A Convex Hull Based Approach for MIMO Radar Waveform Design with Quantized Phases

Weichao Pi, Chenglin Ren, Jianming Zhou

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

Abstract

In this letter, we focus on designing constant-modulus waveform with discrete phases for the multi-input multi-output (MIMO) radar system, where the signal-to-interference-plus-noise ratio (SINR) is maximized in the presence of both the signal independent clutter and the noise. Because of the NP-hardness of the above formulated problem, we take advantage of successive convex hulls of the discrete feasible region to relax the original hard optimization problem to a sequence of several continuous quadratic programming (QP) subproblems. Compared with the conventional SDR technique, the proposed method yields approximated solutions with lower computational costs. In the final part, several numerical simulations were taken to prove the effectiveness of the proposed methody.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages413-417
Number of pages5
ISBN (Electronic)9781728119076
DOIs
Publication statusPublished - Dec 2019
Event4th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019 - Chengdu, China
Duration: 20 Dec 201922 Dec 2019

Publication series

NameProceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019

Conference

Conference4th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
Country/TerritoryChina
CityChengdu
Period20/12/1922/12/19

Keywords

  • MIMO radar
  • convex hull
  • discrete phases
  • waveform design

Fingerprint

Dive into the research topics of 'A Convex Hull Based Approach for MIMO Radar Waveform Design with Quantized Phases'. Together they form a unique fingerprint.

Cite this