IEEE Workshop on Statistical Signal and Array Processing 

Abstract: An important signal parameter estimation problem is time-delay estimation. Here the unknown is the time origin of the signal: s (l, θ) = s (l − θ). The duration of the signal (the domain over which the signal is de ned) is assumed brief compared with the observation interval L. Although in continuous time the signal delay is a continuous-valued variable, in discrete time it is not. Consequently, the maximum likelihood estimate cannot be found by di erentiation, and we must determine the maximum likelihood estimate of signal delay by the most fundamental expression of the maximization procedure. Assuming Gaussian noise, the maximum likelihood estimate of delay is the solution of

Abstract: A novel direction of arrival (DOA) technique is presented which constructs estimates of the relative delay mixing parameters associated with each signal by taking the ratio of time-frequency representations of two mixtures. The technique is based on the degenerate unmixing and estimation technique (DUET) (Jourjine et al., Proc. ICASSP 2000, June 5-9, 2000, Istanbul, Turkey). If the sources are W-disjoint orthogonal, meaning that only one signal is active in the time-frequency plane at a given time-frequency, then the ratio only depends on the mixing parameters of one source. The ratio can thus be used to generate estimates of the mixing parameters and these estimates can be clustered to determine both the number of sources present in the mixtures and their associated mixing parameters. The method allows for the estimation of the DOA for many sources using only two receive antennas, whereas traditional techniques require N antennas to estimate N-1 angles of arrival. Simulation results are presented and compared to MUSIC, ESPRIT, and other DOA estimation techniques.

Abstract: The effects of mutual coupling on the direction finding accuracy of a linear array of dipole elements are studied. An approximative expression of the measured voltages when a plane wave is incident upon the array is derived using mutual impedances. The direction finding accuracy is then investigated by calculating the Cramer-Rao lower bound. It is found that a known coupling does not affect the estimation performance much. In the case of an unknown coupling, the estimation procedure can be simplified by using only a few off-diagonal elements of the coupling matrix. Depending on how many parameters are included, the RMS error can actually be smaller than the CRB for the case when all off-diagonals are estimated.

Abstract: Most conventional techniques for independent component analysis (or blind source separation) resort to second-order statistics to decorrelate the observed data. The prewhitening step makes these algorithms sensitive to the presence of additive Gaussian noise. A higher-order-only technique is presented. The identification problem is approached in a (linear and multilinear) algebraic framework: our derivation starts with the observation that the solution can be obtained from the canonical decomposition (CANDECOMP) of a higher-order cumulant tensor. Next, it is demonstrated that the CANDECOMP components follow from the simultaneous diagonalization, by congruence transformation, of a set of matrices. A reformulation in terms of orthogonal unknowns leads to a simultaneous Schur decomposition, which is solved by a Givens-type iteration. The technique can be considered as the higher-order-only equivalent of the popular JADE-algorithm.