Sentence examples for estimation of direction from inspiring English sources

The focus of this paper is on the use of the binaural cue ILD and estimation of direction of arrival on the horizontal plane.

The human estimation of direction of arrival can be modeled by two important binaural auditory cues [5]: interaural time difference (ITD) and interaural level difference (ILD).

Estimation of direction of arrival (DOA) from data collected by sensor arrays is of fundamental importance to a variety of applications such as radar, sonar, wireless communications, geophysics and biomedical engineering.

In Table 1, the estimation of direction nonlinearity is tested in a two-dimensional case where the prior has identity covariance matrix and the measurement function is mathbf{y} = e^{mathbf{a}^{T} mathbf{x}}.

Therefore, only a true source can exhibit a consistent estimation of direction on consecutive frames of signals because the weighting function of ES-GCC also has certain robustness to reverberation.

In this contribution, an unbiased, efficient, and robust practical technique is presented for estimation of direction dependent as well as orientation averaged two-point correlation functions in three-dimensional (3D) microstructures from the measurement performed on vertical metallographic planes.

In this article, we consider the joint estimation of direction-of-departure (DOD) and direction-of-arrival (DOA) information of maneuvering targets in a bistatic multiple-input multiple-output (MIMO) radar system that exploits spatial time-frequency distribution (STFD).

In the article "Joint DOD/DOA estimation in MIMO radar exploiting time-frequency signal representations"[1] Yimin Zhang et al. deal with the joint estimation of direction-of-departure (DOD) and direction-of-arrival (DOA) information of maneuvering targets in a bistatic multiple-input multiple-output (MIMO) radar system when exploiting spatial time-frequency distribution (STFD).

We use a more realistic GARCH-based noise model in the maximum-likelihood approach for the estimation of direction-of-arrivals (DOAs) of impinging sources onto a linear array, and demonstrate using measured noise that this approach is feasible for the additive noise and direction finding in an underwater environment.

Estimation of directions of arrival by matching pursuit.

To solve these problems Ashino et al. [123] presented Estimation of Directions of Arrival by Matching Pursuit (EDAMP) method for VM migration between heterogeneous hypervisor implementation.