A Compression Sampling System based on Sparse AR Model

Abstract

A compression sampling system based on sparse AR (auto regression) model is designed in this paper. The sparse samples are non-uniform sampled using uniform random sampling (URS) method by mono-chip computer. To guarantee the reconstruction effectiveness, a basis matrix is constructed with prior signal information to represent the received signal sparsely. Then the received signal is recovered from the samples using optimization algorithms in PC. The URS method can scale down the sampling frequency effectively. The basis matrix is constructed based on the known AR model and named sparse AR (SAR) basis in this paper. Since the SAR basis is a self-adaptive basis, better reconstruction quality at a low sampling rate can be obtained. The performance of the proposed compression sampling system is illustrated using normal vibration signal. From both simulation and experiment, the transmitted signal can be reconstructed effectively and accurately