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Journal Article
Compressive Sensing-Based Radar Imaging and Subcarrier Allocation for Joint MIMO OFDM Radar and Communication System
- Authors
- SeongJun Hwang, Jiho Seo, Jaehyun Park, Hyungju Kim, Byung Jang Jeong
- Issue Date
- 2021-04
- Citation
- Sensors, v.21, no.7, pp.1-16
- ISSN
- 1424-8220
- Publisher
- MDPI
- Language
- English
- Type
- Journal Article
- Abstract
- 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.
- KSP Keywords
- Achievable rate, Azimuth Angle, 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, Orthogonal frequency division Multiplexing(OFDM)
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
