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Sequence optimization for integrated radar and communication systems using meta-heuristic multiobjective methods
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
Middlesex University, GBR.
2017 (English)In: 2017 IEEE Radar Conference, RadarConf 2017, Institute of Electrical and Electronics Engineers Inc. , 2017, 0502-0507 p.Conference paper, Published paper (Refereed)
Abstract [en]

In real-world engineering problems, several conflicting objective functions have often to be optimized simultaneously. Typically, the objective functions of these problems are too complex to solve using derivative-based optimization methods. Integration of navigation and radar functionality with communication applications is such a problem. Designing sequences for these systems is a difficult task. This task is further complicated by the following factors: (i) conflicting requirements on autocorrelation and crosscorrelation characteristics; (ii) the associated cost functions might be irregular and may have several local minima. Traditional or gradient based optimization methods may face challenges or are unsuitable to solve such a complex problem. In this paper, we pose simultaneous optimization of autocorrelation and crosscorrelation characteristics of Oppermann sequences as a multiobjective problem. We compare the performance of prominent state-of-the-art multiobjective evolutionary meta-heuristic algorithms to design Oppermann sequences for integrated radar and communication systems. © 2017 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2017. 0502-0507 p.
Series
IEEE Radar Conference, ISSN 1097-5764
Keyword [en]
Autocorrelation, Cost functions, Evolutionary algorithms, Heuristic algorithms, Multiobjective optimization, Optimization, Radar, Communication application, Conflicting objectives, Gradient-based optimization method, Meta heuristic algorithm, Multi-objective evolutionary, Multi-objective problem, Multiobjective method, Simultaneous optimization, Heuristic methods
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
URN: urn:nbn:se:bth-15010DOI: 10.1109/RADAR.2017.7944255ISI: 000405307600096Scopus ID: 2-s2.0-85021424787ISBN: 9781467388238 OAI: oai:DiVA.org:bth-15010DiVA: diva2:1135423
Conference
2017 IEEE Radar Conference, RadarConf, Seattle
Available from: 2017-08-23 Created: 2017-08-23 Last updated: 2017-08-24Bibliographically approved

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Jamil, MominZepernick, Hans-Juergen
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf