TY - JOUR
T1 - Blind Array Calibration of Mutual Coupling, Phase, and Gain for Automotive Radar
AU - Casspi, Solomon Goldgraber
AU - Tabrikian, Joseph
AU - Messer, Hagit
N1 - Publisher Copyright:
© 1965-2011 IEEE.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - One of the limiting factors in the performance of radar systems is the presence of mutual coupling (MC) between receive antenna elements or array imperfections, such as antenna phase and gain errors. Therefore, the data model is misspecified, resulting in high sidelobe levels in the beam pattern, low angular resolution, and biased angle estimation. In this article, we propose a blind calibration scheme for uniform planar arrays. Our method is based on multiple measurements of various scenarios, with an arbitrary and unknown number of targets-of-opportunity, unknown directions-of-arrival (DOAs), and unknown intensities. The proposed method is based on spatial smoothing and forward-backward averaging techniques, in order to identify the signal and noise subspaces. In the presence of MC or array imperfections, the signal subspace leaks into the noise subspace. The proposed method seeks to find and compensate for model misspecification using a model-order selection criterion. We evaluate the performance of our method through simulations, in terms of DOA estimation accuracy and resolution. Our results demonstrate that the DOA estimation performance after calibration with our proposed method is close to that of a perfectly calibrated array.
AB - One of the limiting factors in the performance of radar systems is the presence of mutual coupling (MC) between receive antenna elements or array imperfections, such as antenna phase and gain errors. Therefore, the data model is misspecified, resulting in high sidelobe levels in the beam pattern, low angular resolution, and biased angle estimation. In this article, we propose a blind calibration scheme for uniform planar arrays. Our method is based on multiple measurements of various scenarios, with an arbitrary and unknown number of targets-of-opportunity, unknown directions-of-arrival (DOAs), and unknown intensities. The proposed method is based on spatial smoothing and forward-backward averaging techniques, in order to identify the signal and noise subspaces. In the presence of MC or array imperfections, the signal subspace leaks into the noise subspace. The proposed method seeks to find and compensate for model misspecification using a model-order selection criterion. We evaluate the performance of our method through simulations, in terms of DOA estimation accuracy and resolution. Our results demonstrate that the DOA estimation performance after calibration with our proposed method is close to that of a perfectly calibrated array.
KW - Array calibration
KW - automotive radar
KW - forward-backward averaging (FBA)
KW - model order selection
KW - mutual coupling (MC)
KW - phase and gain calibration
KW - spatial smoothing (SS)
KW - target enumeration
UR - http://www.scopus.com/inward/record.url?scp=85179038681&partnerID=8YFLogxK
U2 - 10.1109/TAES.2023.3336298
DO - 10.1109/TAES.2023.3336298
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AN - SCOPUS:85179038681
SN - 0018-9251
VL - 60
SP - 1060
EP - 1073
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 1
ER -