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Ultrasonic Target Detection and Communications

Event Date 

February 19, 2019 - 1:00pm to 2:00pm

Location 

Wishnick Hall, Room 131
3255 South Dearborn
Chicago, IL 60616

Description 

Ultrasonic imaging applications often resort to signal modeling, parameter estimation and data analysis for aberration detection, pattern recognition, and classification. In this study, we present Split-Spectrum Processing (SSP) for ultrasonic target detection in the presence of strong clutter, and the Chirplet Signal Decomposition (CSD) to characterize highly complex and interfering patterns of ultrasonic scattered echoes for signal analysis and imaging. The chirplet decomposition of ultrasonic signals facilitates a systematic, tractable and quantitative approach to correlate the estimated chirplets to the actual physical characteristics of the objects and their embedded environment that generates scattered ultrasonic echoes. Signal decomposition and identifying the source of ultrasonic signals has a broad range of applications including nondestructive testing, structural health monitoring, and tissue characterization. Ultrasonic communications through solid channels are adversely affected by absorption, scattering, refractions, reverberations, beam skewing, dispersion, mode conversation, and multipath. And, above all, these challenges are compounded by the geometrical structure of solids and type of ultrasonic waves. To explore and combat these challenges, we have developed a Software Defined Ultrasonic Communication (SDUC) System-on-Chip (SoC) platform which is reconfigurable and offers high-performance computational capability. We have examined the SDUC system using AM (Amplitude Modulation), OOK (on and off keying), BPSK (Binary Phase Shift Keying), QPSK (quadrature phase shift keying), and OFDM (orthogonal frequency-division multiplexing). The SDUC system is tested using differently structured solid channels (such as blocks, plates, and pipes); and bitrates and bit rate errors are examined using 2.5 MHz ultrasonic transducers. Over the years there has been an ongoing effort in the ECASP Research Laboratory to engage undergraduate students in research related to signal and image processing, sensors, machine vision, autonomous navigation, embedded computing, and communications. A brief video presentation of the research/development projects of undergraduate students will be presented.

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