• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.120-127
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• 2019

Passive source depth discrimination has been studied for decades since the source depth can be used for discriminating whether the target is near the surface or submerged. In this thesis, an algorithm for source depth discrimination is proposed based on CIR (Channel Impulse Response) from target-radiated noise (or signal). In order to extract CIR without a known source signal, Ray-based blind deconvolution is used. Subsequently, intersections of CIR pattern, which is characterized by ray arrival time difference, is utilized for discriminating source depth. The proposed algorithm is demonstrated through numerical simulation in ocean waveguide, and verified via the experimental data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.357-358
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• 2018

The track radar use the range track loop to track the target range. The bandwidth of the radar range tracker can be determined by tradeoff according to signal to noise ratio and the target range. On the other hand, electronic warfare is carried out to prevent the radar from tracking targets by electronic attack. The deception or noise jamming in electronic warfare can be performed to interfere with the range track loop of the radar. In order to efficiently perform electronic warfare, the bandwidth in radar tracking loop is estimated and can be used for electronic attack. To do this, we have studied the method of estimating the bandwidth of radar tracking loop using the variables that can be gathered in electronic warfare.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.365-372
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• 2019

We propose a method to estimate unknown parameters(e.g., target amplitude and clutter parameters) in the generalized likelihood ratio test(GLRT) using maximum likelihood estimation and the Newton-Raphson method. When detecting targets in a clutter environ- ment, it is important to establish a modular model of clutter similar to the actual environment. These correlated clutter models can be generated using spherically invariant random vectors. We obtain the GLRT of the generated clutter model and check its detection probability using estimated parameters.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.7
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• pp.576-579
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• 2017

Due to the existence of flash lobe caused by the radome structure, a radar return in general contains clutter component added to target echo. Unlike jammer, clutter is apt to simultaneously coexist with target echo, which hinders a monopulse radar from estimating the angle difference between target echo direction and radar steering direction. In this paper, we propose a clutter estimation algorithm applicable to generalized sidelobe canceller(GSC) based monopulse radar. We show that clutter estimation can be achieved via iterative process of the orthogonal projections. Through simulations, the proposed GSC-based system combined with the clutter estimation can outperform the conventional monopulse system in terms of target angle estimation.

• Journal of Advanced Navigation Technology
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• v.24 no.1
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• pp.47-52
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• 2020

Direction of arrival (DoA) estimation is a scheme of estimating the directions of targets by analyzing signals generated or reflected from the targets and is used in various fields. Artificial neural networks (ANN) is a field of machine learning that mimics the neural network of living organisms. They show good performance in pattern recognition. Although researches has been using ANNs to estimate the DoAs, there are limitationsin dealing with variations of the signal-to-noise ratio (SNR) of the target signals. In this paper, we propose a three-stage ANN algorithm for DoA estimation. The proposed algorithm can minimize the performance reduction by applying the model trained in a single SNR environment to various environments through a 'noise reduction process'. Furthermore, the scheme reduces the difficulty in learning and maintains efficiency in estimation, by employing a process of DoA shift. We compare the performance of the proposed algorithm with Cramer-Rao bound (CRB) and the performances of existing subspace-based algorithms and show that the proposed scheme exhibits better performance than other schemes in some severe environments such as low SNR environments or situations in which targets are located very close to each other.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1200-1202
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• 2012

미래 전장에서 다수의 지상로봇들이 획득한 표적정보는 원격에 위치한 통제장치로 실시간 전송된다. 통제장치는 정찰영상과 디지털 지도위에 지상로봇들의 현재 동작 상태를 표시한다. 본 논문은 다수의 지상로봇들로부터 동일 표적에 대한 위치 정보가 수신될 경우 이에 대한 융합처리 방안을 제안한다. 이러한 융합처리를 통해 표적위치 정확도를 개선할 수 있으며, 이동 경로 추정을 통해 표적의 초기 탐지시간을 단축할 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.156-165
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• 2006

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-imbedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18$\%$ on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.61-69
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• 2018

In this paper, we propose a method for recognizing ground target using dual polarization channels in millimeter waveband air-to-surface radar. First, the Push-Broom target detection method is described and the received signal is modeled considering flight-path scenario of air-to-surface radar. The scattering centers were extracted using the RELAX algorithm, which is a time domain spectral estimation technique, and the feature vector of the target was generated. Based on this, a DB for 4 targets is constructed. As a result of the proposed method, it is confirmed that the target classification rates is improved by more than 15% than the single channel using the data of the dual polarization channel.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.387-395
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• 2019

TMA (Target Motion Analysis) in passive sonar is generally conducted with the bearing only or the bearing frequency. In order to conduct TMA fast and accurately, it is essential to estimate a initial target maneuver precisely. The accuracy of TMA can be improved by using SNR (Signal to Noise Ratio) information and acoustic propagation model additionally. This method assumes that the radiated noise level of the target is known, but the accuracy of TMA can be degraded due to a mismatch between the assumed radiated noise level and the actual radiated noise level. In this paper, TMA with the acoustic propagation model, bearing measurements, and SNR information is conducted in the ocean environment of South Korea (East Sea/ Yellow Sea/ South Sea). And the performance analysis of TMA for the mismatch in the radiated noise is presented.