An improved TOA estimation algorithm based on denoised MVDR for B5G positioning

被引：1

作者：

Yao, Yihao ^{[1
]}

Zhao, Kun ^{[1
]}

Zheng, Zhengqi ^{[1
]}

机构：

[1] East China Normal Univ, Engn Ctr SHMEC Space Informat & GNSS, Shanghai 200241, Peoples R China

来源：

PHYSICAL COMMUNICATION | 2023年 / 57卷

基金：

中国国家自然科学基金;

关键词：

TOA estimation; Minimum variance distortionless response (MVDR); 5G positioning; Multipath environments; BEAMFORMER; INDOOR;

D O I：

10.1016/j.phycom.2022.101992

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes an improved minimum variance distortionless response (MVDR) based TOA estimation algorithm for 5G NR signals under multipath environments. The proposed algorithm achieves high resolution by exploiting a large number of subcarriers of 5G signals and reduces the dimension of the covariance matrix involved in MVDR substantially by utilizing a novel smoothing scheme. Since MVDR requires a relatively high signal-to-noise ratio (SNR), a denoising method is used to improve the TOA estimation performance. Simulation results show that the proposed algorithm achieves much higher resolution than the Bartlett beamformer (BF) and the TOA estimation accuracy remains high over a wide range of SNRs.(c) 2022 Elsevier B.V. All rights reserved.

引用

页数：7