Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization

Yongzhe Li; Sergiy A. Vorobyov; Zishu He

doi:10.1109/EUSIPCO.2016.7760646

Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization

Yongzhe Li, Sergiy A. Vorobyov, Zishu He

Sergiy Vorobyov Group

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

15 Citations (Scopus)

Abstract

We develop a new efficient method for designing unimodular waveforms with good auto- and cross-correlation properties for multiple-input multiple-output (MIMO) radar. Our waveform design scheme is conducted based on minimization of the integrated sidelobe level of designed waveforms, which is formulated as a quartic non-convex optimization problem. We start from simplifying the quartic optimization problem and then transform it into a quadratic form. By means of the majorizationminimization technique that seeks to find the solution of a corresponding quadratic optimization problem, we resolve the design of waveforms for MIMO radar. Corresponding algorithms that enable good correlations of the designed waveforms and meanwhile show faster convergence as compared to their counterparts are proposed and then tested.

Original language	English
Title of host publication	Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016
Publisher	IEEE
Pages	2235-2239
Number of pages	5
Volume	2016-November
ISBN (Electronic)	9780992862657
DOIs	https://doi.org/10.1109/EUSIPCO.2016.7760646
Publication status	Published - 28 Nov 2016
MoE publication type	A4 Article in a conference publication
Event	European Signal Processing Conference - Budapest, Hungary Duration: 28 Aug 2016 → 2 Sep 2016 Conference number: 24 http://www.eusipco2016.org/

Publication series

Name	European Signal Processing Conference
Publisher	Institute of Electrical and Electronics Engineers, Inc.
ISSN (Print)	2219-5491
ISSN (Electronic)	2076-1465

Conference

Conference	European Signal Processing Conference
Abbreviated title	EUSIPCO
Country/Territory	Hungary
City	Budapest
Period	28/08/2016 → 02/09/2016
Internet address	http://www.eusipco2016.org/

Access to Document

10.1109/EUSIPCO.2016.7760646

OpenUrl availability

Full text

Cite this

Li, Y., Vorobyov, S. A., & He, Z. (2016). Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization. In Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016 (Vol. 2016-November, pp. 2235-2239). [7760646] (European Signal Processing Conference). IEEE. https://doi.org/10.1109/EUSIPCO.2016.7760646

@inproceedings{1974312de77c499c8c59ee2b210c1d5a,

title = "Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization",

abstract = "We develop a new efficient method for designing unimodular waveforms with good auto- and cross-correlation properties for multiple-input multiple-output (MIMO) radar. Our waveform design scheme is conducted based on minimization of the integrated sidelobe level of designed waveforms, which is formulated as a quartic non-convex optimization problem. We start from simplifying the quartic optimization problem and then transform it into a quadratic form. By means of the majorizationminimization technique that seeks to find the solution of a corresponding quadratic optimization problem, we resolve the design of waveforms for MIMO radar. Corresponding algorithms that enable good correlations of the designed waveforms and meanwhile show faster convergence as compared to their counterparts are proposed and then tested.",

author = "Yongzhe Li and Vorobyov, {Sergiy A.} and Zishu He",

year = "2016",

month = nov,

day = "28",

doi = "10.1109/EUSIPCO.2016.7760646",

language = "English",

volume = "2016-November",

series = "European Signal Processing Conference",

publisher = "IEEE",

pages = "2235--2239",

booktitle = "Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016",

address = "United States",

note = "European Signal Processing Conference, EUSIPCO ; Conference date: 28-08-2016 Through 02-09-2016",

url = "http://www.eusipco2016.org/",

}

Li, Y, Vorobyov, SA & He, Z 2016, Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization. in Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016. vol. 2016-November, 7760646, European Signal Processing Conference, IEEE, pp. 2235-2239, European Signal Processing Conference, Budapest, Hungary, 28/08/2016. https://doi.org/10.1109/EUSIPCO.2016.7760646

Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization. / Li, Yongzhe; Vorobyov, Sergiy A.; He, Zishu.

Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016. Vol. 2016-November IEEE, 2016. p. 2235-2239 7760646 (European Signal Processing Conference).

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

TY - GEN

T1 - Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization

AU - Li, Yongzhe

AU - Vorobyov, Sergiy A.

AU - He, Zishu

N1 - Conference code: 24

PY - 2016/11/28

Y1 - 2016/11/28

N2 - We develop a new efficient method for designing unimodular waveforms with good auto- and cross-correlation properties for multiple-input multiple-output (MIMO) radar. Our waveform design scheme is conducted based on minimization of the integrated sidelobe level of designed waveforms, which is formulated as a quartic non-convex optimization problem. We start from simplifying the quartic optimization problem and then transform it into a quadratic form. By means of the majorizationminimization technique that seeks to find the solution of a corresponding quadratic optimization problem, we resolve the design of waveforms for MIMO radar. Corresponding algorithms that enable good correlations of the designed waveforms and meanwhile show faster convergence as compared to their counterparts are proposed and then tested.

AB - We develop a new efficient method for designing unimodular waveforms with good auto- and cross-correlation properties for multiple-input multiple-output (MIMO) radar. Our waveform design scheme is conducted based on minimization of the integrated sidelobe level of designed waveforms, which is formulated as a quartic non-convex optimization problem. We start from simplifying the quartic optimization problem and then transform it into a quadratic form. By means of the majorizationminimization technique that seeks to find the solution of a corresponding quadratic optimization problem, we resolve the design of waveforms for MIMO radar. Corresponding algorithms that enable good correlations of the designed waveforms and meanwhile show faster convergence as compared to their counterparts are proposed and then tested.

UR - http://www.scopus.com/inward/record.url?scp=85005973785&partnerID=8YFLogxK

U2 - 10.1109/EUSIPCO.2016.7760646

DO - 10.1109/EUSIPCO.2016.7760646

M3 - Conference contribution

AN - SCOPUS:85005973785

VL - 2016-November

T3 - European Signal Processing Conference

SP - 2235

EP - 2239

BT - Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016

PB - IEEE

T2 - European Signal Processing Conference

Y2 - 28 August 2016 through 2 September 2016

ER -

Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization

Abstract

Publication series

Conference

Access to Document

OpenUrl availability

Other files and links

Fingerprint

Advances and New Opportunities in MIMO Radar - Theoretical Analysis and Algorithms

Cite this

Design of multiple unimodular waveforms with low auto- and cross-correlations for radar via majorization-minimization

Abstract

Publication series

Conference

Access to Document

OpenUrl availability

Other files and links

Fingerprint

Press/Media

Advances and New Opportunities in MIMO Radar - Theoretical Analysis and Algorithms

Cite this