TY - GEN
T1 - MIMO imaging method with iterative-based super-resolution for automotive radar
AU - Kim, Bong Seok
AU - Lee, Jonghun
AU - Jin, Youngseok
AU - Kim, Sangdong
AU - Narayanan, Ram M.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper proposes a MIMO imaging method with an iterative-based super-resolution technique for automotive radar applications. Vehicle radars have recently used 4D imaging radar, offering improved detection ranges and high-resolution capability. The application of imaging radar technology aims to extend the maximum detection distance through noise reduction techniques while also enabling the miniaturization of vehicle radars using the MIMO approach. To enhance the maximum detection distance, we employ a Wavelet-based noise reduction method for range FFT. Additionally, for improved angular resolution, we use a MIMO radar implementation based on a super-resolution algorithm, in contrast to the conventional MIMO imaging method that utilizes the FFT algorithm. Specifically, we focus on an emerging iterative-based algorithm, which effectively addresses the complexity issues associated with super-resolution techniques. Through extensive experiments, we validate the effectiveness of this proposed method. The results demonstrate its potential in realizing wide detection distance and high-resolution for vehicle radar systems.
AB - This paper proposes a MIMO imaging method with an iterative-based super-resolution technique for automotive radar applications. Vehicle radars have recently used 4D imaging radar, offering improved detection ranges and high-resolution capability. The application of imaging radar technology aims to extend the maximum detection distance through noise reduction techniques while also enabling the miniaturization of vehicle radars using the MIMO approach. To enhance the maximum detection distance, we employ a Wavelet-based noise reduction method for range FFT. Additionally, for improved angular resolution, we use a MIMO radar implementation based on a super-resolution algorithm, in contrast to the conventional MIMO imaging method that utilizes the FFT algorithm. Specifically, we focus on an emerging iterative-based algorithm, which effectively addresses the complexity issues associated with super-resolution techniques. Through extensive experiments, we validate the effectiveness of this proposed method. The results demonstrate its potential in realizing wide detection distance and high-resolution for vehicle radar systems.
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U2 - 10.1109/ICASSP48485.2024.10447186
DO - 10.1109/ICASSP48485.2024.10447186
M3 - Conference contribution
AN - SCOPUS:85195413671
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 13031
EP - 13035
BT - 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024
Y2 - 14 April 2024 through 19 April 2024
ER -