• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.2
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• pp.164-169
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• 2010

Since the range and Doppler resolution of the synthetic aperture radar(SAR) image becomes very high, the target detection accuracy can be significantly increased, but the computational burden is also increased. The conventional single-cell based CFAR detector performs the target detection on every single cell basis, thus it causes the serious increment of the computational load. In this paper, the improved two-step MCA-CFAR detector is proposed for the improvement of the target detection as well as the reduction of computational load: the first step is to use the MCA-CFAR, and the second step is to use the single-cell based CFAR detection in the expected target area for final decision. The performance of the proposed algorithm is compared with the conventional single-cell based CFAR and MCA-CFAR on SAR images.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.100-105
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• 2011

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1045-1059
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• 2011

A 3-D multi-function radar(MFR) is a modern radar to provide various target information, such as range, doppler, and angle by performing surveillance, multiple target tracking, and missile guidance. In this paper, we introduced a real-time radar signal processor(RSP), which is a crucial component of MFR with its design, implementation using high-speed multiple DSP, and performance. Additionally, we verified that several advanced signal processing algorithms were well-performed in our RSP, such as MCA-CFAR algorithm for target detection in clutter environment, range and velocity measurement algorithm using discriminator estimation, and noise jammer detection algorithm using local minimum selection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.737-747
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• 2013

A 3-D surveillance radar is a pulsed-doppler radar to provide various target information, such as range, doppler and angle by performing TWS. This paper introduces HW/SW architecture of radar signal processing board to process in real-time using high-speed multiple DSP(Digital Signal Processor) based on COTS. Moreover, we introduced a implemented algorithm consisted of clutter map creation/renewal, FIR(Finite Impulse Response) filter for rejection of zero velocity components, doppler filter, hybrid CFAR and finally presented computational burden of each algorithm by performing operational test using a beacon.