GPS Sparse Multipath Signal Estimation Based on Compressive Sensing

Author:

He Guodong12ORCID,Song Maozhong1ORCID,Zhang Shanshan2,Qin Huiping3,Xie Xiaojuan2

Affiliation:

1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

2. School of Physics and Electronic Information, Anhui Normal University, Wuhu 241003, China

3. School of Electronics and Information, South China University of Technology, Guangzhou 510641, China

Abstract

A GPS sparse multipath signal estimation method based on compressive sensing is proposed. A new 0 norm approximation function is designed, and the parameter of the approximate function is gradually reduced to realize the approximation of 0 norm. The sparse signal is reconstructed by a modified Newton method. The reconstruction performance of the proposed algorithm is better than several commonly reconstruction algorithms at different sparse numbers and noise intensities. The GPS sparse multipath signal model is established, and the sparse multipath signal is estimated by the proposed reconstruction algorithm in this paper. Compared with several commonly used estimation methods, the estimation error of the proposed method is lower.

Funder

Ministry of Education of the People's Republic of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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