Browsing by Author "Tsai, Tsung-Yu"

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A Blind Statistical Approach for Optimal Receive Beam Steering in Multipath Environments
(2012)
Tsai, Tsung-Yu
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Ko, Ta
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Lin, You-Hsien
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Tsai, Zsehong
;
Hsu, Terng-Yin
A novel blind statistical algorithm for obtaining the optimal receive beam vector with maximum time-domain effective SNR in OFDMA systems under multipath environment is proposed. The basic procedure of the proposed approach is obtained via the coarse cyclic prefix (CP) detection first and the sample average of the correlation matrices is calculated from selected signal samples for later singular value decomposition (SVD) on the averaged correlation matrix. The proposed approach has the following advantages: First, it is accurate even in the presence of high noise power and when the process of the OFDMA sampled signals are not white (i.e. not all subcarriers are allocated for data transmission). Secondly, it can be operated in time-domain with no training signals and no pre-assumption of the antenna array structure. Hence, it could be applied directly to a variety of existing OFDMA systems and its design can be made relatively simple for implementation. Theoretical proofs of its optimality and the guarantee of convergence are also provided in this paper. Finally, simulation results verifies the theoretical analysis and shows that the proposed approach can accurately achieve a near optimal SNR gain even in low SNR environment and has a convergence speed within two OFDM symbols.
A closed-form phase-comparison ML DOA estimator for automotive radar with one single snapshot
(2013)
Huang, Chung-Jung
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Dai, Chia-Wei
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Tsai, Tsung-Yu
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Chung, Wei-Ho
;
Lee, Ta-Sung
In automotive radar systems, only a small number of snapshots are available for direction-of-arrival (DOA) estimation in high mobility scenarios. We here propose a closed-form single-snapshot maximum likelihood (ML) DOA estimator based on the phase-comparison technique. The estimator can be effective in a wide field-of-view (FOV) scenario and is robust to gain-mismatch effects among antenna elements. Computer simulations are conducted to confirm the effectiveness of the proposed method.
ANIMATING PICTURES USING PROCEDURAL 2.5D WATER FLOW SIMULATION
(2017-01-01)
Sun, Tsai-Ho
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Tseng, Yi-Chun
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Wong, Sai-Keung
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Chen, Hsuan
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Tsai, Tsung-Yu
In this paper, we present a procedural 2.5D water flow simulation technique to animate pictures. For a given picture, we convert it into a 2.5D structure and then perform water simulation for the 2.5D structure (like a shallow-relief sculpture). The proposed approach is divided into three phases: image processing, water simulation and rendering. First, we extract the objects in the picture and compute their 2.5D structure based on image processing techniques. Second, a procedural based approach is adopted to simulate water flows over the 2.5D structure. Finally, we apply a simple ray tracer to render final images. Experimental results show that the simulated water flows naturally over the 2.5D structure of the pictures at real time rates. We also printed out the 2.5D structures of the virtual objects as 3D models for visual comparison.
Directing virtual crowds based on dynamic adjustment of navigation fields
(2018-01-01)
Tsai, Tsung-Yu
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Wong, Sai-Keung
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Chou, Yi-Hung
;
Lin, Guan-Wen
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Navigation fields are a popular data structure for directing the movement of virtual crowds. However, the congestion problem may occur at the corners of objects in using a navigation field because the agents move quite closely to each other. The agents may congest at the corners even though there is room for the agents to move away from the congested regions. In this paper, we propose to place crowd monitors at the corners to collect the data such as the movement direction of crowds and crowd densities. Then the navigation field is adjusted dynamically so that the crowds are led to move away from the congested regions. We also propose a simple data structure for speeding up the collision detection process between agents and objects. Experimental results show that our approach successfully alleviates the congestion problem at the corners.
Low-Complexity Beam Steering Algorithm Based on Binary Search Strategy for Receive Beamform
(2012)
Lin, You-Hsien
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Tsai, Tsung-Yu
;
Chen, Ying-Liang
;
Ko, Ta
;
Chien, Chun-Che
The complexity of beamforming, such as complexity complex weighting and combining process, are extremely important for implementation. This work presents a low complexity time-domain statistic noise suppression and beam steering algorithm based on binary search strategy to estimate the optimal beam vector at the receivers. The beam steering algorithm based on binary search strategy could achieve closely (about 99%) optimal SNR gain within only two binary search. It is desirable choice to archive the suitable trade-off between the performance and the processing overhead. Hence, it could obtain a near-optimal performance with considerably low complexity and high convergence speed. In addition, this algorithm is well-matched to different specifications.