Document Type


Date of Award

Fall 1-31-2011

Degree Name

Doctor of Philosophy in Electrical Engineering - (Ph.D.)


Electrical and Computer Engineering

First Advisor

Ali Abdi

Second Advisor

Alexander Haimovich

Third Advisor

Hongya Ge

Fourth Advisor

Osvaldo Simeone

Fifth Advisor

Aijun Song


A vector sensor is capable of measuring important non-scalar components of the acoustic field such as the particle velocity, which cannot be obtained by a single scalar pressure sensor. In the past few decades, extensive research has been conducted on the theory and design of vector sensors. On the other hand, underwater acoustic communication systems have been relying on scalar sensors only, which measure the pressure of the acoustic field. By taking advantage of the vector components of the acoustic field, such as the particle velocity, the vector sensor can be used for detecting the transmitted data. In this dissertation, the concept of data detection and equalization in underwater particle velocity channels using acoustic vector sensors was developed. System equations for such a receiver were derived and channel equalization using these sensors was formulated. A multiuser system using vector sensors and space time block codes was also developed, which does not use spreading codes and bandwidth expansion. This is particularly important in bandlimited underwater channels.

With regard to channel models for particle velocity channels, characterization of particle velocity channels and their impact on vector sensor communication systems performance were therefore of interest. In multipath channels such as shallow waters, a vector sensor receives the signal through several paths and each path has a different delay (travel time). Motion of the transmitter or receiver in a multipath channel introduces different Doppler shifts as well. Those introduce different levels of correlation in an array of vector sensors. Therefore, in this dissertation, a statistical framework for mathematical characterization of different types of correlations in acoustic vector sensor arrays was developed. Exact and closed-form approximation correlation expressions were derived which related signal correlations to some key channel parameters such as mean angle of arrivals and angle spreads. Using these expressions, the correlations between the pressure and velocity channels of the sensors could be calculated, in terms of element spacing, frequency and time separation. The derived closed-form parametric expressions for the signal correlations can serve as useful tools to estimate some important physical parameters as well.

Knowledge of the delay and Doppler spreads in acoustic particle velocity channel is also important for efficient design of underwater vector sensor communication system. In this dissertation, these channel spreads were characterized using the zero crossing rates of channel responses in frequency and time domain. Useful expressions for delay and Doppler spreads were derived in terms of the key channel parameters, mean angle of arrivals and angle spreads. These results are needed for design and performance predication of communication systems in time-varying and frequency-selective underwater particle velocity channels.



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