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A novel background dictionary learning and structured sparse representation based anomaly detection method is proposed for hyperspectral imagery. First, a robust PCA spectrum dictionary is learned from the plausible background area detected by the local RX detector. With the learned dictionary, the reweighted Laplace prior based structured sparse representation model is then employed to reconstruct...
Unstructured detectors such as KGLRT, ACE and AMF are widely applied for target detection in hyperspectral imagery (HSI). However, conventional global and local approaches construct background model without considering the contamination caused by anomalies and suspected targets. This paper proposes a local ACE algorithm based on the minimum covariance determinant (MCD) estimator. In the proposed algo-rithm,...
This paper considers spectrally efficient anti-jamming system design based on message-driven frequency hopping (MDFH). As a highly efficient frequency hopping scheme, MDFH is particularly robust under strong jamming. However, disguised jamming from sources of similar power strength can cause performance losses. To overcome this drawback, in this paper, we propose an anti-jamming MDFH (AJ-MDFH) system...
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