Sparse DOA Estimation With Polarimetric Arrays

被引：0

作者：

Aubry, Augusto ^{[1
]}

Boddi, Marco ^{[1
]}

De Maio, Antonio ^{[1
]}

Rosamilia, Massimo ^{[1
]}

机构：

[1] Univ Napoli Federico II, Dept Elect Engn & Informat Technol, DIETI, I-80125 Naples, Italy

来源：

IEEE OPEN JOURNAL OF SIGNAL PROCESSING | 2024年 / 5卷

关键词：

Direction-of-arrival estimation; Vectors; Atoms; Signal processing algorithms; Sensors; Maximum likelihood estimation; Covariance matrices; DOA estimation; high resolution; polarimetry; sparse methods; PERFORMANCE ANALYSIS; ESPRIT; RADAR; ANGLE;

D O I：

10.1109/OJSP.2024.3411468

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 addresses the Direction-of-Arrival (DOA) estimation problem using a narrowband polarimetric array sensing system. The considered receiving equipment is composed of two sub-arrays of sensors with orthogonal polarizations. By suitably modeling the received signal via a sparse representation (accounting for the multiple snapshots and the polarimetric array manifold structure), two iterative algorithms, namely Polarimetric Sparse Learning via Iterative Minimization (POL-SLIM) and Polarimetric Sparse Iterative Covariance-based Estimation (POL-SPICE), are devised to accomplish the estimation task. The proposed algorithms provide accurate DOA estimates while enjoying nice (rigorously proven) convergence properties. Numerical analysis shows the effectiveness of POL-SLIM and POL-SPICE to successfully locate signal sources in both passive sensing applications (with large numbers of collected snapshots) and radar spatial processing, also in comparison with single-polarization counterparts as well as theoretical benchmarks.

引用

页码：886 / 901

页数：16

共 46 条

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