Add to ORKGIn this paper, a theoretical expression of the optimum non-Gaussian radar detector is derived from the non-Gaussian SIRP model (Spherically Invariant Random Process) clutter and a bayes-ian estimator of the characteristic function of the SIRP. The SIRP model is used to perform coherent detection and to modelize the clutter as a complex Gaussian process whose variance is itself a positive random variable (r.v.). The PDF of the variance charac-terizes the statistics of the SIRP and after performing a bayesian estimation of this PDF from reference clutter cells we derive the Bayesian Optimum Radar Detector (BORD) and its statistical as-ymptotic form without any knowledge about the statistics of the clutter. We evaluate BORD performance for an ...
The area of research dedicated to the design and optimisation of radar detection schemes is a consta...
ii We examine the problem of determining a decision threshold for the binary hy-pothesis test that n...
This paper presents a detailed theoretical analysis of a recently introduced covariance matrix estim...
We derive the expression of an optimum non-Gaussian radar detector from the non-Gaussian spherically...
International audienceWe derive the expression of an optimum non-Gaussian radar detector from the no...
International audienceIn this paper detection performances of the Bayesian Optimum Radar Detector (B...
Abstract — In this paper, an expression of the optimum non-Gaussian radar detector is derived from t...
International audienceIn this paper, we study the adaptive version of the asymptotical Bayesian Opti...
In this paper, we study the adaptive version of the asymptot-ical Bayesian Optimum Radar Detector (B...
International audienceAt low grazing angle and/or high resolution radar, sea clutter is not Gaussian...
For a long time, radar echoes coming from the various returns of the transmitted signal on many obje...
In this paper, we use the theory of generalized likelihood ra-tio tests (GLRT) to study the adaptive...
This paper considers the problem of adaptive radar detection in Gaussian clutter with unknown spectr...
International audienceIn this paper, we use the theory of generalized likelihood ratio tests (GLRT) ...
New results are presented for coherent detection of radar signals with random parameters in correlat...
The area of research dedicated to the design and optimisation of radar detection schemes is a consta...
ii We examine the problem of determining a decision threshold for the binary hy-pothesis test that n...
This paper presents a detailed theoretical analysis of a recently introduced covariance matrix estim...
We derive the expression of an optimum non-Gaussian radar detector from the non-Gaussian spherically...
International audienceWe derive the expression of an optimum non-Gaussian radar detector from the no...
International audienceIn this paper detection performances of the Bayesian Optimum Radar Detector (B...
Abstract — In this paper, an expression of the optimum non-Gaussian radar detector is derived from t...
International audienceIn this paper, we study the adaptive version of the asymptotical Bayesian Opti...
In this paper, we study the adaptive version of the asymptot-ical Bayesian Optimum Radar Detector (B...
International audienceAt low grazing angle and/or high resolution radar, sea clutter is not Gaussian...
For a long time, radar echoes coming from the various returns of the transmitted signal on many obje...
In this paper, we use the theory of generalized likelihood ra-tio tests (GLRT) to study the adaptive...
This paper considers the problem of adaptive radar detection in Gaussian clutter with unknown spectr...
International audienceIn this paper, we use the theory of generalized likelihood ratio tests (GLRT) ...
New results are presented for coherent detection of radar signals with random parameters in correlat...
The area of research dedicated to the design and optimisation of radar detection schemes is a consta...
ii We examine the problem of determining a decision threshold for the binary hy-pothesis test that n...
This paper presents a detailed theoretical analysis of a recently introduced covariance matrix estim...