• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.210-217
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• 2003

We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.996-1003
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• 2016

Trilateration technique using time of arrival(TOA) is generally used for single target position estimation in radar system. However, trilateration technique has limitation in case of multiple targets, since it is difficult to distinguish the measurements corresponding to the respective targets. In this study, to eliminate ambiguity of relation between measurements and targets, micromotion of each target is measured by micro Doppler which is actively studied in radar industry nowadays and these information are used to distinguish measurements used at trilateration technique. Resultingly, the trilateration technique is applied successfully for each target. The targets are considered as multiple submissiles separated from the missile. Simulation results shows the performance of the proposed algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.137-142
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• 2013

Direction of arrival is estimating for desire signal direction among received signal on antenna in spatial. In this paper, we were an estimation a receiving signal direction of arrival using multi beam forming in radar. We proposed, by signal direction of arrival estimation method, an algorithm which combine spatial correlation matrix weight value and beam steering algorithm in this paper. Through simulation, we were analysis a performance to compare general algorithm and proposal algorithm. In direction of arrival estimation, proposed algorithm is effectivity to decrease processing time because it is not doing an eigen decomposition. We showed that proposal algorithm improve more target estimation than general algorithm.

• Smart Media Journal
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• v.4 no.1
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• pp.16-24
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• 2015

In this paper, we propose a method for multi-touch tracking using MRF-based particle filters and gesture likelihood estimation Each touch (of one finger) is considered to be one object. One of frequently occurring issues is the hijacking problem which means that an object tracker can be hijacked by neighboring object. If a predicted particle is close to an adjacent object then the particle's weight should be lowered by analysing the influence of neighboring objects for avoiding hijacking problem. We define a penalty function to lower the weights of those particles. MRF is a graph representation where a node is the location of a target object and an edge describes the adjacent relation of target object. It is easy to utilize MRF as data structure of adjacent objects. Moreover, since MRF graph representation is helpful to analyze multi-touch gestures, we describe how to define gesture likelihoods based on MRF. The experimental results show that the proposed method can avoid the occurrence of hijacking problems and is able to estimate gesture likelihoods with high accuracy.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.39-49
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• 2002

This paper presents a robust tracker design method that is specific to the trajectories of target aircraft. This method assumes that representative trajectories of the target aircraft are available. The exact trajectories known to the tracker enables the incorporation of the exact data in the tracker design instead of the measurement data. An estimator is designed to have acceptable performance in tracking a finite number of different target trajectories with a capability to trade off the mean and maximum errors between the exact trajectories and the estimated or predicted trajectories. Constant estimator gains that minimize the cost functions related to the estimation or prediction error are computed off-line from an iterative algorithm. This tracker design method is applied to the longitudinal motion tracking of target aircraft.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.435-449
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• 2020

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.445-450
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• 2018

Reliable detection and parameter estimation of a radar cross section(RCS) fluctuating target have been known as a difficult task. To reduce the effect of RCS fluctuation, various diversity techniques have been considered. This paper presents a new method for synthesizing a covariance matrix applicable to a coherent multi-input multi-output(MIMO) radar with frequency diversity. It is achieved by efficiently combining covariance matrices corresponding to different carrier frequencies such that the signal-to-noise ratio(SNR) in the combined covariance matrix is maximized. The value of a synthesized covariance matrix is assessed by examining the phase curves of its entries and the improvement on direction of arrival(DOA) estimation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.1-6
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• 2009

Due to the different camera properties of the multi-view camera system, the color properties of captured images can be inconsistent. This inconsistency makes post-processing such as depth estimation, view synthesis and compression difficult. In this paper, the method to correct the different color properties of multi-view images is proposed. We utilize a gray gradient bar on a display device to extract the color sensitivity property of the camera and calculate a look-up table based on the sensitivity property. The colors in the target image are converted by mapping technique referring to the look-up table. Proposed algorithm shows the good subjective results and reduces the mean absolute error among the color values of multi-view images by 72% on average in experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.99-110
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• 2017

Improving tracking performance by estimating the status of multiple targets using radar is important. In a clutter environment, a joint event occurs between the track and measurement in multiple target tracking using a tracking filter. As the number increases, the joint event increases exponentially. The problem to be considered when multiple target tracking filter design in such environments is that first, the tracking filter minimizes the rate of false track alarmsby eliminating the false track and quickly confirming the target track. The purpose is to increase the FTD performance. The second consideration is to improve the track maintenance performance by allocating each measurement to a track efficiently when an event occurs. Through two considerations, a single target tracking data association technique is extended to a multiple target tracking filter, and representative algorithms are JIPDAF and LM-IPDAF. In this study, a probabilistic evaluation of many hypotheses in the assignment of measurements was not performed, so that the computation amount does not increase nonlinearly according to the number of measurements and tracks, and the track existence probability based on the track density The LM-IPDAF algorithm was introduced. This paper also proposes a method to reduce the computational complexity by improving the clutter density estimation method for calculating the track existence probability of LM-IPDAF. The performance was verified by a comparison with the existing algorithm through simulation. As a result, it was possible to reduce the simulation processing time by approximately 20% while achieving equivalent performance on the position RMSE and Confirmed True Track.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.35-41
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• 2018

Electrical impedance tomography (EIT) is a kind of nondestructive testing technique that obtains the internal resistivity distribution from the voltages measured at the electrodes located outside the area of interest. However, an image reconstruction problem in EIT has innate non-linearity and ill-posedness, so that it is difficult to obtain satisfactory reconstructed results. In general, a neural network can efficiently model the input and output relationships of a non-linear system. This paper proposes a method for estimating the position and size of a circular target using a multi-layer neural network. To verify the performance of the proposed method, neural network was trained and various computer simulations were performed and satisfactory performance was verified.