Hamschin, Brandon Michael
(2011)
Waveform Design with Time and Frequency Constraints for Optimal Detection of Elastic Objects.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
In active sonar, the goal is to learn about an object or environment by transmitting a sound and processing the echo. The sound we choose to transmit will determine what we learn about the object, much like the choice of question we ask a person will determine what we learn from them. Thus, designing the best (i.e. optimal) transmit waveform is a longstanding area of research that remains active since different environments and ever evolving operational objectives weigh heavily on how we define optimality.In this work we extend a recent result by Kay that gives the optimal transmit signal that maximizes the probability of detecting an elastic object in the presence of Gaussian reverber- ation and additive Gaussian interference. Kay's solution specifies the spectral magnitude for the optimal transmit waveform, and hence there is an unlimited number of "optimal" wave- forms that can be transmitted, all with the same spectral magnitude but differing in terms of time domain characteristics such as duration and peak power. We extend Kay's approach in order to obtain a unique optimal waveform by incorporating time-domain constraints into two optimization-based problem formulations. These two problem formulations lead to new and complementary signal design approaches that impose temporal duration constraints while preserving, to varying degrees, the optimality inherent in the spectral magnitude.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
24 June 2011 |
Date Type: |
Completion |
Defense Date: |
28 March 2011 |
Approval Date: |
24 June 2011 |
Submission Date: |
5 April 2011 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Electrical Engineering |
Degree: |
MSEE - Master of Science in Electrical Engineering |
Thesis Type: |
Master's Thesis |
Refereed: |
Yes |
Uncontrolled Keywords: |
Detection Theory; Digital Signal Processing; Optimization; Waveform Design; Classification Theory; Estimation Theory |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-04052011-212244/, etd-04052011-212244 |
Date Deposited: |
10 Nov 2011 19:34 |
Last Modified: |
15 Nov 2016 13:38 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/6802 |
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