Due to the sparse distribution of ground moving targets, compressed sensing (CS) is a natural approach for their detection. Especially the detection from short CPIs of around 100 pulses is of high interest, since it allows to monitor large areas. In this paper we compare two approaches for handling of the non-sparse clutter - i. e. weighting and filtering - and put special emphasis on radar parameters fulfilling CS requirement
In this paper we present some preliminary results on the application of Compressive Sensing (CS) to ...
Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals ...
We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Compressed sensing (also known as Compressive sampling) is a new mathematical tool for data processi...
Compressed Sensing (CS) provides a rich mathematical framework to efficiently acquire a sparse signa...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rat...
Recently, it is shown that the fundamental problem of rangeDoppler estimation can be solved efficien...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
The first step of ground moving target indication is the differentiation between moving and nonmovin...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
This paper aims at introducing the recent theory of compressive sensing to radar imaging systems in ...
Stretch processing is a pulse compression technique used in Radio Detection and ranging (RADAR) d...
A compressed sensing/sparse-recovery procedure is adopted to obtain enhanced range resolution capabi...
In this paper we present some preliminary results on the application of Compressive Sensing (CS) to ...
Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals ...
We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements...
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse sig...
Compressed sensing (also known as Compressive sampling) is a new mathematical tool for data processi...
Compressed Sensing (CS) provides a rich mathematical framework to efficiently acquire a sparse signa...
This paper presents the application of Compressive Sensing (CS) theory in radar signal processing. C...
Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rat...
Recently, it is shown that the fundamental problem of rangeDoppler estimation can be solved efficien...
In recent years, compressive sensing has received a lot of attention due to its ability to reduce th...
The first step of ground moving target indication is the differentiation between moving and nonmovin...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
This paper aims at introducing the recent theory of compressive sensing to radar imaging systems in ...
Stretch processing is a pulse compression technique used in Radio Detection and ranging (RADAR) d...
A compressed sensing/sparse-recovery procedure is adopted to obtain enhanced range resolution capabi...
In this paper we present some preliminary results on the application of Compressive Sensing (CS) to ...
Compressed Sensing is a new signal processing methodology that allows to reconstruct sparse signals ...
We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements...