SPACE-TIME ADAPTIVE PROCESSING BASED ON WEIGHTED REGULARIZED SPARSE RECOVERY

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...

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...

Space-Time Adaptive Processing Based on Unequally spaced Antenna Arrays

It is known that the spatial correlation between the desired signal and the undesired signals is an important parameter in adaptive array processing. In this paper, we consider the adaptive antenna of mobile communications under space-time adaptive processing (STAP), where user signals are of multipath rays with different delays, and the space-time correlation functions are employed instead of ...

Space-Time Adaptive Processing: Fundamentals

In this lecture, we present the principles of space-time adaptive processing (STAP) for radar, applied to moving target indication. We discuss the properties of optimum STAP, as well as problems associated with estimating the adaptive weights not encountered with spatial-only processing (i.e. beamforming).