Direction of Arrival Estimation and Tracking with Sparse Arrays Jian-Feng Gu, Ph.D. Concordia University, 2013 Direction of Arrival (DOA) estimation and tracking of a plane wave or multiple plane waves impinging on an array of sensors from noisy data are two of the most important tasks in array signal processing, which have attracted tremendous research interest over the past several decades. I...

Direction of arrival (DOA) estimation plays an important role in multi-channel (binaural) speech enhancement systems and auditory humanoid robots. A number of localization methods have been presented, however, most of them require a large array of microphones, or cannot adapt to some special conditions, e.g., humanoid robot with the effect of headrelated transfer function (HRTF). In this paper,...

In this contribution, we propose a DOA (Direction Of Arrival) estimation method of speech signal whose angular resolution is almost uniform with respect to DOA. Our previous DOA estimation method[1] achieves high precision with only two microphones, however its resolution degrades as the propagating direction apart from the array broadside. In the proposed method, the equilateral-triangular mic...

This paper investigates the possibility estimating the direction of arrival (DOA) in a system identification perspective. The system is modeled as an autoregressive (AR) process and extended Kalman filter (EKF) is used to estimate the DOA, which forms a state of the augmented state vector of the EKF. The states generate the signals at a linearly phased array. Simulation results demonstrate the ...

OBJECTIVE To investigate mitophagy in 5 patients with severe dominantly inherited optic atrophy (DOA), caused by depletion of OPA1 (a protein that is essential for mitochondrial fusion), compared with healthy controls. METHODS Patients with severe DOA (DOA plus) had peripheral neuropathy, cognitive regression, and epilepsy in addition to loss of vision. We quantified mitophagy in dermal fibro...

The MUltiple SIgnal Classification (MUSIC) algorithm for DoA is known to degrade due to imprecise knowledge about the array manifold. In this paper, we present a theorem to show how imprecise knowledge affects the performance of the MUSIC algorithm. This theorem proves that performance of the MUSIC algorithm degrades less if the array responses of the sources impinging on the array are less cor...