By exploring sparsity in the target space, compressive sensing (CS) based multi-input multi-output (MIMO) radar systems achieve either the same localization performance as traditional methods but with significantly fewer measurements, or significantly improved performance with the same number of measurements. The work presented here investigates the performance gain of CS-MIMO radars, stemming from optimal power allocation among the transmit antennas, or optimal waveform design. In both cases, the optimization criterion is the minimization of the coherence between the target returns from different search cells, or equivalently, the coherence of the columns of the sensing matrix
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
Compressive Sensing (CS) provides a new paradigm in data acquisition and signal processing based on ...
This scientific article delves into the intricate domain of waveform design in the context of Compre...
Multi-input and multi-output (MIMO) radars achieve high resolution of arrival direction by transmitt...
In this paper, an optimization methodology for re-positioning antenna elements of a collocated Compr...
The performance of conventional radar is foreseen to be im-proved by the implementation of compressi...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in rece...
Abstract—We study compressive sensing in the spatial domain to achieve target localization, specific...
Abstract—Compressed sensing is a technique for efficiently sampling signals which are sparse in some...
Compressed sensing techniques make it possible to exploit the sparseness of radar scenes to potentia...
Abstract Conventional algorithms used for parameter estimation in colocated multiple-...
Abstract—This paper considers range-angle-Doppler estima-tion in collocated, compressive sensing-bas...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
Compressive Sensing (CS) provides a new paradigm in data acquisition and signal processing based on ...
This scientific article delves into the intricate domain of waveform design in the context of Compre...
Multi-input and multi-output (MIMO) radars achieve high resolution of arrival direction by transmitt...
In this paper, an optimization methodology for re-positioning antenna elements of a collocated Compr...
The performance of conventional radar is foreseen to be im-proved by the implementation of compressi...
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing in radar,...
Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in rece...
Abstract—We study compressive sensing in the spatial domain to achieve target localization, specific...
Abstract—Compressed sensing is a technique for efficiently sampling signals which are sparse in some...
Compressed sensing techniques make it possible to exploit the sparseness of radar scenes to potentia...
Abstract Conventional algorithms used for parameter estimation in colocated multiple-...
Abstract—This paper considers range-angle-Doppler estima-tion in collocated, compressive sensing-bas...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
The dissertation discusses compressive sensing and its applications to localization in multiple-inpu...
Compressive Sensing (CS) provides a new paradigm in data acquisition and signal processing based on ...
This scientific article delves into the intricate domain of waveform design in the context of Compre...