• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1641-1648
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• 2016

A weather radar estimates Doppler frequency and width of Doppler spectrum from the received weather signal which represents the return echoes from rain or dust particles in a corresponding area. These estimates are very important parameters since they are directly related to precipitation, wind velocity and degree of turbulence. Therefore, these estimated values should be highly reliable to obtain accurate weather information. However, the echoes of a weather radar include both the weather signal and the clutter which occurred from ground reflection or moving objects, etc. The existence of the clutter in the echoes may cause serious errors in the estimation of weather-related parameters. Therefore, in this paper, models are developed to represent the weather signal and the clutter for the purpose of analyzing estimation errors caused by the strong clutter echoes. Using these models, various return echoes according to the weather signal and clutter power are simulated to analyze the effects of the clutter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1737-1743
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• 2008

A weather radar extracts the weather information from the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. The characteristics of Doppler weather signal and ground clutter should be analyzed to extract the accurate weather information. However, the conventional symmetric weather Doppler model is somewhat inappropriate in representing various weather situations. Therefore, the improved model is suggested to describe the skewness in the Doppler spectrum model. Using the suggested model, many various weather signals can be simulated efficiently in time and spectral domain according to weather situations, operation environment and system characteristics. This simulation method may be very helpful in verifying the accuracy of the weather information extraction algorithms and developing the new system for further performance improvement.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.1-8
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• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.853-856
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• 2007

A weather radar extracts the weather information from the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. The acquisition of accurate weather information depends on the operation environment which include the Doppler weather signal and ground clutter characteristics. Since the conventional symmetric weather Doppler model does not represent the measurements in real situations, the improved model is suggested to describe the skewness in the Doppler spectrum model. Using the suggested model, many various weather signals can be simulated to verify the accuracy of signal processing algorithms and the reliability of the extracted weather information

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.22-30
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• 2023

When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.