Ultrasound imaging through aberrating layers

Whereas aberrating layers are typically viewed as an impediment to medical ultrasound imaging, they can, surprisingly, also be used to our benefit. As long as we can model the effect of an aberrating layer, we can utilize ‘model-based imaging’, the imaging technique explored throughout this thesis, to reconstruct ultrasound images where...

Joint Blind Calibration and Time-Delay Estimation for Multiband Ranging

In this paper, we focus on the problem of blind joint calibration of multiband transceivers and time-delay (TD) estimation of multipath channels. We show that this problem can be formulated as a particular case of covariance matching. Although this problem is severely ill-posed, prior information about radio-frequency chain distortions and...

Constrained Least Squares for Extended Complex Factor Analysis

For subspace estimation with an unknown colored noise, Factor Analysis (FA) and its extensions, denoted as Extended FA (EFA), are good candidates for replacing the popular eigenvalue decomposition (EVD). Finding the unknowns in (E)FA can be done by solving a non-linear least square problem. For this type of optimization problems, the Gauss...

Statistical Graph Signal Processing: Stationarity and Spectral Estimation

Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domain. Although time-varying signals are abundant in nature, in many contemporary applications the information of interest resides in more irregular domains that can be conveniently represented using a graph. This chapter reviews...

Efficient Calibration of Radio Interferometers Using Block LDU Decomposition

Having an accurate calibration method is crucial for any scientific research done by a radio telescope. The next generation radio telescopes such as the Square Kilometre Array (SKA) will have a large number of receivers which will produce exabytes of data per day. In this paper we propose new direction-dependent and independent calibration...

Complex Factor Analysis and Extensions

Many subspace-based array signal processing algorithms assume that the noise is spatially white. In this case, the noise covariance matrix is a multiple of the identity and the eigenvectors of the data covariance matrix are not affected by it. If the noise covariance is an unknown arbitrary diagonal (e.g., for an uncalibrated array), the...

Covariance matching techniques for radio astronomy calibration and imaging

The search for the answer to one of the most fundamental scientific questions, “How was the universe formed?”, requires us to study very weak radio signals from the early universe. In the last eighty years, radio astronomers have been able to use radio frequency observations for significant discoveries such as quasars, super massive Black Holes...