Closed-form eigenstructure-based direction finding using arbitrary but identical subarrays on a sparse uniform Cartesian array grid

Author

Zoltowski, Michael D. ; Wong, Kainam Thomas

Author_Institution

Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA

Volume

48

Issue

8

fYear

2000

fDate

8/1/2000 12:00:00 AM

Firstpage

2205

Lastpage

2210

Abstract

A sparse uniform Cartesian-grid array suffers cyclic ambiguity in its Cartesian direction-cosine estimates due to the spatial Nyquist sampling theorem. The proposed MUSIC-based or MODE-based algorithm improves and generalizes previous disambiguation schemes that populate the thin array grid with identical subarrays-such as electromagnetic vector sensors, underwater acoustic vector hydrophones, or half-wavelength spaced subarrays

Keywords

acoustic signal processing; array signal processing; direction-of-arrival estimation; eigenvalues and eigenfunctions; hydrophones; radio direction-finding; sensors; signal classification; signal sampling; underwater sound; Cartesian direction-cosine estimates; MODE-based algorithm; MUSIC-based algorithm; closed-form eigenstructure-based direction finding; cyclic ambiguity; disambiguation schemes; electromagnetic vector sensors; half-wavelength spaced subarrays; identical subarrays; sparse uniform Cartesian array grid; spatial Nyquist sampling theorem; thin array grid; underwater acoustic vector hydrophones; Acoustic arrays; Acoustic sensors; Geometry; Intelligent sensors; Narrowband; Phased arrays; Radar signal processing; Sensor arrays; Signal processing algorithms; Underwater acoustics;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.852001

Filename

852001