Delay Estimation Based on Compressed Sensing Subspace Pursuit Algorithm

Abstract

Abstract. In this paper, a novel method is constructed to estimate the time delay. The purpose of this article is to deal with the lack of measurement data in small sample (single snapshot) and low signal to noise ratio environment during wireless location. First, the sparse representation model of received signals is established. And then the measurement matrix is proofed to achieve the restricted isometry property. The idea of subspace pursuit is to find the subspace which consist of the received signal. Therefore, the delay estimation can be achieved using the corresponding relation between the time delay and the measurement matrix. Finally, simulations show that the subspace pursuit algorithm is suitable for small sample environment. The method can achieve a higher precision than greedy algorithms such as orthogonal matching pursuit and Regularized orthogonal matching pursuit algorithm. Furthermore, the subspace pursuit algorithm has a better performance in anti-multi channels.