2D DOA estimation for volumetric antenna array using convolutional neural network for smart antenna application (Record no. 20)

MARC details
000 -LEADER
fixed length control field 03077nas a2200361 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260817161123.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220914s2022 th uu m rtt 0| a1eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b1239175x
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Thesis no.TC-22-01
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bajracharya, Oja
245 10 - TITLE STATEMENT
Title 2D DOA estimation for volumetric antenna array using convolutional neural network for smart antenna application
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani, Thailand :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2022
300 ## - PHYSICAL DESCRIPTION
Extent 34 leaves :
Other physical details ill.
490 1# - SERIES STATEMENT
Series statement Thesis ;
Volume/sequential designation no. TC-22-01
500 ## - GENERAL NOTE
General note A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Telecommunications
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M. Eng.) - Asian Institute of Technology, 2022
520 ## - SUMMARY, ETC.
Summary, etc. Direction of Arrival (DOA) Estimation is amongst the pivotal technologies in the field of smart antenna systems. Smart antenna systems are capable of locating and tracking signals by the use of various DOA algorithms. Hence, these systems can dynamically adapt to enhance the reception of the signals in the necessary directions and minimize the effect of the interfering signals. Two-dimensional (2D) DOA estimation provides ample spatial statistics of the signals impinging in the antenna array, and has more practical significance in smart antenna applications for source localization. Since regular planar antenna arrays are unable to meet the requirements for the quick and precise localization of mobile sources, the concept of volumetric antenna arrays has been introduced. However, there have been limited research done on DOA estimation of these volumetric antenna arrays. A novel approach to 2D DOA estimation of a volumetric antenna array using Convolutional Neural Network (CNN) is proposed in this study. The 2D DOA prediction network takes the covariance matrices of the various angle pairs as its input. These matrices are computed from the volumetric extension of the planar array which is preprocessed for better feature extraction. In addition, the signals simulated undergo multipath fading during its generation, to closely resemble a real-world signal. Finally, the CNN outputs the predicted angle pairs for a given number of test samples of angle pair covariance matrices.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Neural networks (Computer science)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Antenna arrays
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Attaphongse Taparugssanagorn,
Relator term Chairperson
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Teerapat Sanguankotchakorn,
Relator term Examination Committee
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Mongkol Ekpanyapong,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology Scholarships,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Thesis ;
Volume/sequential designation no. TC-22-01
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B17272">http://203.159.5.9/ait-thesis/detail.php?q=B17272</a>
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b1239175x
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902 ## - LOCAL DATA ELEMENT B, LDB (RLIN)
a 240419
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Operator's initials, OID (RLIN) 0
Cataloger's initials, CIN (RLIN) 220914
First date, FD (RLIN) m
-- b
-- m
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945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnarc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 40-Archives
909 ## - LOCAL ITEMS USED
Barcode Barcode : 30020220005659
CREATED CREATED : 2022-09-13
RECORD Id RECORD # : i1339910x
LPATRON LPATRON : 0
LCHKIN LCHKIN : -
RENEWALS # RENEWALS : 0
-- # OVERDUE : 0
-- IUSE3 : 0
-- TOT CHKOUT : 0
-- TOT RENEW : 0
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 17/08/2026   AIT Thesis no.TC-22-01 30020220005659 17/08/2026 1 17/08/2026 40-Archives
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