• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.39-44
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• 2010

A method is presented of dynamic determination of mode transition probability for IMM in order to improve the accuracy performance of maneuvering target tracking for air traffic control surveillance processing system under multiple radar environment. It is shown that dynamic determination of mode transition probability based on the time intervals between the data input from multiple radars gives the optimized performance in terms of position estimation accuracy.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.955-958
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• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1284-1291
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• 2014

For detection and parameter estimation, a multicarrier radar should discriminate a channel containing jamming signal and either leave it out or regenerate jammer suppressed target signal. To discriminate jamming channels, we use the angular spectrum of an eigenvector that embeds target echoes and jamming signals. We propose a criteria to discriminate the jammer channels and its basis through mathematical analysis. Moreover, we show some procedures to regenerate the jammer suppressed target echoes. Finally, the validity of the proposed method is demonstrated through simulation results showing improved performance in terms of direction of arrival(DOA) estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.782-791
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots. In order to match up targets with measured azimuths, we apply the maximum likelihood (ML), depth-first, and breadth-first tree search algorithms, in which we use the measured azimuths and the number of pixels on IR screen for pruning branches and selecting candidates. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the probability of missing target, mean of the number of calculating nodes, and mean error of the estimated coordinates of the proposed algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1207-1215
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• 2013

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.1-7
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• 2010

In this paper, we use the maximum-likelihood detection by the estimation of trellis targets on the 16-level cell NAND flash memory. This mechanism has a performance gain by using a maximum-likelihood detector. The NAND flash memory channel is a memory channel because of the coupling effect. Thus, we use the known data arrays to finding the targets of trellis. The maximum-likelihood detection by proposed scheme performs better than the threshold detection on the 16-level cell NAND flash memory channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.2
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• pp.146-153
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• 2013

The IR-UWB radar system radiates a pulse whose width is several hundred pico sec at Tx antenna and check the time to receive the pulse that reflected from target to measure the TOA. In this paper, we present a new algorithm which supplement the conventional ranging algorithm for more accurate estimation. We get received signal data using IR-UWB Radar module which equipped a NVA6000 UWB Transceiver and analysis the data of multi-path. Consequently, we found the property of UWB multi-path signal, which best fit a Gamma distribution. so we present a algorithm using Gamma-distribution and compared a performance with conventional ranging algorithm.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.177-183
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• 2008

The sub-salt imaging technique becomes more crucial to detect the hydro-carbonates in petroleum exploration as the target reservoirs get deeper. However, the weak reflections from the sub-salt structures prevent us from obtaining high fidelity sub-salt image. As an effort to overcome this difficulty, we applied the waveform inversion by implementing multi-grid technique to the sub-salt imaging. Through the comparison between the conventional waveform inversion using fixed grid and the multi-grid technique, we confirmed that the waveform inversion using multi-grid technique has advantages over the conventional fixed grid waveform inversion. We showed that the multi-grid technique can complement he velocity estimation result of the waveform inversion for imaging the sub-salt structures, of which velocity model cannot be obtained correctly by the conventional fixed grid waveform inversion.

• 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.