Authors

Anurag Umbarkar

Type

Text

Type

Thesis

Advisor

DOBOLI, ALEX | SANGJIN HONG.

Date

2010-08-01

Keywords

MAXIMUM LIKELIHOOD, PSOC, RECONFIGURABLE, SOUND LOCALIZATION, WIRELESS NETWORK | Computer Engineering -- Engineering, Electronics and Electrical

Department

Department of Computer Engineering

Language

en_US

Source

This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.

Identifier

http://hdl.handle.net/11401/72689

Publisher

The Graduate School, Stony Brook University: Stony Brook, NY.

Format

application/pdf

Abstract

There have been extensive theoretical studies on sound-based localization using pairs of microphones as well as microphone arrays. In contrast, there has been much less work on implementing and experimenting sound-based localization realized as customized electronic designs. This thesis presents a low cost implementation of a phase-based sound localization method. The implementation uses PSoC programmable mixed-signal embedded System on Chip, which incorporates microcontroller, on-chip SRAM and flash memory, programmable digital blocks and programmable analog blocks, all integrated on the same chip. The report presents a set of experiments to characterize the quality of localization using the proposed low-cost design.In addition, the thesis suggests a modification in the digital signal processing part through which Maximum Likelihood is replaced by an alternative method. The results for both these methods are then compared on the basis of accuracy, memory requirement and execution time. In order to improve the localization accuracy, filter corner frequency reconfiguration and gain reconfiguration is implemented. A wireless sensor network implementation is alsopresented. An extensive set of experiments are provided to explore the advantages of dynamic reconfigurability as well as the network implementation.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.