Doctoral Dissertations
Keywords and Phrases
3-D radar imaging; Adaptive turbo equalization; Compressed sensing (CS); Sparse nonlinear optimization; Underwater acoustic (UWA) communications
Abstract
"This dissertation proposes three classes of new sparse nonlinear optimization algorithms for network echo cancellation (NEC), 3-D synthetic aperture radar (SAR) image reconstruction, and adaptive turbo equalization in multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications, respectively.
For NEC, the proposed two proportionate affine projection sign algorithms (APSAs) utilize the sparse nature of the network impulse response (NIR). Benefiting from the characteristics of l₁-norm optimization, affine projection, and proportionate matrix, the new algorithms are more robust to impulsive interferences and colored input than the conventional adaptive algorithms.
For 3-D SAR image reconstruction, the proposed two compressed sensing (CS) approaches exploit the sparse nature of the SAR holographic image. Combining CS with the range migration algorithms (RMAs), these approaches can decrease the load of data acquisition while recovering satisfactory 3-D SAR image through l₁-norm optimization.
For MIMO UWA communications, a robust iterative channel estimation based minimum mean-square-error (MMSE) turbo equalizer is proposed for large MIMO detection. The MIMO channel estimation is performed jointly with the MMSE equalizer and the maximum a posteriori probability (MAP) decoder. The proposed MIMO detection scheme has been tested by experimental data and proved to be robust against tough MIMO channels."--Abstract, page iv.
Advisor(s)
Zheng, Y. Rosa
Committee Member(s)
Xiao, Chengshan
Zoughi, R.
Grant, Steven L.
Hosder, Serhat
Department(s)
Electrical and Computer Engineering
Degree Name
Ph. D. in Electrical Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Spring 2014
Journal article titles appearing in thesis/dissertation
- Proportionate affine projection sign algorithm for network echo cancellation
- A comparative study of compressed sensing for 3-D synthetic aperture radar image reconstruction
- Robust adaptive channel estimation in MIMO underwater acoustic communications
Pagination
xi, 105 pages
Note about bibliography
Includes bibliographical references.
Rights
© 2014 Zengli Yang, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Subject Headings
Signal processing -- Digital techniquesUnderwater acoustic telemetryAdaptive filtersWireless communication systemsAdaptive control systems
Thesis Number
T 10494
Electronic OCLC #
882557726
Recommended Citation
Yang, Zengli, "Sparse nonlinear optimization for signal processing and communications" (2014). Doctoral Dissertations. 2267.
https://scholarsmine.mst.edu/doctoral_dissertations/2267