This paper proposes a MIMO imaging method that leverages an extrapolation-iterative adaptive approach to achieve super-resolution capabilities for automotive radar applications. In recent years, autonomous vehicles have incorporated 4D imaging radar systems to attain high-resolution data. The MIMO technique finds application in the design of compact vehicle radars, enabling the adoption of radar-based imaging technology. However, the conventional MIMO imaging approach, relying on the FFT algorithm, encounters challenges in realizing higher resolutions. To overcome this limitation, we propose a MIMO radar implementation founded upon a super-resolution algorithm. Specifically, we investigate the combination of extrapolation and iterative adaptive approach, an iterative algorithm that has gained popularity as a means to mitigate the complexity drawbacks associated with super-resolution techniques. Through simulations and experiments, we validate this method, showcasing its immense potential in enhancing the accuracy and precision of vehicle radar systems.
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Kim et al. (2024) studied this question.
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