A robust RFPI-based 1-bit compressive sensing reconstruction algorithm

In this paper, we introduce a 1-bit compressive sensing reconstruction algorithm that is not only robust against bit flips in the binary measurement vector, but also does not require a priori knowledge of the sparsity level of the signal to be reconstructed. Through numerical experiments, we show that our algorithm outperforms state-of-the-art reconstruction algorithms for the 1-bit compressive sensing problem in the presence of random bit flips and when the sparsity level of the signal deviates from its estimated value.