Compressive sensing signal detection algorithm based on orthogonal matching pursuit

Without reconstructing the signal itself, signal detection could be solved by a detection algorithm, which directly processes the sampling values obtained from compressive sensing signal. In current detection algorithm, as the judgment criterion, the characteristic quantity is determined in one iterative process. When the signal of interest exists, the characteristic quantity obtained from the detection algorithm fluctuates, which decreases the detection performance. Therefore, in this paper, we propose an improved algorithm, which amends the characteristic quantity based on orthogonal matching pursuit in each iteration, reduces the fluctuation of the characteristic quantity and improves the detection performance. Experiment results show that compared with original algorithm the proposed method greatly reduces the fluctuation of the characteristic quantity, has higher success rate of detection under the same detection threshold, requires fewer samples under the same success rate of detection and allows lower SNR under the same success rate of detection.