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Antenna Array Calibration Using a Sparse Scene

Johanna Geiß, Erik Sippel, Markus Hehn, Martin Vossiek

2021IEEE Open Journal of Antennas and Propagation17 citationsDOIOpen Access PDF

Abstract

In radar systems, antenna arrays acquire direction-dependent information to localize targets or create images of the environment. However, because of unknown complex amplitudes per channel and mutual coupling, a calibration is necessary for good performance. Common calibration approaches measure to targets under known angles in a multipath-free far-field environment, which often can only be provided by anechoic chambers. Therefore, this process is not suitable for low-cost and frequent calibration. To overcome these limitations, this paper proposes a novel calibration approach using an unknown but sparse target scene. Multiple measurements at known relative positions of the radar are combined to a synthetic aperture. Then, the full mutual coupling matrix is estimated simultaneously with the unknown target scene. The method requires neither target position information, far-field conditions, nor an anechoic chamber because multipath propagation can be suppressed easily for targets located in the near-field. The proposed calibration approach is validated by measurements of a commercial 77GHz radar. The performance is evaluated by comparing the achieved image quality using the calibration results of this work and the radar's ex-factory calibration data. The proposed novel calibration procedure improves the image quality, while considerably lowering the demands on the calibration measurements and environment.

Topics & Concepts

Anechoic chamberCalibrationComputer scienceRadarMultipath propagationAntenna (radio)Remote sensingChannel (broadcasting)Radar imagingSynthetic aperture radarComputer visionArtificial intelligenceAcousticsElectronic engineeringEngineeringTelecommunicationsPhysicsGeologyQuantum mechanicsAdvanced SAR Imaging TechniquesSynthetic Aperture Radar (SAR) Applications and TechniquesAntenna Design and Optimization
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