A variety of detection statistics have been developed and applied to hyperspectral imagery (HSI). The Reed Xiaoli (RX) algorithm is a generalized likelihood ratio test (GLRT) that uses local estimates of the spectral mean and spectral covariance. It satisfies an optimality criterion if, locally, the spectral data have a multivariate normal probability distribution. Alternatively, the stochastic...

Many aspects of a buried mine’s thermal IR signature can be predicted through physical models, and insight provided by such models can lead to better detection. Several techniques for exploiting this information are described. The first approach involves ML estimation of model parameters and followed by classification of those parameters. We show that this approach is related to an approximate ...

Our aim in this paper is to extend the matched subspace detectors (MSDs) of [1–3] to the detection of stochastic signals. In [1–3] the signal to be detected was assumed to be placed deterministically at an unknown location in a known signal subspace. The basis for the subspace was irrelevant. In this paper the signal is assumed to be placed randomly at an unknown location in a known subspace. I...

The problem of noncoherent multiuser detection for multipulse modulation over the Gaussian multiuser channel is studied. It is assumed that neither the energies nor the carrier phases of the signals of any of the users are available at the receiver. Recently, a post-decorrelative generalized likelihood ratio test (GLRT) based detector was proposed as a solution to this problem. In this paper, w...

Recent work on multiantenna spectrum sensing in cognitive radio (CR) networks has been based on generalized likelihood ratio test (GLRT) detectors, which lack the ability to learn from past decisions and to adapt to the continuously changing environment. To overcome this limitation, in this paper we propose a Bayesian detector capable of learning in an efficient way the posterior distributions ...

Most past research on multiuser detection has focused on linearly modulated systems. This paper considers the more general problem of multiuser detection with nonlinear modulation. Our goals are to (a) gain fundamental insight into the capabilities of multiuser detection in such a setting, and (b) to provide practical algorithms that perform better than conventional methods. For the rst goal, w...

The spectrum has increasingly become occupied by various wireless technologies. For this reason, the a scarce resource. In prior work, authors have addressed sensing problem using multi-input and multi-output (MIMO) in cognitive radio systems. We considered detection estimation framework for MIMO network where noise covariance matrix is unknown with perfect channel state information. study, we ...