• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.690-699
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• 2014

Jet engine modulation(JEM) is a technique used to identify the jet engine type from the radar target signature modulated by periodic rotation of the jet engine mounted on the aircraft target. As a new approach of JEM, this paper proposes an automatic algorithm for extracting the jet engine information. First, the rotation period of the jet engine is yielded from auto-correlation of the JEM signal preprocessed by complex empirical mode decomposition(CEMD). Then, the final blade number is estimated by introducing the DM(Divisor-Multiplier) rule and the 'Scoring' concept into JEM spectral analysis. Application results of the simulated and measured JEM signals demonstrated that the proposed algorithm is effective in accurate and automatic extraction of the jet engine information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.101-109
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• 2021

Wave observations using a marine X-band radar are conducted by analyzing the backscattered radar signal from sea surfaces. Wave parameters are extracted using Modulation Transfer Function obtained from 3D wave number and frequency spectra which are calculated by 3D FFT of time series of sea surface images (42 images per minute). The accuracy of estimation of the significant wave height is, therefore, critically dependent on the quality of radar images. Wave observations during Typhoon Maysak and Haishen in the summer of 2020 show large errors in the estimation of the significant wave heights. It is because of the deteriorated radar images due to raindrops falling on the sea surface. This paper presents the algorithm developed to increase the accuracy of wave heights estimation from radar images by adopting convolution neural network(CNN) which automatically classify radar images into rain and non-rain cases. Then, an algorithm for deriving the Hs is proposed by creating different ANN models and selectively applying them according to the rain or non-rain cases. The developed algorithm applied to heavy rain cases during typhoons and showed critically improved results.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.6
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• pp.661-670
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• 2013

In this paper, we propose the measurement techniques of mixed waveform. Mixed waveform has phase-continuous periodic waveform with fixed frequency signal and Linear Frequency Modulation(LFM) signal. This waveform is generated from a compact radar transmitter with frequency synthesizer and high power amplifier. Frequency synthesizer generates various signal waveform with continuos phase and high power amplifier amplify transmitting signal. First, we describe a compact radar transmitter with the phase-continuos signal and then verify the distortion characteristic of pulse compression by the mismatch of LFM waveform. Second, we describe three kinds of measurement techniques for measuring LFM waveform. These techniques include methods using signal analyzer, signal source analyzer and new methods using RF mixer and phase shifter. Finally, we verify the accuracy of the measurement technique from the pulse compression result of receiving signal.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.947-952
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• 2015

To supplement energy needs and take advantage of renewable energy sources, many wind farms are currently being built in mountainous areas under the supervision of the Korean government. However, operation of these wind farms can cause serious threats to national security due to Doppler modulation from the wind turbines causing interference with military radar operating in the vicinity. Therefore it is necessary to develop methods to analyze the Doppler frequency during the operation of wind turbines and the effect on radar signals. Based on modeling of the mountainous region, blockage analysis, turbine motion and the radar signals, this paper proposes a signal processing method to extract and analyze the Doppler frequency. Simulation results showed the change of Doppler frequency over time caused by the geometry of the mountainous area and the wind turbine.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.428-435
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• 2024

In this paper, a human activity regeneration (HAR) system based on multiple input multiple output frequency modulation continuous wave (MIMO FMCW) radar was designed and implemented. Using point cloud data from MIMO radar sensors has advantages in terms of privacy, safety, and accuracy. For the implementation of the HAR system, a customized neural network based on PointPillars and depthwise separate convolutional neural network (DS-CNN) was developed. By processing high-resolution point cloud data through a lightweight network, high accuracy and efficiency were achieved. As a result, the accuracy of 98.27% and the computational complexity of 11.27M multiply-accumulates (Macs) were achieved. In addition, the developed neural network model was implemented on Raspberry-Pi embedded system and it was confirmed that point cloud data can be processed at a speed of up to 8 fps.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.85-91
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• 2016

Typically, radar systems change the pulse repetition interval of their modulated signal in order to avoid detection. On the other hand the radar-signal detection system tries to detect the modulation pattern. The histogram or auto-correlation methods are usually used to detect the PRI pattern of the radar signal. However these methods tend to lost the sequence information of the PRI pulses. This paper proposes a PRI-sequence detection algorithm based on the finite-state machine that could detect not only the PRI pattern but also their sequence.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.125-129
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• 2019

This paper describes the jamming effect of phase-coded pulse compression(PCPC) radar. Barker code radar, a typical PCPC radar, separates transmission pulses into 13 or 31 small pulses and phase modulates and transmits each pulse signal to increase radar detection efficiency and reduce the influence of jamming. Generally, when the radar is subjected to jamming, the detection distance becomes shorter and the detection error rate becomes higher. In the case of noise jamming or carrier jamming on the PCPC radar, the jamming effect is very small for no phase-coded convergence. However, the jamming effect is large in the case of synchronous jamming using the pulse-coded signal as a jamming signal with DRFM. It can be seen that the jamming effect increases when the storage time of the pulse-coded signal is prolonged. This study is considered to be useful for PCPC radar and EW jamming system design.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.243-251
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• 2019

Recently, several studies were conducted on the micro-Doppler(MD) phenomenon to identify a warhead from decoys. Both, the warhead and decoy, can be modeled as various shapes and maneuver with their own micro-motion. Their MD phenomenon can be demonstrated by amplitude modulation and phase modulation. Most studies have utilized approximate solutions to express the amplitude modulation regardless of various warhead and decoy shapes. However, the exact solution of the amplitude modulation is required for more effective warhead identification. In this study, we proposed a new modeling method of receiving radar signals from warheads and decoys based on physical optics. The proposed solution was evaluated using an electromagnetic prediction technique and computer-aided design models.