Block-sparse signal is a typical sparse signal.Among the block-sparse signal problems for compressed sensing

the most existing recovery algorithms require block sparsity as prior knowledge and have a high complexity.In this paper

a block sparsity adaptive iteration algorithm for compressed sensing has been proposed when the block sparsity is unknown.Firstly

the algorithm initializes a block sparsity which will increase by steps.Subsequently

for each block sparsity

a sub-set of the signal support set can be determined by the algorithm

which updates the previous one

until the exact support set is acquired

finally the original signal can be reconstructed through the exact support set.This algorithm doesn’t require block sparsity as prior knowledge and has a low complexity.Simulation results demonstrate its high recovery probability than most existing algorithms

which makes it a promising for practical block-sparse signal compressed sensing task.