Recover algorithm of distributed compressed sensing based on FOCUSS

Distributed compressed sensing exploits both intra- and inter-signal correlation to obtain better recovery performance than that of constructing multiple signals separately. But its recovery algorithm is not researched in depth yet. In this paper, we target the second joint sparse model(JSM-2) of distributed compressed sensing, which is applied to wireless communication widely, and AST-based FOCUSS is expanded to the distributed compressed sensing, the new recovery algorithm is derived. And then, the convergence performance is analyzed by exploiting the globe convergence theory. To verify the presented algorithm and its convergence performance, some simulations are performed, simulation results proved that the presented algorithm work well.