Polyphase Waveform and Reflection Design Based on RIS-Aided Radar System

XIE Zhuang; ZHU Jiahua; XU Zhou; FAN Chongyi; JIN Tian; HUANG Xiaotao

doi:10.11999/JEIT230767

Volume 45 Issue 11

Nov. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(11): 3848-3859

XIE Zhuang, ZHU Jiahua, XU Zhou, FAN Chongyi, JIN Tian, HUANG Xiaotao. Polyphase Waveform and Reflection Design Based on RIS-Aided Radar System[J]. Journal of Electronics & Information Technology, 2023, 45(11): 3848-3859. doi: 10.11999/JEIT230767

Citation:

XIE Zhuang, ZHU Jiahua, XU Zhou, FAN Chongyi, JIN Tian, HUANG Xiaotao. Polyphase Waveform and Reflection Design Based on RIS-Aided Radar System[J]. Journal of Electronics & Information Technology, 2023, 45(11): 3848-3859. doi: 10.11999/JEIT230767

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Polyphase Waveform and Reflection Design Based on RIS-Aided Radar System

doi: 10.11999/JEIT230767

1.
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410000, China
2.
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410000, China
3.
College of Electronic Countermeasure, National University of Defense Technology, Hefei 230000, China

Funds: The National Natural Science Foundation of China (62101573), The Scientific Research Project of National University of Defense Technology (ZK20-35)

Received Date: 2023-07-27
Rev Recd Date: 2023-10-17

Available Online: 2023-10-19

Publish Date: 2023-11-28

Abstract

Abstract

This study addresses the joint design problem of radar transmit waveform, receive filter and Reconfigurable Intelligent Surface (RIS) reflecting coefficients with an aim to enhance the target detection performance of a RIS-aided radar system. With restrictions on the finite phases of the radar waveform and RIS reflecting coefficients, the performance enhancement problem is formulated as a nonconvex joint design, in which the system Signal-to-Interference-plus-Noise-Ratio (SINR) is taken as the optimization objective. A novel cyclic optimization algorithm is developed to tackle this. In each cycle, two subproblems with respect to waveform and RIS reflecting coefficients are involved and are resolved by leveraging the Minorization Maximization (MM) strategy. The simulation results highlight the effectiveness of the proposed algorithm for providing high-quality RIS reflecting coefficients, radar transmit waveform, and receive filter.
- Reconfigurable Intelligent Surface (RIS) aided radar,
- Waveform design,
- Target detection,
- Cyclic optimization,
- Polyphase constraint

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References(34)

References

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