Array signal processing for QR

The amplitude estimation of a signal whose waveform is known (up to an unknown scaling factor) in the presence of interference and noise is of interest in several applications including using the emerging quadrupole resonance (QR) technology for explosive detection. In such applications, a sensor array is often deployed for interference suppression. This paper considers the complex amplitude estimation of a known waveform signal whose array response is also known a priori. Two approaches, viz the Capon and the maximum likelihood (ML) methods, are considered for the signal amplitude estimation in the presence of temporally white but spatially colored interference and noise. A comparative study shows that the ML estimate is strictly unbiased while the Capon estimate is biased downwards even for SNR /spl Gt/ 1. We show that both methods are asymptotically statistically efficient when number of data samples is large but not when the signal-to-noise ratio (SNR) is high.