Dissertation Defense, Yang Yang

Dissertation Defense, Yang Yang

Title:     Signal Processing and Communications for Radar Sensor Networks

 Date:    Friday, August 7, 2009

Time:    9:00AM 

Place:   Packard Lab, Room 416


This dissertation research mainly addresses some aspects of communications and signal processing focused on networks of radar sensors. Particularly we investigate two problems: waveform design for radar target identification and classification, and energy-efficient cross-layer design for signal detection in radar sensor networks. 

For the first problem, we consider both the ordinary radar with a single transmitter and receiver, and the recently proposed multiple-input multiple-output (MIMO) radar. The optimizing criteria include the mutual information and the minimum mean-square error. We obtain the mathematical solution for the optimum waveform under a given power constraint, which employs water-filling to allocate the limited power appropriately. We also develop minimax robust waveforms for MIMO radar, assuming the target power spectral density lies in an uncertainty class of spectra bounded by known upper and lower bounds. Finally, we develop an iterative optimization algorithm to find waveform solutions that not only optimize the performance measures of interest, but have the desired Kronecker structure.

For the second problem, we are concerned with the scenario of detecting the presence of an object through active sensing in the radar sensor networks. Firstly we consider the energy-efficient routing for signal detection under the Neyman-Pearson criterion. We propose three different routing metrics that aim at an appropriate tradeoff between the detection performance and the energy expenditure, and further design efficient algorithms for finding the optimum routes based on state-of-the-art methods in operations research. Next, we proceed to the case of detecting fluctuating signals in large-scale sensor networks, and we propose a distributed and energy-efficient cross-layer framework, which is scalable with respect to the network size, and greatly alleviates the requirement on the storage and processing ability of the fusion center.


PhD Committee:

Professor  Rick S. Blum (Committee Chair)

            Professor  Shalinee Kishore, ECE

            Profressor Tiffany Jing Li, ECE

            Dr. Brian M. Sadler, U.S. Army Research Laboratory

            Dr. Sana Sfar, InterDigital Communications, LLC

            Professor Aurélie C. Thiele, ISE, Lehigh