terrain information of the specific urban area in Korea may be extracted from Digital Terrain Elevation Data (DTED) for the specific urban area in Korea and used as an input to the commercial simulation tool.

In addition, the commercial simulation tool may use an AREPS (Advanced Refractive Effects Prediction System) simulation tool.

In addition, in the step of modeling the radiation pattern of the antenna for a long-range detection radar, the distance dx of the x- axis is 0.475λ, and the distance dy of the y- axis is 0.538λ, and is fixed by y- shifting using a total of 1024 isotropic array elements of 32 × 32. As a method, the radiation pattern of the antenna for the long-range detection radar can be derived.

In addition, the present invention according to another aspect for achieving the above object is an atmospheric refractive index according to the atmospheric condition of the specific domestic downtown area, including the actual measured air pressure, temperature and dew point temperature in a specific domestic downtown area to be measured. Modeling through a trilinear model using 3 linear lines; Modeling a radiation pattern of an AESA (Active Electronically Scanned Array) radar antenna; Dividing the modified atmospheric refractive index modeled through the trilinear model into four scenarios; And modeling and analyzing the propagation characteristics for the AESA radar by inputting the topographic information of the specific urban area in Korea, the radiation pattern of the AESA radar antenna, and the modified atmospheric refractive index for the four scenarios into a commercial simulation tool. In the step of modeling the radiation pattern of the AESA radar antenna, using a total of 1024 isotropic array elements of 32 × 32, the distance dx in the x- axis is 0.475λ, and the distance dy in the y- axis is fixed to y- shift to 0.538λ. It provides a method for analyzing the propagation characteristics of a long-range detection radar according to high-rise weather that derives the radiation pattern of the AESA radar antenna.

In addition, according to another aspect of the present invention for achieving the above object, a computer stored in a computer-readable recording medium that realizes a method for analyzing propagation characteristics of a long-range detection radar according to the high-rise weather described above through being executed by a processor Provide programs.

According to a method of analyzing the propagation characteristics of a long-range detection radar according to high-rise weather according to an embodiment of the present invention, actual measurement actually measured at a weather station and topographic information in a domestic downtown area under the conditions of a commercial simulation tool, Advanced Refractive Effects Prediction System (AREPS) The propagation characteristics of long-range detection radar for various atmospheric phenomena can be analyzed by reflecting the modified atmospheric refractive index that approximates atmospheric characteristics (atmospheric pressure, temperature and dew point temperature, etc.) using a trilinear model.

Furthermore, according to the method of analyzing propagation characteristics of a long-range detection radar according to a high-rise weather according to the present invention, traps in the standby state of the most severe combined atmospheric conditions using the propagation characteristics of the long-range detection radar previously analyzed By changing the height and thickness of the trap, you can easily analyze the target detection performance by analyzing the path loss value for the radar's front-facing target position.

1 is a flowchart illustrating a method for analyzing propagation characteristics of a long-range detection radar according to a high-rise weather according to an embodiment of the present invention.
Figure 2 is a view showing the position of the transmitting antenna and the target and the change of the radio wave transmission proceeding in accordance with the atmospheric refractive index gradient in an air-to-air situation.
3 is a diagram showing atmospheric refractive index calculated using atmospheric characteristics measured at an Osan weather station.
4 is a view for explaining trilinear modeling of atmospheric refractive index according to altitude.
5 is a view illustrating the arrangement shape and arrangement spacing of a 32 × 32 AESA antenna.
6 is a diagram illustrating a directivity pattern of a u - v domain with respect to a front direction.
7 is a view showing a directivity along a zx -plane in a front direction oriented pattern (φ = 0 °) along the θ direction.
FIG. 8 is a diagram in which the maximum altitude hmax is fixed at 100 m to confirm various situations in air-to-air, and simulated in four scenarios of a modified atmospheric refractive index according to the altitude.
9 is a diagram showing the results of a path loss simulation according to four atmospheric refractive index siranios.
10 is a view showing a path loss simulation result according to h ₁ and Δ h at a target height of 5000 m.
11 is a schematic diagram illustrating a propagation characteristic analysis system of a long-range detection radar according to high-rise weather according to an embodiment of the present invention.

The present invention provides a method for analyzing the propagation characteristics of a long-distance detection radar according to high-rise weather reflecting atmospheric characteristics measured by a weather station and topographic information in a domestic downtown area, and proposes a method to analyze radar target detection performance I want to.

To this end, the present invention reflects a modified atmospheric index of refraction that approximates topographic information and actual atmospheric characteristics of a downtown area in Korea to a trilinear model in the conditions of a commercial simulation tool, Advanced Refractive Effects Prediction System (AREPS) simulation. It analyzes the propagation characteristics of the long-distance detection radar for and analyzes the target detection performance by analyzing the path loss value for the duct using it.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in various different forms, and only the embodiments of the present invention make the disclosure of the present invention complete, and the scope of the invention to those skilled in the art It is provided to inform you completely. The same reference numerals in the drawings refer to the same elements.

1 is a flowchart illustrating a method for analyzing propagation characteristics of a long-range detection radar according to a high-rise weather according to an embodiment of the present invention.

Referring to FIG. 1, a method of analyzing propagation characteristics of a long-distance detection radar according to a high-rise weather according to an embodiment of the present invention includes a step (S1) of modeling a linear refractive index according to altitude (S1) and a long-range detection radar (AESA) ) Modeling the antenna pattern (S2), classifying the modified atmospheric refractive index approximated through trilinear modeling into four scenarios (S3), and analyzing propagation characteristics using a commercial simulation tool (S4) ). And, it may further include the step of analyzing the target detection performance (S5).

Trilinear modeling of atmospheric refractive index according to altitude (S1)

FIG. 2 is a diagram for explaining a step of trilinear modeling the atmospheric refractive index for altitude according to the present invention, showing a change in radio wave transmission and a position of a transmitting antenna and a target according to an atmospheric refractive index gradient in an air-to-air situation It is a drawing.

In the propagation progress and target detection scenario for the air-to-air situation as shown in FIG. 2, the height of the transmitting antenna is ' h _s ' , and the height of the target and the distance of the target are defined as 'h _t ' and 'rt', respectively. In this case, if the refraction gradient 대기 M of the atmosphere is greater than 157, the atmospheric characteristics of the sub refraction, the atmospheric characteristics of the normal refraction between 79 and 157, and the super refraction between 0 and 79 The atmospheric characteristics of and, when ∇M is less than 0, indicates the trap, that is, the atmospheric characteristics when a duct phenomenon occurs.

FIG. 3 is a graph showing atmospheric refractive index calculated on a specific date using atmospheric pressure, temperature, and dew point temperature measured at an Osan weather station. In FIG. 3, (a) is January 8, 2010, (b) (C) shows the graph of calculating the atmospheric refractive index using air pressure, temperature, and dew point temperature observed on December 6, 2017, respectively (c). Atmospheric refractive index data measured in FIG. 3 can be expressed as a combination of linear lines, as shown in FIG. 4.

FIG. 4 is a diagram illustrating trilinear modeling of atmospheric refractive index according to altitude.

Referring to FIG. 4, atmospheric refractive index data measured using the air pressure, temperature, and dew point temperature measured in FIG. 3 may be combined with three linear lines to model trilinear.

For example, in FIG. 4, the height and slope of the first and second linear lines are defined as h ₁ , d ₁ , h ₂ and d ₂ , respectively, and the maximum altitude and the third linear line slope are h _max and d. Expressed as ₃ . In addition, when the slope of the second linear line is negative, it indicates that a trap occurs, and the thickness of the trap is defined as Δ h, which is the difference between h ₁ and h ₂ .

In this way, the majority of atmospheric refractive indices confirmed by Osan meteorological stations in Korea can be approximated by modeling using a trilinear model.Advanced Refractive Effects Prediction of AREPS can be varied by changing the slope and height of each linear line. System), it is easy to derive the modified atmospheric refractive index to be input.

Modeling the antenna pattern of a long-range detection radar (AESA) (S2)

An array antenna of AESA (Active Electronically Scanned Array) was used as an example to derive an antenna radiation pattern, which is one of the important input variables for radio wave analysis in air-to-air.

FIG. 5 is a view illustrating the arrangement shape and spacing of the 32 × 32 AESA antenna, and shows an AESA planar array antenna using a total of 1024 isotropic array elements of 32 × 32. 5, the position of the array element in order to improve the grating lobes (grating lobe) x-axis distance dx is 0.475λ, y-axis distance dy was fixed by y -shift to 0.538λ.

6 is a diagram showing a directivity pattern of a u - v domain with respect to a front direction, and FIG. 7 is a diagram showing a directivity with a zx- plane as a front direction directional pattern (φ = 0 °) along the θ direction. to be. The radiation patterns derived from the antennas of FIGS. 6 and 7 have a 4.4 ° HPBW (Half power beam width) and a SLL (Side lobe level) of -35.7dB. This radiation pattern is input to the AREPS simulation tool and used as a source source at h _s height.

Step to divide the modified atmospheric refractive index into four scenarios (S3)

FIG. 8 is a diagram in which maximum altitude hmax is fixed at 100 m to confirm various situations in air-to-air, and simulated in four scenarios of a modified atmospheric refractive index according to the altitude.

As shown in FIG. 8, in the present invention, four scenarios of modified atmospheric refractive index including normal atmosphere, surface duct, upper duct (high tropospheric duct, elevated duct), and combined atmospheric conditions It is separated by.

Of Figure 8 (a) is modified atmospheric refraction slope d1 = d2 = d3 = 90 which represents a normal atmosphere (normal), (b) of Figure 8 is h1 = 0m, h2 = 2000m, Δ h = 2000m, d2 = - Represents the atmosphere for a surface duct with 100, d3 = 90. And, (c) of Figure 8 h1 = 4800m, h2 = 5800m, Δ h = 1000m, d1 = 90, d2 = -100, d3 = 90 to wait for the upper duct (elevated duct) near the AESA radar represents, (d) of Figure 8 is h1 = 4800m, h2 = 5800m, Δ h = 1000m, d1 = 20, d2 = -100, d3 = 180 cho refraction from a lower height to secure a (super refraction), the trap (trap ), A combination of three atmospheric conditions of sub refraction (combined atmospheric condition).

Step of analyzing propagation characteristics using a commercial simulation tool (S4)

The radiation patterns of the AESA array antennas derived through FIGS. 5 to 7 and the modified atmospheric refractive indices for the four scenarios are respectively input to the AREPS commercial simulation tool, while DTED (Digital Terrain Elevation Data), digital terrain elevation of 200 km in Osan, Korea Data) was extracted and used as a simulation condition along with source source height hs = 5000m.

That is, the radiation pattern of the AESA array antenna, the modified atmospheric refractive index for the four scenarios, and the topographic information of a specific urban area in Korea, for example, the topographic information of Osan in Korea, are input to the AREPS commercial simulation tool, respectively, and the AESA radar Propagation characteristics are modeled and analyzed.

Step of analyzing target detection performance (S5)

9 is a diagram showing a result of a path loss simulation according to four atmospheric refractive index siranios.

FIG. 9 (a) is a diagram showing simulation results for a normal atmosphere, and as shown in (a), shows propagation loss in consideration of terrain reflection in a normal atmospheric condition.

FIG. 9 (b) is a view showing simulation results for the surface duct atmosphere, and when the source source elevation is sufficiently high compared to the duct generation point, the simulation results are similar to the normal atmosphere. It was confirmed that it was derived.

9 (c) and 9 (d) are diagrams showing simulation results for a scenario related to an elevated duct and a combined atmospheric condition among four atmospheric refractive index scenarios, and are directed in the front direction in an AESA radar. As a result, the path loss value increases when the beam is steered, which corresponds to scenario conditions in which target detection performance is deteriorated.

As shown in (c) of FIG. 9, when the upper duct is slightly lower than the transmit antenna, the radio waves are transmitted to the lower part based on the source source (source source height hs = 5000m) by the trap. As it progresses, the progress of the radio waves seems to proceed in two ways. As a result, path loss may occur in a large portion in the front direction of the AESA radar, and the target detection performance in the front direction of the AESA radar may be deteriorated.

As shown in (d) of FIG. 9, in the atmosphere for a combined atmospheric condition, since super refraction and sub refraction occur in the upper and lower positions of the duct generation position, respectively, in the front direction. It can be seen that the area in which target detection performance deteriorates due to the rapid increase in path loss increases.

Target distance to check the target detection performance of AESA radar in front direction in air-to-air situationsr _t = 150 km, target heighth _t = 1000/3000/5000/7000 / 9000m The path loss values for each scenario (normal / surface duct / upper duct / combination atmospheric conditions) are shown in Table 1 below.

FIG. 10 is a view showing a simulation result of path loss according to h ₁ and Δ h at a target height of 5000 m, the starting height of a trap (500 m ≤) in a combined atmospheric condition, which is the most serious of the four scenarios. h ₁ ≤ 6000 m) and thickness (50 m ≤ Δ h ≤ 2000 m).

In FIG. 10, the atmospheric refractive inclinations were set to d1 = 20, d2 = -100, d3 = 180, and the height of the front-direction target was fixed to ht = 5000m. The black dotted line in the graph shows the area where the path loss value of the trap h ₂ and the thickness Δ h are 4800 m to 5800 m and 50 m to 2000 m, respectively. It was confirmed that the target power detection performance was rapidly deteriorated because the received power value was significantly reduced by radio wave attenuation in this area.

As described above, in the method of analyzing the propagation characteristics of a long-distance detection radar according to a high-rise weather according to an embodiment of the present invention, a normal atmosphere, a surface duct, an elevated duct using a trilinear model, Atmospheric refractive indices for combined atmospheric conditions and domestic miscalculations were extracted from DTED and applied to AREPS simulation tools to analyze air-to-air AESA radar propagation characteristics, and based on this, path loss values according to target locations were derived. At this time, the array antenna of the AESA radar used a 32 × 32 y- shift plane array shape, and a radiation pattern with 44 ° and 357 dB of HPBW and SLL in the zx- plane was applied to the analysis.

As a result of AREPS simulation in the atmospheric state of the combined atmospheric condition, it was confirmed that the target detection performance was significantly deteriorated because the path loss value for the front-facing target position 150 km away from the source source was 171 dB. And, the path loss value for the target position in the front direction of 5000m in altitude was analyzed by changing the height and thickness of the trap in the atmospheric condition of the combined atmospheric condition. From these results, it was confirmed that the target detection performance was remarkably deteriorated in a region from 4,800 m to 5,200 m, where the trapped height h ₂ was similar to the AESA radar position.

11 is a configuration diagram briefly illustrated to describe a system for analyzing propagation characteristics of a long-range detection radar according to high-rise weather according to an embodiment of the present invention.

Referring to FIG. 11, a system for analyzing propagation characteristics of a long-range detection radar according to a high-rise weather according to an embodiment of the present invention is a domestic air pressure measured at a weather station 10, for example, an air pressure measured at a city center in Osan, It includes an atmospheric refractive index calculating unit 20 for calculating the atmospheric refractive index using the atmospheric characteristics of the downtown area including the temperature and the dew point temperature.

The atmospheric refractive index calculating unit 20 may be implemented in the weather station 10, and as shown in FIG. 2, the weather station 10, for example, Osan, based on the change in radio wave propagation in accordance with the atmospheric refractive index gradient in an air-to-air situation Atmospheric refractive index can be calculated as shown in FIG. 3 by using atmospheric characteristics including atmospheric pressure, temperature, and dew point temperature measured at a weather station.

In addition, the atmospheric refractive index according to the atmospheric state calculated by the atmospheric refractive index calculating unit 20 is modeled by the trilinear modeling unit 30. The trilinear modeling unit 30 models the atmospheric refractive index according to the calculated atmospheric characteristics using three linear lines, as shown in FIG. 4.

The majority of atmospheric refractive indices confirmed by Osan's meteorological station in Korea can be approximated using a trilinear model, and it is easy to derive the modified atmospheric refractive index to be input to the AREPS by changing the slope and height of various linear phenomena. have.

The modified atmospheric refractive index modeled in the trilinear modeling unit 30 is divided into four scenarios by the scenario division unit 40. Scenario division unit 40, as shown in Figure 5, the modified atmospheric model refractive index modeled through the trilinear model 40, normal atmosphere (normal), surface duct (surface duct), upper duct (elevated duct) and combination atmospheric conditions It is divided into four scenarios, such as the atmosphere of (combined atmospheric condition).

The propagation characteristic analysis unit 50 uses terrain information of a specific urban area, for example, terrain information of the downtown area of Osan extracted from Digital Terrain Elevation Data (DTED), and a long-range detection radar modeled from the antenna radiation pattern modeling unit 60. The radiation pattern of the antenna and the modified atmospheric refractive indices for the four scenarios classified in the scenario division unit 40 are input to an AREPS commercial simulation tool to model and analyze the propagation characteristics for a long-range detection radar.

Antenna emission pattern modeling unit 60 AESA distance dx along the x axis to the total using 1024 isotropic array element of the pattern of the radar antenna for a 32 × 32 was 0.475λ, y-axis distance dy is fixed by y -shift to 0.538λ The radiation pattern of the AESA radar antenna is derived by the method described above.

On the other hand, the propagation characteristic analysis system of a long-range detection radar according to high-rise weather according to an embodiment of the present invention is a path loss analysis unit that analyzes path loss based on the propagation characteristics of the long-range detection radar modeled through the propagation characteristic analysis unit 50 ( 70) may be further included.

The path loss analysis unit 70 changes the height and thickness of the trap of the atmospheric refractive index to model propagation characteristics for the modeled long-distance detection radar, while the path to the front target position at high altitude, as shown in FIG. 10. Target detection performance is analyzed by analyzing the loss value.

The method of analyzing the propagation characteristics of the long-range detection radar according to the high-rise weather according to the embodiment of the present invention described above may be executed in the system shown in FIG. 11. For example, it may be implemented in the form of a computer-executable recording medium (or computer program product), such as a program module executed by a computer. Here, the computer readable medium may include a computer storage medium (eg, a memory, hard disk, magnetic / optical medium, or solid-state drive (SSD)). And, the computer-readable medium can be any available medium that can be accessed by a computer, including, for example, both volatile and non-volatile media, removable and non-removable media.

In addition, the method for analyzing propagation characteristics of a long-range detection radar according to high-rise weather according to an embodiment of the present invention includes instructions that may be executed by a computer in whole or in part, and a computer program may include programmable machine instructions processed by a processor. And, it may be implemented in a high-level programming language, an object-oriented programming language, assembly language, or machine language.

In the above, although preferred embodiments of the present invention have been described and illustrated using specific terms, such terms are only intended to clearly describe the present invention, and embodiments and described terms of the present invention are the technical spirit of the following claims. And it is obvious that various changes and changes can be made without deviating from the scope. Such modified embodiments should not be understood individually from the spirit and scope of the present invention and should be said to fall within the scope of the claims of the present invention.

10: weather station
20: atmospheric refractive index calculation unit
30: Trilinear modeling department
40: scenario division
50: radio wave characteristics analysis unit
60: antenna radiation pattern modeling unit
70: path loss analysis unit

Claims (7)

A trilinear model is used to measure the atmospheric refractive index according to the atmospheric condition of the specific domestic urban area including the atmospheric pressure, temperature, and dew point temperature actually measured in a specific domestic urban area to be measured using three linear lines. Modeling through;
Modeling a radiation pattern of an antenna for a long range detection radar;
Dividing the modified atmospheric refractive index modeled through the trilinear model into four scenarios; And
Modeling and analyzing the propagation characteristics for the long-distance detection radar by inputting the terrain information of the specific urban area in the country, the radiation pattern of the antenna for the long-distance detection radar, and the modified atmospheric refractive index for the four scenarios into a commercial simulation tool step;
Method for analyzing the propagation characteristics of a long-range detection radar according to a high-rise meteorology comprising a.
According to claim 1,
In the step of dividing the modified atmospheric refractive index modeled through the trilinear model into four scenarios, the modified atmospheric refractive index modeled through the trilinear model is normal, normal, surface duct, and elevated duct. ) And combined atmospheric conditions are classified into four scenarios.
According to claim 1,
The method of analyzing the propagation characteristics of a long-distance detection radar according to high-rise weather, which is extracted from DTED (Digital Terrain Elevation Data) for the specific urban area in Korea and used as an input to the commercial simulation tool.
According to claim 1,
The commercial simulation tool is a method for analyzing propagation characteristics of a long-range detection radar according to high-rise weather using an AREPS (Advanced Refractive Effects Prediction System) simulation tool.
According to claim 1,
In the step of modeling the radiation pattern of the antenna for the long-range detection radar, the distance dx of the x- axis is 0.475λ and the distance dy of the y- axis is 0.538λ, and is fixed by y- shifting using a total of 1024 isotropic array elements of 32 × 32. Method for analyzing propagation characteristics of a long-range detection radar according to high-rise weather that derives a radiation pattern of the long-range detection radar antenna.
delete A computer program stored in a computer-readable recording medium that realizes a method of analyzing propagation characteristics of a long-range detection radar according to any one of claims 1 to 5 through execution by a processor.

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