An lp-norm minimization approach to time delay estimation in impulsive noise

被引:30
|
作者
Zeng, Wen-Jun [1 ]
So, H. C. [1 ]
Zoubir, Abdelhak M. [2 ]
机构
[1] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[2] Tech Univ Darmstadt, Inst Telecommun, Signal Proc Grp, Darmstadt, Germany
关键词
alpha-stable process; l(p)-norm minimization; Impulsive noise; Robust estimation; Time delay estimation;
D O I
10.1016/j.dsp.2013.03.013
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
Estimating the time delay between two signals received at spatially separated sensors is an important topic in signal processing and has a variety of practical applications. Conventionally, time delay estimation (TDE) can be achieved in two steps. The coefficients of 'a finite impulse response filter used to model the subsample delay are first computed and then interpolated to produce the delay estimate. Despite its simplicity, the two-step method suffers from error accumulation, estimation bias, and is not robust to impulsive noise or outliers. To overcome these drawbacks, a family of robust algorithms for direct TDE is proposed using l(p)-norm minimization, with 1 <= p <= 2. Although the direct approach leads to a nonconvex optimization problem, efficient algorithms are designed for finding the global solution. Its robustness and accuracy in the presence of a-stable noise are demonstrated by comparing it with the standard two-step scheme, cross-correlator and fractional lower-order covariation method. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:1247 / 1254
页数:8
相关论文
共 50 条
  • [21] Lp-norm based minimisation algorithm for signal parameter estimation
    Zhang, H
    Peng, YL
    ELECTRONICS LETTERS, 1999, 35 (20) : 1704 - 1705
  • [22] A Temperature Data Prediction Method Using Graph Filter and Lp-Norm Minimization
    Tseng, Chien-Cheng
    Lee, Su-Ling
    Su, Rui-Heng
    2017 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW), 2017,
  • [23] An Investigation of lp-Norm Minimization for the Artifact-Free Inversion of Gravity Data
    Li, Zelin
    Yao, Changli
    REMOTE SENSING, 2023, 15 (14)
  • [24] Joint Weighted Tensor Schatten p-Norm and Tensor lp-Norm Minimization for Image Denoising
    Zhang, Xiaoqin
    Zheng, Jingjing
    Yan, Yufang
    Zhao, Li
    Jiang, Runhua
    IEEE ACCESS, 2019, 7 : 20273 - 20280
  • [25] Seismic Traffic Noise Attenuation Using lp-Norm Robust PCA
    Wu, Bangyu
    Yu, Jiaxu
    Ren, Haoran
    Lou, Yihuai
    Liu, Naihao
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (11) : 1998 - 2001
  • [26] Sparse Hyperspectral Unmixing via Heuristic lp-Norm Approach
    Salehani, Yaser Esmaeili
    Gazor, Saeed
    Cheriet, Mohamed
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (04) : 1191 - 1202
  • [27] Standardized time series Lp-norm variance estimators for simulations
    Tokol, G
    Goldsman, D
    Ockerman, DH
    Swain, JJ
    MANAGEMENT SCIENCE, 1998, 44 (02) : 234 - 245
  • [28] On resistant Lp-Norm Estimation by means of iteratively reweighted least Squares
    Marx, Christian
    JOURNAL OF APPLIED GEODESY, 2013, 7 (01) : 1 - 10
  • [29] Robust Active Noise Control: Minimum Output Variance Approach With Least Mean Lp-Norm Algorithm
    Yang, Wenxing
    Han, Fengxia
    Wang, Guoqing
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71 (04) : 2484 - 2488
  • [30] Group-Based Sparse Representation Based on lp-Norm Minimization for Image Inpainting
    Li, Ruijing
    Tang, Lan
    Bai, Yechao
    Wang, Qiong
    Zhang, Xinggan
    Liu, Min
    IEEE ACCESS, 2020, 8 : 60515 - 60525