Hybrid Optimization Method for Cognitive and MIMO Radar Code Design

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1 Citation (Scopus)


Cognitive and MIMO radars need to adapt the transmitted waveforms based on the radar task as well as the propagation and the target environments. Many waveform optimization methods proposed in the literature for optimizing the sidelobe and cross-correlation levels are based on stochastic search algorithms or slow numerical approximation methods. However, for real-time applications, it is necessary to perform the optimization fast since the radar channels and target parameters may vary rapidly. For this purpose, we propose a hybrid optimization approaches based on gradient and randomization for fast optimization of the transmit waveform codes.
Original languageEnglish
Title of host publication2017 25th European Signal Processing Conference (EUSIPCO)
ISBN (Electronic)978-0-9928626-7-1
ISBN (Print)978-1-5386-0751-0
Publication statusPublished - 26 Oct 2017
MoE publication typeA4 Article in a conference publication
EventEuropean Signal Processing Conference - Kos Island, Greece, Kos, Greece
Duration: 28 Aug 20172 Sep 2017
Conference number: 25

Publication series

NameEuropean Signal Processing Conference
ISSN (Electronic)2076-1465


ConferenceEuropean Signal Processing Conference
Abbreviated titleEUSIPCO
Internet address

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  • Cite this

    Aittomäki, T., & Koivunen, V. (2017). Hybrid Optimization Method for Cognitive and MIMO Radar Code Design. In 2017 25th European Signal Processing Conference (EUSIPCO) (pp. 2226-2229). (European Signal Processing Conference). IEEE. https://doi.org/10.23919/EUSIPCO.2017.8081605