A Space-Time Adaptive Processing Method Based on Sparse Reconstruction of Reverberation Interference

Space-time Adaptive Processing Based on Weighted Regularized Sparse Recovery

In this paper, novel space-time adaptive processing algorithms based on sparse recovery (SR-STAP) that utilize weighted l1-norm penalty are proposed to further enforce the sparsity and approximate the original l0-norm. Because the amplitudes of the clutter components from different snapshots are random variables, we design the corresponding weights according to two different ways, i.e., the Cap...

A New IRIS Segmentation Method Based on Sparse Representation

Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...

A New IRIS Segmentation Method Based on Sparse Representation

Iris recognition is one of the most reliable methods for identification. In general, itconsists of image acquisition, iris segmentation, feature extraction and matching. Among them, iris segmentation has an important role on the performance of any iris recognition system. Eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. In thi...

Space-time adaptive processing

High Dimension Space Time Adaptive Processing Based on FFT

One of the advantages of the joint space time adaptive processing technique is that the freedom degree can be increased greatly without adding any antenna elements, which can improve the ability of the anti-jamming array to reject the narrow band jamming. But the disadvantage is that the computation will be more and more complex with the processing dimension being higher and higher. In this pap...