This paper deals with radar detection in impulsive clutter. Its aim is twofold. Firstly, assuming a Spherically Invariant Random Vectors (SIRV) model for the clutter, the corresponding unknown covariance matrix is estimated by a recently introduced algorithm [1, 2]. A statistical analysis (bias, consistency, asymptotic distribution) of this estimate will be summarized allowing us to give the GLRT properties: the SIRV-CFAR (Constant False Alarm Rate) property, i.e. texture-CFAR and Covariance Matrix-CFAR, and the relationship between the Probability of False Alarm (PFA) and the detection threshold. Secondly, one of the main contributions of this paper is to give some results obtained with real non-Gaussian data. These results demonstrate the...
An algorithm for detecting a random target signal against a mixture of correlated compound-Gaussia...
We address the estimation of the structure of the covariance matrix and its application to adaptive ...
In this paper, we study the adaptive version of the asymptot-ical Bayesian Optimum Radar Detector (B...
This paper deals with radar detection in impulsive clutter. Its aim is twofold. Firstly, assuming a ...
International audienceThis paper deals with radar detection in impulsive noise. Its aim is twofold. ...
New results are presented for coherent detection of radar signals with random parameters in correlat...
This thesis deals with radar detection in impulsive noise contexts. Indeed, under Gaussian assumptio...
Abstract—This paper deals with covariance matrix estimation for radar detection in non-Gaussian nois...
ii We examine the problem of determining a decision threshold for the binary hy-pothesis test that n...
The subject of detection of spatially distributed targets in non-Gaussian noise with unknown statist...
International audienceIn this paper, we use the theory of generalized likelihood ratio tests (GLRT) ...
International audienceThis paper deals with covariance matrix estimation for radar detection in non-...
Abstract: The clutter encountered in low grazing an-gle situations is generally a non gaussian impul...
In this paper, we use the theory of generalized likelihood ra-tio tests (GLRT) to study the adaptive...
Special Issue on MIMO Radar and its ApplicationsInternational audienceIn this paper, the generalized...
An algorithm for detecting a random target signal against a mixture of correlated compound-Gaussia...
We address the estimation of the structure of the covariance matrix and its application to adaptive ...
In this paper, we study the adaptive version of the asymptot-ical Bayesian Optimum Radar Detector (B...
This paper deals with radar detection in impulsive clutter. Its aim is twofold. Firstly, assuming a ...
International audienceThis paper deals with radar detection in impulsive noise. Its aim is twofold. ...
New results are presented for coherent detection of radar signals with random parameters in correlat...
This thesis deals with radar detection in impulsive noise contexts. Indeed, under Gaussian assumptio...
Abstract—This paper deals with covariance matrix estimation for radar detection in non-Gaussian nois...
ii We examine the problem of determining a decision threshold for the binary hy-pothesis test that n...
The subject of detection of spatially distributed targets in non-Gaussian noise with unknown statist...
International audienceIn this paper, we use the theory of generalized likelihood ratio tests (GLRT) ...
International audienceThis paper deals with covariance matrix estimation for radar detection in non-...
Abstract: The clutter encountered in low grazing an-gle situations is generally a non gaussian impul...
In this paper, we use the theory of generalized likelihood ra-tio tests (GLRT) to study the adaptive...
Special Issue on MIMO Radar and its ApplicationsInternational audienceIn this paper, the generalized...
An algorithm for detecting a random target signal against a mixture of correlated compound-Gaussia...
We address the estimation of the structure of the covariance matrix and its application to adaptive ...
In this paper, we study the adaptive version of the asymptot-ical Bayesian Optimum Radar Detector (B...