Resolving ambiguities in estimating spatial frequencies in sparse linear array

Donald W. Tufts; Hongya Ge; Ramdas Kumaresan

doi:10.1109/ICASSP.1994.389649

Resolving ambiguities in estimating spatial frequencies in sparse linear array

Donald W. Tufts, Hongya Ge, Ramdas Kumaresan

Research output: Contribution to journal › Conference article › peer-review

13 Scopus citations

Abstract

We extend our previous work on ambiguity resolution in sparse linear prediction to array signal processing. A non-uniformly spaced linear array with minimum number of sensors is introduced in order to obtain high resolution spatial frequency estimates at reduced computation and at minimum hardware cost. By properly choosing inter-element spacing, combining and processing subarray outputs in parallel, a computationally simple algorithm is proposed for unambiguously estimating spatial frequencies of the source signals.

Original language	English (US)
Article number	389649
Pages (from-to)	II345-II348
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
DOIs	https://doi.org/10.1109/ICASSP.1994.389649
State	Published - 1994
Externally published	Yes
Event	Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6) - Adelaide, Aust Duration: Apr 19 1994 → Apr 22 1994

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.1994.389649

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title = "Resolving ambiguities in estimating spatial frequencies in sparse linear array",

abstract = "We extend our previous work on ambiguity resolution in sparse linear prediction to array signal processing. A non-uniformly spaced linear array with minimum number of sensors is introduced in order to obtain high resolution spatial frequency estimates at reduced computation and at minimum hardware cost. By properly choosing inter-element spacing, combining and processing subarray outputs in parallel, a computationally simple algorithm is proposed for unambiguously estimating spatial frequencies of the source signals.",

author = "Tufts, {Donald W.} and Hongya Ge and Ramdas Kumaresan",

note = "Publisher Copyright: {\textcopyright} 1994 IEEE.; Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6) ; Conference date: 19-04-1994 Through 22-04-1994",

year = "1994",

doi = "10.1109/ICASSP.1994.389649",

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AU - Tufts, Donald W.

AU - Ge, Hongya

AU - Kumaresan, Ramdas

PY - 1994

Y1 - 1994

N2 - We extend our previous work on ambiguity resolution in sparse linear prediction to array signal processing. A non-uniformly spaced linear array with minimum number of sensors is introduced in order to obtain high resolution spatial frequency estimates at reduced computation and at minimum hardware cost. By properly choosing inter-element spacing, combining and processing subarray outputs in parallel, a computationally simple algorithm is proposed for unambiguously estimating spatial frequencies of the source signals.

AB - We extend our previous work on ambiguity resolution in sparse linear prediction to array signal processing. A non-uniformly spaced linear array with minimum number of sensors is introduced in order to obtain high resolution spatial frequency estimates at reduced computation and at minimum hardware cost. By properly choosing inter-element spacing, combining and processing subarray outputs in parallel, a computationally simple algorithm is proposed for unambiguously estimating spatial frequencies of the source signals.

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DO - 10.1109/ICASSP.1994.389649

M3 - Conference article

AN - SCOPUS:85079285085

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

M1 - 389649

T2 - Proceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6)

Y2 - 19 April 1994 through 22 April 1994

ER -

Resolving ambiguities in estimating spatial frequencies in sparse linear array

Abstract

All Science Journal Classification (ASJC) codes

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