ROBUST ADAPTIVE METHODS AND THEIR APPLICATIONS IN QUADRUPOLE RESONANCE By HONG XIONG A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ROBUST ADAPTIVE METHODS AND THEIR APPLICATIONS IN QUADRUPOLE RESONANCE By Hong Xiong May 2006 Chair: Jian Li Major Department: Electrical and Computer Engineering Signal amplitude estimation and detection problems have been encountered in many practical applications including the emerging quadrupole resonance (QR) technology for the detection of substance of interest (e.g., explosives). In the QR application, the signal waveform is known a priori. The main challenge of applying QR to the detection of substance of interest is that the returned QR signal is often unavoidably corrupted by strong radio frequency interferences (RFIs). Motivated by the QR application, this dissertation investigates robust adaptive methods for the amplitude estimation of a signal with known arbitrary waveform in the presence of strong RFIs and noise. The main objective is to fundamentally address the signal processing perspectives for explosive detection by QR. The focus is to establish realistic data models, devise innovative signal processing algorithms, and evaluate their performances. For the single antenna based application, we consider the amplitude estimation of a signal with arbitrary known waveform in the presence of strong interferences and noise. Three adaptive finite-impulse response filter based methods are presented to suppress the strong interferences. We first extend the generalized Capon (GC)