A Total Lp-Norm Optimization for Bearing-Only Source Localization in Impulsive Noise with SαS Distribution

Autor: Ji-An Luo, Chang-Cheng Xue, Ying-Jiao Rong, Shen-Tu Han
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Sensors, Vol 21, Iss 19, p 6471 (2021)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s21196471
Popis: This paper considers the problem of robust bearing-only source localization in impulsive noise with symmetric α-stable distribution based on the Lp-norm minimization criterion. The existing Iteratively Reweighted Pseudolinear Least-Squares (IRPLS) method can be used to solve the least LP-norm optimization problem. However, the IRPLS algorithm cannot reduce the bias attributed to the correlation between system matrices and noise vectors. To reduce this kind of bias, a Total Lp-norm Optimization (TLPO) method is proposed by minimizing the errors in all elements of system matrix and data vector based on the minimum dispersion criterion. Subsequently, an equivalent form of TLPO is obtained, and two algorithms are developed to solve the TLPO problem by using Iterative Generalized Eigenvalue Decomposition (IGED) and Generalized Lagrange Multiplier (GLM), respectively. Numerical examples demonstrate the performance advantage of the IGED and GLM algorithms over the IRPLS algorithm.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje