• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1077-1083
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• 2009

To reject the Doppler frequency spectrum dispersion of clutter caused by high-speed antenna rotation of MTI radar system due to terrain characteristics, signal processing parameters(MTI filter constant, M/N detector ration, K-factor and offset of CFAR) are adjusted for the optimal elimination of the ground clutter. For this investigation, logging equipment is designed and utilized for the collection of classified ground clutter data. Test case is devised through Matlab simulation for the classified analysis and optimization of clutter rejection. Then indoor radar test and outside test in accordance with terrain characteristics are repeatedly performed for the verification of the test. This whole process is through the evolutional development model and repeated for the optimization. Final result is that ground-clutter rejection capability is 5.6 times(7.5 dB) better than that of existing radar system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.187-193
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• 2021

In order to solve the problem of false terrains caused by environmental interferences and tunneling effect in the conventional multi-beam seafloor terrain detection, this paper proposed a seafloor topography detection method based on fast two-dimensional (2D) Censored Mean Level Detector-statistics Constant False Alarm Rate (CMLD-CFAR) method. The proposed method uses s cross-sliding window. The target occlusion phenomenon that occurs in multi-target environments can be eliminated by censoring some of the large cells of the reference cells, while the remaining reference cells are used to calculate the local threshold. The conventional 2D CMLD-CFAR methods need to estimate the background clutter power level for every pixel, thus increasing the computational burden significantly. In order to overcome this limitation, the proposed method uses a fast algorithm to select the Regions of Interest (ROI) based on a global threshold, while the rest pixels are distinguished as clutter directly. The proposed method is verified by experiments with real multi-beam data. The results show that the proposed method can effectively solve the problem of false terrain in a multi-beam terrain survey and achieve a high detection accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1292-1299
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• 2014

Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.3 no.2
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• pp.66-78
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• 1992

Available data for the radar clutter, and the empirical and the theoretical models for the radar clutter have been collected and analyzed. Data sets and models from the remote sensing field have been studied extensively. Although the grazing angles used in remote sensing is larger than the angles normally encountered in radar clutter application, remote sensing field has the merit of abundance of data in much more detailed target classes. The remote sensing model is also superior to the normally used clutter models in the sense that each target class has its own model, rather than being generally characterized by assumed roughness parameters.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.275-282
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• 2019

Clusters generated by features such as mountains or buildings are considered as the contaminated data that are independent of atmospheric phenomena. The basic way to reduce the clutter signal is to install a clutter fence around the wind profiler. In order to investigate the effect of clutter fence on the wind profiler data, the wind vector collection rate and wind vector accuracy of wind profiler was investigated before and after clutter fence installation. The clutter fence of wind profiler contributed to improve the data quality as well as the data collection rate.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.389-398
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• 2019

In this paper, we propose a method to detect small unmanned aerial vehicles(UAVs) flying in a real-world environment. Small UAV signals are frequently obscured by clutter signals because UAVs usually fly at low altitudes over urban or mountainous terrain. Therefore, to obtain a desirable detection performance, clutter signals must be considered in addition to noise, and thus, a performance analysis of each clutter removal technique is required. The proposed detection process uses clutter removal and pulse integration methods to suppress clutter and noise signals, and then detects small UAVs by utilizing a constant false alarm rate detector. After applying three clutter removal techniques, we analyzed the performance of each technique in detecting small UAVs. Based on experimental data acquired in a real-world outdoor environment, we found it was possible to derive a clutter removal method suitable for the detection of small UAVs.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.181-188
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• 2022

An intelligent distributed multi-agent system (IDMS) using reinforcement learning (RL) is a challenging and intricate problem in which single or multiple agent(s) aim to achieve their specific goals (sub-goal and final goal), where they move their states in a complex and cluttered environment. The environment provided by the IDMS provides a cumulative optimal reward for each action based on the policy of the learning process. Most actions involve interacting with a given IDMS environment; therefore, it can provide the following elements: a starting agent state, multiple obstacles, agent goals, and a cluttered index. The reward in the environment is also reflected by RL-based agents, in which agents can move randomly or intelligently to reach their respective goals, to improve the agent learning performance. We extend different cases of intelligent multi-agent systems from our previous works: (a) a proposed environment-clutter-based-index for agent sub-goal selection and analysis of its effect, and (b) a newly proposed RL reward scheme based on the environmental clutter-index to identify and analyze the prerequisites and conditions for improving the overall system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.5
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• pp.373-381
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• 2017

DBS(Doppler Beam Sharpening) algorithm is a way to improve azimuth resolution performance in radar. Since DBS image includes the is information about the search area of radar, various clutter components exist besides the target to be detected. To detect and track the desired target in a DBS image, it must be able to identify a target and the clutter components. In this paper, we describe how to use image size and terrain information(DTED) to identify the target in a DBS image. By using morphological filter and chain code, it acquires image size and excludes the clutter components. By matching with DTED, we determine target.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1797-1801
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• 2004

In this paper we show the hardware testbed and software simulator of multi function array radar (MFAR). The hardware MFAR is simple and flexible hardware to implement various radar beamforming and detecting algorithms. To overcome the limitation of hardware MFAR, the software simulator is proposed. User can simulate radar under the various environment conditions adjusting the parameter of simulator. User can set environment of radar, such as the location and velocity of target, jammer and the terrain clutter. The radar use various probing pulses and supports two operation mode, surveillance and tracking mode.