• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.111-125
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• 2015

In this study, the target detection using both high-resolution satellite SAR and Elecro-Optical (EO) images such as TerraSAR-X and WorldView-2 is performed, considering the characteristics of targets. The targets of our interest are featured by being stationary and appearing as cluster targets. After the target detection of SAR image by using Constant False Alarm Rate (CFAR) algorithm, a series of processes is performed in order to reduce false alarms, including pixel clustering, network clustering and coherence analysis. We extend further our algorithm by adopting the fast and effective ellipse detection in EO image using randomized hough transform, which is significantly reducing the number of false alarms. The performance of proposed algorithm has been tested and analyzed on TerraSAR-X SAR and WordView-2 EO images. As a result, the average false alarm for group of targets is 1.8 groups/$64km^2$ and the false alarms of single target range from 0.03 to 0.3 targets/$km^2$. The results show that groups of targets are successfully identified with very low false alarms.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• 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.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.3-9
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• 1999

In this paper, the characteristics of LFM and CW signals in active sonar environment is investigated. CA, OS and TM CFAR processors are applied to the received CW/LFM signals which are plotted in the range/doppler domain. The performances of detection are analyzed. Particularly, using the real data, we certified that the results of the experiments are identical with the theoretical performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.4
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• pp.482-490
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• 2017

The radar signal processing procedure is divided into the pre-processing such as frequency down converting, down sampling, pulse compression, and etc, and the post-processing such as doppler filtering, extracting target information, detecting, tracking, and etc. The former is generally designed using FPGA because the procedure is relatively simple even though there are large amounts of ADC data to organize very quickly. On the other hand, in general, the latter is parallel processed by multiple DSPs because of complexity, flexibility and real-time processing. This paper presents the radar signal processor design using FPGA which includes not only the pre-processing but also the post-processing such as doppler filtering, bore-sight error, NCI(Non-Coherent Integration), CFAR(Constant False Alarm Rate) and etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.28-42
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• 2013

Personal Rapid Transit(PRT) is a new unmanned transportation system using electricity. The purpose of the PRT is relieving the congestion of city traffic and connecting between inner city and airport, high-speed railroad. PRT requires to develop devices for the guarantee of safety and reliability. PRT as the mean of rail transportation must be equipped with control system for front rail sensing. Ultra Wide Band(UWB) radar system is suitable for PRT's detection because it has the advantage of low power consumption, low interference and high resolution. In this paper, an improved adaptive Constant False Alarm Rate(CFAR) algorithm is proposed and studied in various noise environments. The proposed algorithm improves performance in various noise environments compared to the Mean Level CFAR algorithms and other adaptive CFAR algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.791-798
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• 2018

The CFAR algorithm is mainly used for target detection in radar systems. In particular, OS CFAR is used in a non-uniform noise environment. However, it requires a large amount of computation, because it should sort reference cells in ascending order. This makes it difficult to apply the radar system in real time. In this paper, we describe how to reduce the computational burden of OS CFAR. We compared the power of the test cell and reference cell to determine only the presence or absence of target detection. The common reference cells overlapping in the reference cells of the three test cells are obtained. We first compare the test cell with the highest power value among the three test cells to the common reference cells. Next, we compare each test cell to general reference cells, excluding the common reference cells. The computation time is shortened by reducing the power comparison computation amounts.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.96-107
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• 1999

The generalized sidelobe cancellers(GSC's) ar used for suppressing an interference in array radar. The frequency-domain GSC's have a faster convergence rate than the time-domain GSC's because they remove the correlation between the interferences using a frequency-domain least mean square(LMS) algorithm. However, we have not fully used the advantage of the frequency-domain GSC's since we have always updated the weights of all frequency bins, even the interferer free frequency bin. In this paper, we propose a new frequency-domain GSC based on constant false-alarm rate(CFAR) detector, of which GSC adaptively determine the bin whose weight is updated according to the power of each frequency bin. This canceller updates the weight of only updated according to the power of each frequency bin. This canceller updates the weight of only the bin of which the power is high because of the interference signal. The computer simulation shows that the new GSC reduces the iteration number for convergence over the conventional GSC's by more than 100 iterations. The signal-to-noise ration(SNR) improvement is more than 5 dB. Moreover, the number of renewal weights required for the adaptation is much fewer than that of the conventional one.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.27-31
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• 2010

Recently, spectrum requirements are rapidly increasing in accordance with wireless communication development. For this reason, FCC(Federal communications commission) is considering cognitive radio system to increase spectral efficiency. In this paper, we present the performance analysis of signal detection by using RS(Reference signal) for LTE environments. Especially, we analyze the performance of detection probability in case of downlink LTE system. In the simulation, we generate OFDMA signal format which is specified in the LTE system. We assume additive white Gausssian noise channel environment. We estimate the performance by setting the threshold value of 5 % and 10 % based on CFAR(Constant false alarm rate) and false alarm rate, respectively. Finally, we discuss a future study plan on the applicability of CR to the LTE system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.347-357
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• 2003

This paper describes on the suppression of sea clutter on marine radar display using a cell-averaging CFAR(constant false alarm rate) technique, and on the analysis of radar echo signal data in relation to the estimation of ARPA functions and the detection of the shadow effect in clutter returns. The echo signal was measured using a X -band radar, that is located on the Pukyong National University, with a horizontal beamwidth of $$3.9^{\circ}$$, a vertical beamwidth of $20^{\circ}$, pulsewidth of $0.8 {\mu}s$ and a transmitted peak power of 4 ㎾ The suppression performance of sea clutter was investigated for the probability of false alarm between $l0-^0.25;and; 10^-1.0$. Also the performance of cell averaging CFAR was compared with that of ideal fixed threshold. The motion vectors and trajectory of ships was extracted and the shadow effect in clutter returns was analyzed. The results obtained are summarized as follows；1. The ARPA plotting results and motion vectors for acquired targets extracted by analyzing the echo signal data were displayed on the PC based radar system and the continuous trajectory of ships was tracked in real time. 2. To suppress the sea clutter under noisy environment, a cell averaging CFAR processor having total CFAR window of 47 samples(20+20 reference cells, 3+3 guard cells and the cell under test) was designed. On a particular data set acquired at Suyong Man, Busan, Korea, when the probability of false alarm applied to the designed cell averaging CFAR processor was 10$^{-0}$.75/ the suppression performance of radar clutter was significantly improved. The results obtained suggest that the designed cell averaging CFAR processor was very effective in uniform clutter environments. 3. It is concluded that the cell averaging CF AR may be able to give a considerable improvement in suppression performance of uniform sea clutter compared to the ideal fixed threshold. 4. The effective height of target, that was estimated by analyzing the shadow effect in clutter returns for a number of range bins behind the target as seen from the radar antenna, was approximately 1.2 m and the information for this height can be used to extract the shape parameter of tracked target..