Efficient single/multiple unimodular waveform design with low weighted correlations

Yongzhe Li*, Sergiy A. Vorobyov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

8 Citations (Scopus)

Abstract

A new method for designing single/multiple unimodular waveforms with good weighted correlation properties, which is based on minimizing the weighted integrated sidelobe levels of waveforms, is developed. The main contributions of the paper lie in formulating the objective as a quartic form where Hadamard product of matrices is involved, converting the non-convex quartic optimization problem into a quadratic form and then solving it by means of majorization-minimization technique which seeks to find the solution iteratively. Corresponding algorithm enables good weighted correlations of the designed waveforms and shows fast convergence compared with existing methods.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherIEEE
Pages3226-3230
Number of pages5
ISBN (Electronic)9781509041176
DOIs
Publication statusPublished - 16 Jun 2017
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
PublisherIEEE
ISSN (Electronic)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP
CountryUnited States
CityNew Orleans
Period05/03/201709/03/2017

Keywords

  • Majorization-minimization
  • radar
  • waveform design
  • weighted correlations

Press / Media

Cite this

Li, Y., & Vorobyov, S. A. (2017). Efficient single/multiple unimodular waveform design with low weighted correlations. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 3226-3230). [7952752] (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). IEEE. https://doi.org/10.1109/ICASSP.2017.7952752