Wide-area persistent radar video o↵ers the ability to track moving targets. A shortcoming of the current technology is an inability to maintain track when Doppler shift places moving target returns co-located with strong clutter. Further, the high down-link data rate required for wide-area imaging presents a stringent system bottleneck. We present a multi-channel approach to augment the synthet...

In this paper, projection statistics (PS) are applied to detect and mitigate outliers in adaptive processing algorithms. Outliers present in training data result in slow adaptive processor convergence. In radar, these outliers may arise from clutter discretes, desired targets, or jammers. PS provide a computationally tractable technique for identifying and mitigating outlier data samples prior ...

Practical STAP implementations rely on reduced-dimension processing, using techniques such as principle components or partially adaptive filters. The dimension reduction not only decreases the computational load, it also reduces the sample support required for estimating the interference statistics. This results because the clutter covariance is implicitly assumed to possess a certain (nonparam...

In this paper, the algorithms for adaptive rejection of a radar clutter are synthesized for the case of a priori unknown spectral-correlation characteristics at wobbulation of a repetition period of the radar signal. The synthesis of algorithms for the non-recursive adaptive rejection filter (ARF) of a given order is reduced to determination of the vector of weighting coefficients, which realiz...

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...

Two-dimensional (2D) convolution is a basic operation in digital signal processing, especially in image and video applications. Although its computation is conceptually simple, a sum of products of constants by variables, its implementation is highly demanding in terms of computational power, especially when addressed to real-time embedded systems. This work brings an innovative approach orient...

In this paper we present a blind adaptive space-time processing algorithm for separating signals which are spectrally and/or spatially overlapped. The algorithm exploits the cyclostationary nature of many communication signals, but does not require knowledge of the statistical properties of the desired signal. It merely requires knowledge of a (distinct) cycle frequency. It is shown that the pe...

In this paper, we study the space-time adaptive processing (STAP) and its subband realization for mobile communications. The conditions of perfect STAP processing (i.e., perfect equalization of desired user signal and perfect suppression of undesired user signals), are investigated in noise-free case, which provide a basic rule for practical design of STAP systems. Based on the polyphase repres...

Space-Time Adaptive Processing (STAP) is now commonly used in radar engineering to detect the targets by using a phased array antenna system. However, the computational cost of the standard version and the memory storage are high. In addition, the detection could be more robust against interfering targets. To solve the above problems, autoregressive (AR) modelling of the disturbances, namely th...