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The SAM Workshop is an important IEEE Signal Processing Society event dedicated to sensor array and multichannel signal processing. The organizing committee invites the international community to contribute with state-of-the-art developments in the field.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         

The eigenbeam-ESPRIT (EB-ESPRIT) is well known as a high-resolution parametric direction-of-arrival (DOA) estimation technique for a spherical microphone array. Unlike other eigenbeam beamformers such as EB-MVDR and EB-MUSIC, there is no need for exhaustive grid-search with EB-ESPRIT. However, when sources are positioned near the equator, the EB-ESPRIT inevitably induces a singularity problem due to the singularity of its tangent function utilized as a directional parameter. Here, a new EB-ESPRIT technique based on a nonsingular directional parameter is proposed.


This work addresses the issue of undersampled phase retrieval using the gradient framework and proximal regularization theorem. It is formulated as an optimization problem in terms of least absolute shrinkage and selection operator (LASSO) form with (ℓ2+ℓ1) norms minimization in the case of sparse incident signals. Then, inspired by the compressive phase retrieval via majorization-minimization technique (C-PRIME) algorithm, a gradient-based PRIME algorithm is proposed to solve a quadratic approximation of the original problem.


Sea clutters with Doppler-varying spectrum exert a
notable negative impact on the detection performance, especially
with low-velocity targets, when a passive bistatic radar is employed
to detect sea-surface targets. One feasible solution is to
modulate the reference signal onto the Doppler dimension and, as
such, a filter with a wide notch and sharp edges can be obtained
to suppress the residual clutters. However, to achieve this goal, a
considerably high computational complexity is demanded in the


Societal acceptance of self-driving cars (SDC) is predicated on a level of trust between humans and the au- tonomous vehicle. Although the performance of SDCs has im- proved dramatically, the question of mainstream acceptance and requisite trust is still open. We are exploring this question through integration of virtual reality SDC simulator and an electroencephalographic (EEG) recorder. In order for a passenger to build and maintain trust, the SDC will need to operate in a manner that elicits positive emotional response and avoids negative emotional response.