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Distributed MIMO radar target altitude estimation for ground-based systems

Authors
Shin, HyuksooChung, Wonzoo
Issue Date
4월-2019
Publisher
INST ENGINEERING TECHNOLOGY-IET
Keywords
MIMO radar; least squares approximations; radar antennas; antenna arrays; ground-based systems; target localisation methods; linear least squares; altitude localisation; ellipsoid fitting approach; target position information; distributed MIMO radar target altitude estimation; multiple-input multiple-output radars; BRM algorithm
Citation
IET RADAR SONAR AND NAVIGATION, v.13, no.4, pp.627 - 637
Indexed
SCIE
SCOPUS
Journal Title
IET RADAR SONAR AND NAVIGATION
Volume
13
Number
4
Start Page
627
End Page
637
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/66469
DOI
10.1049/iet-rsn.2018.5159
ISSN
1751-8784
Abstract
This study presents novel target altitude estimation schemes optimised for ground-based multiple-input multiple-output (MIMO) radars with widely separated antennae, where the antennae are located in a plane so that the altitudes of the antennae are close together. For the ground-based systems, existing target localisation methods based on linear least squares such as least square (LS) and bistatic range measurement (BRM) suffer from performance degradation in target altitude estimation and eventually fail in altitude localisation for a perfect ground-based system where the altitude of antennae are the same. The authors propose three target altitude estimation schemes based on linear least squares for the ground-based systems resolving the drawback of existing algorithms for the ground-based systems; extended BRM approach, which estimates the square of target altitude from the auxiliary parameters produced by BRM algorithm, ellipsoid fitting approach, which directly estimates the square of target altitude with other target position information, and extended ellipsoid fitting approach, which utilise the estimation results of ellipsoid fitting approach to improve the target altitude estimation performance. Performance improvement of the proposed algorithms is analysed in terms of mean squared error and simulation results verify the performance.
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