Remote sensing with radar is typically an ill-posed linear inverse problem: a scene is to be
inferred from limited measurements of scattered electric fields. Parsimonious models provide …

This paper provides principles and applications of the sparse microwave imaging theory and
technology. Synthetic aperture radar (SAR) is an important method of modern remote …

Abstract Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction
information of several electromagnetic waves/sources from the outputs of a number of …

Sparse representation can efficiently model signals in different applications to facilitate
processing. In this article, we will discuss various applications of sparse representation in …

In recent years there has been a growing interest in the study of sparse representation of
signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are …

This paper demonstrates theoretically and empirically that a greedy algorithm called
Orthogonal Matching Pursuit (OMP) can reliably recover a signal with m nonzero entries in …

A full-rank matrix \bfA∈R^n*m with n<m generates an underdetermined system of linear
equations \bfAx=\bfb having infinitely many solutions. Suppose we seek the sparsest …

We present a source localization method based on a sparse representation of sensor
measurements with an overcomplete basis composed of samples from the array manifold …

The theory of compressive sensing has shown that sparse signals can be reconstructed
exactly from many fewer measurements than traditionally believed necessary. In [1], it was …

With solid theoretical foundations and numerous potential applications, Blind Signal
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …