On pre-whitening and accuracy in DOA estimation by sparse signal processing on beamformed data

Design and analysis of compressed sensing radar detectors

We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements corrupted by additive white Gaussian noise. We propose two novel architectures and compare their performance by means of Receiver Operating Characteristic (ROC) curves. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP)...

Asymptotic analysis of complex LASSO via complex approximate message passing (CAMP)

Recovering a sparse signal from an undersampled set of random linear measurements is the main problem of interest in compressed sensing. In this paper, we consider the case where both the signal and the measurements are complex-valued. We study the popular recovery method of l1- regularized least squares or LASSO.While several studies have shown...

Compressive sensing for high resolution radar imaging

In this paper we present some preliminary results on the application of Compressive Sensing (CS) to high resolution radar imaging. CS is a recently developed theory which allows reconstruction of sparse signals with a number of measurements much lower than what is required by the Shannon sampling theorem. This method has already found its way in...

Experimental example of the pseudo-forces method used in characterisation of a structure-borne sound source

In the analysis of machinery noise the aspect of sound source characterisation is of importance. Unlike for airborne sources, no widely applicable methods are available yet for structure-borne sound sources. In previous work a 'pseudo-forces' methodology was suggested. In this approach fictitious forces on the outer surface replace the internal...