Abstract
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 paper, 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.
Original language | English |
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Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | IEEE Transactions on Aerospace and Electronic Systems |
DOIs | |
State | Accepted/In press - 2023 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:IEEE
Keywords
- Array calibration
- Automotive engineering
- Calibration
- Data models
- Direction-of-arrival estimation
- Phased arrays
- Radar
- Sensor arrays
- automotive radar
- forward-backward averaging
- model order selection
- mutual coupling
- phase and gain calibration
- spatial smoothing
- target enumeration