Adaptive detection of fluctuating radar targets in unknown correlated Gaussian disturbance has received considerable attention in the past. The Kelly's generalized likelihood ratio test (GLRT) is the preferred algorithm for detecting Swerling-I targets in Gaussian noise. Instead the problem of adaptive detection in non-Gaussian environment is still under investigation. In this paper we pursue two aims: (i) to investigate the performance of the Kelly's GLRT in non-Gaussian clutter; (ii) to derive a detection algorithm with constant false alarm rate (CFAR) behavior with respect to the amplitude probability density function (apdf) parameters and to the correlation structure of the disturbance that outperforms the Kelly's GLRT in non-Gaussian clutter. Performance analysis is presented using both simulated data and real sea clutter data.
Coherent adaptive radar detection in non-Gaussian clutter
Gini Fulvio;Greco Maria V.;
1998-01-01
Abstract
Adaptive detection of fluctuating radar targets in unknown correlated Gaussian disturbance has received considerable attention in the past. The Kelly's generalized likelihood ratio test (GLRT) is the preferred algorithm for detecting Swerling-I targets in Gaussian noise. Instead the problem of adaptive detection in non-Gaussian environment is still under investigation. In this paper we pursue two aims: (i) to investigate the performance of the Kelly's GLRT in non-Gaussian clutter; (ii) to derive a detection algorithm with constant false alarm rate (CFAR) behavior with respect to the amplitude probability density function (apdf) parameters and to the correlation structure of the disturbance that outperforms the Kelly's GLRT in non-Gaussian clutter. Performance analysis is presented using both simulated data and real sea clutter data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.