Low-Rank Beamforming

Jacob Benesty; Gongping Huang; Jingdong Chen; Ningning Pan

doi:10.1007/978-3-031-36974-2_5

Low-Rank Beamforming

Jacob Benesty, Gongping Huang, Jingdong Chen, Ningning Pan

School of Marine Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

Nature is usually low rank! This means that there is nonnegligible redundancy in the observations. So, it is important to be able to translate this idea into equations in order to make things work better in practice. In this chapter, we discuss this concept and explain how it can be applied to beamforming. Then, we derive a large class of low-rank fixed and adaptive beamformers.

Original language	English
Title of host publication	Springer Topics in Signal Processing
Publisher	Springer Science and Business Media B.V.
Pages	87-111
Number of pages	25
DOIs	https://doi.org/10.1007/978-3-031-36974-2_5
State	Published - 2024

Publication series

Name	Springer Topics in Signal Processing
Volume	22
ISSN (Print)	1866-2609
ISSN (Electronic)	1866-2617

Keywords

Kronecker product decomposition
Low-rank beamforming
Optimal beamformer

Access to Document

10.1007/978-3-031-36974-2_5

Cite this

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Low-Rank Beamforming

Abstract

Publication series

Keywords

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