Open Access

ARTICLE

l₁-norm Based GWLP for Robust Frequency Estimation

Yuan Chen¹, Liangtao Duan¹, Weize Sun^{2, *}, Jingxin Xu³

1 University of Science & Technology Beijing, Beijing, 100083, China.
2 ShenZhen University, Shenzhen, 518060, China.
3 Department of Housing and Public Works, Queensland Government, Brisbane, Australia.

* Corresponding Author: Weize Sun. Email: .

Journal on Big Data 2019, 1(3), 107-116. https://doi.org/10.32604/jbd.2019.07294

Abstract

In this work, we address the frequency estimation problem of a complex singletone embedded in the heavy-tailed noise. With the use of the linear prediction (LP) property and l₁-norm minimization, a robust frequency estimator is developed. Since the proposed method employs the weighted l₁-norm on the LP errors, it can be regarded as an extension of the l_p-generalized weighted linear predictor. Computer simulations are conducted in the environment of α-stable noise, indicating the superiority of the proposed algorithm, in terms of its robust to outliers and nearly optimal estimation performance.

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Keywords

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