• ETRI Journal
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• 제43권1호
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• pp.120-132
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• 2021

A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

• 한국컴퓨터정보학회논문지
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• 제12권2호
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• pp.83-91
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• 2007

본 논문에서는 삼차원 볼륨이미지로부터 정육면체형 셀의 분해를 통해 위상학적으로 정확한 삼중선형 등위면을 계산하고 가시화하는 알고리즘을 제시하였다. 등위면은 삼차원 볼륨이미지를 가시화하는데 자주 사용되며, 볼륨데이타의 각 정육면체형 셀안의 등위면을 삼각형의 집합으로 나타냄으로써 컴퓨터에서 가시화하기 쉽게 된다. 그러나, 대부분의 기존 등위면 계산 방식들은 이상적인 형태인 삼중선형 등위면의 위상을 보존하지 못하여 정확성이 떨어지는 단점을 가지고 있다. 본 논문은 삼차원 볼륨이미지를 구성하는 정육면체형 셀에서 일어날 수 있는 모든 등위면 형태에 대하여 정확한 삼중선형 등위면의 위상을 결정하고, 각 경우에 따라 적절한 정육면체 셀의 분해를 실시한 뒤, 분해된 셀들에 대하여 등위면을 나타내는 삼각형들을 추출하여, 위상학적으로 정확한 삼중선형 등위면을 만들어낸다. 마지막으로, 본 논문에서 제안된 알고리즘을 구현한 결과는 정확한 삼중선형을 가시화할 수 있음을 보여준다.

• ETRI Journal
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• 제45권1호
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• pp.138-149
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• 2023

In this study, the problem of blind signal separation for coprime planar arrays is investigated. For coprime planar arrays comprising two uniform rectangular subarrays, we link the signal separation to the tensor-based model called coupled canonical polyadic decomposition (CPD) and propose an improved coupled trilinear decomposition approach. The output data of coprime planar arrays are modeled as a coupled tensor set that can be further interpreted as a coupled CPD model, allowing a signal separation to be achieved using coupled trilinear alternating least squares (TALS). Furthermore, in the procedure of the coupled TALS, a Vandermonde structure enforcing approach is explicitly applied, which is shown to ensure fast convergence. The results of Monto Carlo simulations show that our proposed algorithm has the same separation accuracy as the basic coupled TALS but with a faster convergence speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권6호
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• pp.667-681
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• 2009

We describe a method to decompose a cube with trilinear interpolation into a collection of tetrahedra with linear interpolation, where the isosurface topology is preserved for all isovalues during decomposition. Visualization algorithms that require input scalar data to be defined on a tetrahedral grid can utilize our method to process 3D rectilinear data with topological correctness. As one of many possible examples, we apply the decomposition method to topologically accurate tetrahedral mesh extraction of an interval volume from trilinear volumetric imaging data. The topological correctness of the resulting mesh can be critical for accurate simulation and visualization.

• Journal of the Optical Society of Korea
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• 제20권1호
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• pp.204-211
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• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.