Abstract

Coded-aperture antenna plays an important role in terahertz coded-aperture imaging radar system. However, the performance of a system is inevitably affected by the phase errors introduced by the coded-aperture antenna elements. In this paper, we propose a phase error compensation method by deducing a formula to compute all element phase errors accurately. According to the formula, the phase errors can be calibrated by using a calibrator and can be used to compensate the imaging model of the system. Numerical simulations demonstrate that the proposed method can effectively improve the imaging quality when the elemental phase error exceeds 10 ∘ .

Highlights

  • As a promising imaging technology, terahertz coded-aperture imaging (TCAI) has the advantages of both terahertz imaging [1,2,3] and coded-aperture imaging [4,5]

  • After the phase error is obtained by using the calibrator and the appropriate coding sequences, we can bring the results calculated into Equation (5) to compensate the phase and correct the imaging model

  • This paper analyzes the influence of phase error on the TCAI model and proposes an antenna phase error compensation method for TCAI method

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Summary

Introduction

As a promising imaging technology, terahertz coded-aperture imaging (TCAI) has the advantages of both terahertz imaging [1,2,3] and coded-aperture imaging [4,5]. A low-profile aperture capable of microwave imaging was demonstrated by leveraging metamaterials and compressive imaging [11] This is the first time to propose aperture-coded imaging algorithm based on metamaterials. In 2015, the authors in [18] proposed the sparse auto-calibration method to compensate the gain-phase error in radar coincidence imaging. In 2019 a novel online antenna array calibration method was presented for estimating DOA in the case of uncorrelated and coherent signals with unknown gain-phase errors [21]. These methods are efficient, there are still some challenges. The proposed method is robust and can significantly improve the imaging quality

Principle of the Proposed Method
Numerical Experiments and Discussions
Effect of Phase Error
Performance for Different Targets with Different Algorithms
Performance with TVAL3 Algorithm under Different SNRs
Findings
Conclusions
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