• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.96-99
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• 2016

Generally, bistatic clutter, contrary to the monostatic clutter, has nonlinear structure in Angle-Doppler domain due to the noncooperative motion of the transmitter and the receiver. In this paper, we first simulate the bistatic clutter structure resulting from the relative motion of the transmitter and the receiver and then analyze their relations through the bistatic clutter structure in Angle-Doppler domain. Also, we show the operation condition of the transmitter and the receiver leading to low rank of a covariance matrix of the bistatic clutter.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.343-348
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• 2022

The STAP system suppresses clutter and jamming of the radar signal, but required a large number of samples for optimal performance. A large number of samples increases the signal processing computation. Therefore, there is need for a transformation method for reducing the signal rank. The LCMV beamforming method can easily set the distortion-free-constraint in the direction of arrival, and the beamforming scaling is excellent, so that overall rank can be reduced. In this study, the information of target is estimated using the proposed quadratic pattern constraints(QPC) and LCMV beamforming methods. The proposed method can perform beam pattern control in a desired direction according to the number of constraint conditions as a secondary pattern constraint condition. Through simulation, the performance of the propose method is verified. As a result on th simulation, the desired target was estimated when the proposed method had an angular resolution of 10 degrees or more, but it was not possible to accurately estimate the desired target when the angular resolution was less than 10 degrees.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.103-114
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• 2019

Moving-target detection using frequency-modulated continuous-wave (FMCW) radar systems has recently attracted attention. Detection tasks are more challenging with noise resulting from signals reflected from strong static objects or small moving objects(clutter) within radar range. Robust Principal Component Analysis (RPCA) approach for FMCW radar to detect moving objects in noisy environments is employed in this paper. In detail, compensation and calibration are first applied to raw input signals. Then, RPCA via Gradient Descents (RPCA-GD) is adopted to model the low-rank noisy background. A novel update algorithm for RPCA is proposed to reduce the computation cost. Finally, moving-targets are localized using an Automatic Multiscale-based Peak Detection (AMPD) method. All processing steps are based on a sliding window approach. The proposed scheme shows impressive results in both processing time and accuracy in comparison to other RPCA-based approaches on various experimental scenarios.