A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...
— This paper provides a novel state vector and covariance sub-matrix recovery algorithm for a recently developed submap based exactly sparse Extended Information Filter (EIF) SLA...
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
This paper presents a novel modeling algorithm that is capable of simultaneously recovering correct shape geometry as well as its unknown topology from arbitrarily complicated dat...
This paper considers recovery of jointly sparse multichannel signals from incomplete measurements. Several approaches have been developed to recover the unknown sparse vectors from...