TY - JOUR
T1 - MIMO-Monopulse Target Localization for Automotive Radar
AU - Feng, Ruoyu
AU - Uysal, Faruk
AU - Aubry, Pascal
AU - Yarovoy, Alexander
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2018
Y1 - 2018
N2 - In this study, the authors propose a novel direction of arrival (DoA) estimation algorithm called ‘multiple-input–multiple-output (MIMO)–monopulse’ by combining the monopulse approach with MIMO radar. Monopulse is fast and accurate angle estimation algorithm, which has been well developed for tracking radar. The application of the monopulse technique on MIMO radar is not much considered before, especially for automotive-radar application, and will be discussed in this study. Conventional methods of monopulse DoA estimation include amplitude and phase comparison monopulse. In this study, to improve the performance of monopulse, they utilise Chebyshev and Zolotarev weighting to synthesise sum and difference patterns. A new visualisation method for monopulse ratio is discussed. Finally, they demonstrate the success of the proposed algorithm by processing real data from a 79 GHz frequency-modulated continuous-wave automotive radar.
AB - In this study, the authors propose a novel direction of arrival (DoA) estimation algorithm called ‘multiple-input–multiple-output (MIMO)–monopulse’ by combining the monopulse approach with MIMO radar. Monopulse is fast and accurate angle estimation algorithm, which has been well developed for tracking radar. The application of the monopulse technique on MIMO radar is not much considered before, especially for automotive-radar application, and will be discussed in this study. Conventional methods of monopulse DoA estimation include amplitude and phase comparison monopulse. In this study, to improve the performance of monopulse, they utilise Chebyshev and Zolotarev weighting to synthesise sum and difference patterns. A new visualisation method for monopulse ratio is discussed. Finally, they demonstrate the success of the proposed algorithm by processing real data from a 79 GHz frequency-modulated continuous-wave automotive radar.
UR - http://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2018.5013
U2 - 10.1049/iet-rsn.2018.5013
DO - 10.1049/iet-rsn.2018.5013
M3 - Article
SN - 1751-8784
VL - 12
SP - 1131
EP - 1136
JO - IET Radar, Sonar and Navigation
JF - IET Radar, Sonar and Navigation
IS - 10
ER -