Compression Sensing Signal Detection Algorithm Based on Orthogonal Matching Pursuit

At present, most of the detection algorithms used in our country take the iteration process of feature as the research object. This detection method is only suitable for the presence of perceptual signals, but not for all the signal measurement work. This paper introduces the basic principle of signal compression sensing, the construction of measurement matrix and the orthogonal matching pursuit algorithm. The orthogonal matching pursuit algorithm is applied to compressed sensing reconstruction of sparse signals in one-dimensional time domain and transform domain, and the reconstruction performance of the orthogonal matching pursuit algorithm is analyzed. Compared with the detection algorithm based on matching pursuit, this algorithm based on the idea of orthogonal matching pursuit corrects the feature quantities as the basis of decision. When the signal of interest exists, the feature quantities with smaller fluctuations are obtained, and better detection results are obtained. The experimental results show that the OMP detection algorithm proposed in this paper has better performance in improving detection success rate, sampling points required, noise suppression and so on compared with MP detection algorithm.