Doctoral Dissertations
Abstract
“A common approach to the wide-band microphone array problem is to assume a certain array geometry and then design optimal weights (often in subbands) to meet a set of desired criteria. In addition to weights, we consider the geometry of the microphone arrangement to be part of the optimization problem. Our approach is to use particle swarm optimization (PSO) to search for the optimal geometry while using an optimal weight design to design the weights for each particle’s geometry. The resulting directivity indices (DI’s) and white noise SNR gains (WNG’s) form the basis of the PSO’s fitness function. Another important consideration in the optimal weight design are several regularization parameters. By including those parameters in the particles, we optimize their values as well in the operation of the PSO. The proposed method allows the user great flexibility in specifying desired DI’s and WNG’s over frequency by virtue of the PSO fitness function.
Although the above method discusses beam and nulls steering for fixed locations, in real time scenarios, it requires us to estimate the source positions to steer the beam position adaptively. We also investigate source localization of sound and RF sources using machine learning techniques. As for the RF source localization, we consider radio frequency identification (RFID) antenna tags. Using a planar RFID antenna array with beam steering capability and using received signal strength indicator (RSSI) value captured for each beam position, the position of each RFID antenna tag is estimated. The proposed approach is also shown to perform well under various challenging scenarios”--Abstract, page iv.
Advisor(s)
Zawodniok, Maciej Jan, 1975-
Committee Member(s)
Kosbar, Kurt Louis
Stanley, R. Joe
Zhang, Jiangfan
Nadendla, V. Sriram Siddhardh
Department(s)
Electrical and Computer Engineering
Degree Name
Ph. D. in Electrical Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Spring 2022
Journal article titles appearing in thesis/dissertation
- On the design of optimal linear microphone array geometries
- On the design of optimal 2D microphone array geometries
- Passive RFID tags for metallic environments using phased array reader antennas
- DNN-based RFID antenna tags localization
- 3D localization of RFID antenna tags using convolutional neural networks
Pagination
xiv, 127 pages
Note about bibliography
Includes bibliographic references.
Rights
© 2022 Sohel Jayesh Patel, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Thesis Number
T 12129
Recommended Citation
Patel, Sohel J., "Array signal processing for source localization and enhancement" (2022). Doctoral Dissertations. 3159.
https://scholarsmine.mst.edu/doctoral_dissertations/3159