Blind Array Calibration of Mutual Coupling, Phase, and Gain for Automotive Radar

被引:3
作者
Casspi, Solomon Goldgraber [1 ]
Tabrikian, Joseph [2 ]
Messer, Hagit [1 ]
机构
[1] Tel Aviv Univ, Sch Elect Engn, IL-6997801 Tel Aviv, Israel
[2] Ben Gurion Univ Negev, Sch Elect & Comp Engn, IL-8410501 Beer Sheva, Israel
基金
以色列科学基金会;
关键词
Calibration; Phased arrays; Radar; Direction-of-arrival estimation; Sensor arrays; Automotive engineering; Data models; Array calibration; automotive radar; forward-backward averaging (FBA); model order selection; mutual coupling (MC); phase and gain calibration; spatial smoothing (SS); target enumeration; OF-ARRIVAL ESTIMATION; SIGNAL-PROCESSING RESEARCH; UNIFORM CIRCULAR ARRAYS; DOA ESTIMATION; SELF-CALIBRATION; 2-D DOA; LOCALIZATION; ALGORITHM;
D O I
10.1109/TAES.2023.3336298
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
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.
引用
收藏
页码:1060 / 1073
页数:14
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