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Iterative Sequential Estimation for Multiple Structured Signals

Authors :
Zhimei Hao
Xianxiang Yu
Na Gan
Guolong Cui
Source :
IEEE Access, Vol 8, Pp 44452-44458 (2020)
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

In this paper, we address the signal estimation problem for a linear combination of multiple structured models, which is widely employed in the passive and/or active sensing systems to characterize the behaviors, for example, jamming and multipath propagation, in radar and communication societies. An iterative sequential estimation (ISE) algorithm is presented to obtain simultaneously the multiple structured signals. At each iteration, employing the estimated signals at the previous step, the optimal linear filters, based on mean-squared error criteria, are designed to minimize the output average power for every element of each signal. Finally, we evaluate the performance of the proposed ISE method compared with the least-square and compressed sensing algorithms via numerical simulations. The results highlight the presented algorithm shows a better signal estimation performance at low SNR and plays a trade-off between the computational complexity and the signal estimation performance.

Details

Language :
English
ISSN :
21693536 and 98745689
Volume :
8
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.b464dc84a9874568964eb59282eb761f
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2020.2978006