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학술지 Compressive Sensing-Based Radar Imaging and Subcarrier Allocation for Joint MIMO OFDM Radar and Communication System
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저자
황성준, 서지호, 박재현, 김형주, 정병장
발행일
202104
출처
Sensors, v.21 no.7, pp.1-16
ISSN
1424-8220
출판사
MDPI
DOI
https://dx.doi.org/10.3390/s21072382
협약과제
21ZH1100, 연결의 한계를 극복하는 초연결 입체통신 기술 연구, 박승근
초록
In this paper, a joint multiple-input multiple-output (MIMO OFDM) radar and communication (RadCom) system is proposed, in which orthogonal frequency division multiplexing (OFDM) waveforms carrying data to be transmitted to the information receiver are exploited to get high-resolution radar images at the RadCom platform. Specifically, to get two-dimensional (i.e., range and azimuth angle) radar images with high resolution, a compressive sensing-based imaging algorithm is proposed that is applicable to the signal received through multiple receive antennas. Because both the radar imaging performance (i.e., the mean square error of the radar image) and the communication performance (i.e., the achievable rate) are affected by the subcarrier allocation across multiple transmit antennas, by analyzing both radar imaging and communication performances, we also propose a subcarrier allocation strategy such that a high achievable rate is obtained without sacrificing the radar imaging performance.
키워드
Bayesian matching pursuit, MIMO OFDM radar and communication, Subcarrier allocation strategy
KSP 제안 키워드
Achievable rate, Azimuth Angle, Bayesian matching pursuit, Communication performance, Communication system, Compressive sensing, Imaging performance, Multiple input multiple output(MIMO), Multiple input multiple output orthogonal frequency division multiplexing(MIMO-OFDM), Multiple receive antennas, OFDM radar