Impact of Blanket Jamming on Signal Recovery from Compressed Measurements

Sparse signal processing has recently attracted much attention in the field of radar and communication because of its advantages in subsampling and accurate recovery for signal. Since the process of matched filtering that provides a large signal-to-noise ratio (SNR) gain is replaced by non-linear optimization, it is necessary to examine the anti-jamming ability in a new way. In this paper, we focus on the impact of blanket jamming on signal reconstruction from compressed measurements. According to the jamming sparsity on signal dictionary, we divide the blanket jamming into incoherent and coherent models, and then derive the signal-to-jamming ratio (SJR) gain after reconstruction under different compression ratios, sparsity levels, and some other parameters. Numerical simulations verified the theoretical derivation and assisted in obtaining results which are difficult to express analytically.