The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam makalah ini, kami membentangkan algoritma penyesuaian yang rendah dengan kerumitan yang rendah namun tepat untuk penjejakan arah ketibaan (DOA) dua dimensi (2-D) berdasarkan tatasusunan segi empat tepat seragam (URA). Algoritma baharu ialah gabungan baharu proses penjejakan dan pembentukan pancaran dengan menggunakan tiga peringkat algoritma penjejakan DOA satu dimensi (1-D) -- dalam struktur pokok hierarki -- untuk menentukan dua komponen DOA secara berulang dalam bentuk kasar- cara yang baik. Di antara setiap algoritma penjejakan DOA 1-D yang lain, proses pembentukan pancaran ortogonal pelengkap digunakan untuk membahagikan isyarat masuk ke dalam kumpulan yang sesuai untuk meningkatkan ketepatan penjejakan. Memandangkan algoritma baharu hanya melibatkan algoritma penjejakan DOA berasaskan subruang 1-D, kerumitan keseluruhan adalah jauh lebih kecil daripada lanjutan dua dimensi (2-D) langsung bagi algoritma penjejakan DOA 1-D sedia ada, yang memerlukan kemas kini vektor dimensi lebih tinggi diikuti oleh penguraian eigen dimensi lebih tinggi atau carian 2-D. Tambahan pula, dengan skema penjejakan DOA berstruktur pokok, komponen DOA 2-D yang dijejaki dipasangkan secara automatik tanpa overhed pengiraan tambahan. Simulasi lengkap menunjukkan bahawa algoritma baharu boleh memberikan prestasi penjejakan yang memuaskan dalam pelbagai senario.
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Salinan
Kuo-Hsiung WU, Wen-Hsien FANG, "A Low Complexity Adaptive Algorithm for Eigenspace-Based Two-Dimensional Direction of Arrival Tracking" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 8, pp. 2097-2106, August 2009, doi: 10.1587/transfun.E92.A.2097.
Abstract: In this paper, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms -- in a hierarchical tree structure -- to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspace-based DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search. Furthermore, with the tree-structured DOA tracking scheme, the tracked 2-D DOA components are automatically paired without extra computational overhead. Furnished simulations show that the new algorithm can provide satisfactory tracking performance in various scenarios.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.2097/_p
Salinan
@ARTICLE{e92-a_8_2097,
author={Kuo-Hsiung WU, Wen-Hsien FANG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Low Complexity Adaptive Algorithm for Eigenspace-Based Two-Dimensional Direction of Arrival Tracking},
year={2009},
volume={E92-A},
number={8},
pages={2097-2106},
abstract={In this paper, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms -- in a hierarchical tree structure -- to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspace-based DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search. Furthermore, with the tree-structured DOA tracking scheme, the tracked 2-D DOA components are automatically paired without extra computational overhead. Furnished simulations show that the new algorithm can provide satisfactory tracking performance in various scenarios.},
keywords={},
doi={10.1587/transfun.E92.A.2097},
ISSN={1745-1337},
month={August},}
Salinan
TY - JOUR
TI - A Low Complexity Adaptive Algorithm for Eigenspace-Based Two-Dimensional Direction of Arrival Tracking
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2097
EP - 2106
AU - Kuo-Hsiung WU
AU - Wen-Hsien FANG
PY - 2009
DO - 10.1587/transfun.E92.A.2097
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2009
AB - In this paper, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms -- in a hierarchical tree structure -- to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspace-based DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search. Furthermore, with the tree-structured DOA tracking scheme, the tracked 2-D DOA components are automatically paired without extra computational overhead. Furnished simulations show that the new algorithm can provide satisfactory tracking performance in various scenarios.
ER -