The performance of long range radar is affected by the atmospheric conditions and terrain, as well as the beam operation of the radar system. In this paper, a modeling and simulation(M&S) tool was developed considering the external environment and radar systems of long range radars for performance prediction, and was described using the verification method. Atmospheric refraction and wave propagation were simulated using APM, to analyze the effects of the external environment. The beam template of radar, which is used for actual radar systems, was utilized to analyze the effects of beam operation. The developed M&S tool was verified by comparison with the experimental results obtained from three different situations and confirmed to be highly effective in predicting the performance of long range radar.
Factors that contribute to varying radar performance include internal causes such as equipment obsolescence, and external causes such as terrain and atmosphere. In particular, the atmosphere, which is a natural element, causes inevitable performance changes. The refractive index changes with atmospheric conditions in real time and affects the propagation environment, which affects the radar performance. Depending on the refractive index, atmospheric conditions are divided into super, sub, standard, normal, and trap, and the radar performance changes, such as the maximum detection range, occur differently during each atmospheric state. Therefore, it is important to predict and respond to changes in radar performance depending on the atmospheric conditions. In this study, the changes in the maximum detection range at low altitudes and detection performance at a long distance are analyzed using the M&S tool with respect to the refractive index. As a result, the maximum detection range decreases for a larger refractive index and vice versa, while the detection performance at a long distance changes because of abnormal atmospheric conditions.
This paper presents an altitude detection accuracy for long range and multifunction radar. The accuracy is difficult to estimate because it is affected by an time varying atmosphere refractivity. We analyze altitude accuracy with a raytracing simulator with atmosphere refractivity. An altitude error is simulated with measured and modeled refractivity, and the modeled refractivity is used for compensate an altitude accuracy. As a result, the error is modeled with normal distribution function, and analyzed.
To provide adequate radar coverage in an area with mountainous terrain, we require multiple radar stations and complex beam operations to reduce the blocking area. Consequently, the distance between two radar stations is reduced, which causes radio interference due to insufficient frequency bands and reduces the detection performance of the radar system. To prevent this, interference must be detected and avoided. However, it is difficult to predict and respond to interference as the beam operation is complicated. In this study, we developed a modeling and simulation(M&S) method that uses the actual frequency and beam operation to analyze interference and evaluated its effectiveness at different operating frequencies.
In search radar systems, one face of the antenna generally rotates. By contrast, multi-function radar systems operate with four faces in a fixed position. Four-face multi-function radar is operated independently and has the advantage of being able to operate a beam simultaneously using a phased array antenna. However, there are disadvantages in terms of interference between the faces during beam transmission. A search beam can avoid such interference by concurrently sending another beam that is not for tracking owing to differences in their waveforms and transmission times according to the target location and type. In this study, to overcome such disadvantages, we developed a resource management model that applies the concept of tracking synchronization for a simultaneous four-face operation. We analyzed the results of resource changes in the target #1,000 scenario using a resource management model we developed through a modeling and simulation (M&S) tool. As a result, the new resource management system operates the time resources efficiently and improves the radar performance.
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