Keywords

Acoustic surface wave devices -- Design and construction, Wireless sensor networks -- Design and construction

Abstract

Surface acoustic wave (SAW) devices are a solution for today’s ever growing need for passive wireless sensors. Orthogonal frequency coding (OFC) together with time division multiplexing (TDM) provides a large number of codes and coding algorithms producing devices that have excellent collision properties. Novel SAW noise-like re- flector (NLR) structures with pulse position modulation (PPM) are shown to exhibit good auto- and cross-correlation, and anti-collision properties. Multi-track, multi-transducer approaches yield devices with adjustable input impedances and enhanced collision properties for OFC TDM SAW sensor devices. Each track-transducer is designed for optimum performance for loss, coding, and chip reflectivity. Experimental results and theoretical predictions confirm a constant Q for SAW transducers for a given operational bandwidth, independent of device and transducer embodiment. Results on these new NLR SAW structures and devices along with a new novel 915 MHz transceiver based on a software radio approach was designed, built, and analyzed. Passive wireless SAW temperature sensors were interrogated and demodulated in a spread spectrum correlator system using a new adaptive filter. The first-ever SAW OFC four-sensor operation was demonstrated at a distance of 1 meter and a single sensor was shown to operate up to 3 meters. Comments on future work and directions are also presented

Notes

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Graduation Date

2011

Semester

Spring

Advisor

Weeks, Arthur

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Format

application/pdf

Identifier

CFE0003636

URL

http://purl.fcla.edu/fcla/etd/CFE0003636

Language

English

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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Engineering Commons

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