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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.00668 |
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| _version_ | 1866914070014197760 |
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| author | Zhang, Xiaojuan Zeng, Yonghong Shin, Francois Chin Po |
| author_facet | Zhang, Xiaojuan Zeng, Yonghong Shin, Francois Chin Po |
| contents | We propose an Joint Radar and Communication (JRC) system that utilizes the Orthogonal Time Frequency Space (OTFS) signals. The system features a fast radar sensing algorithm for detecting target range and speed by using the OTFS communication signals, and a self-interference cancellation for enhanced multi-target separation. In addition to target detection, we propose methods for monitoring human vital signs, such as breathing rate and heartbeat. Furthermore, we explore two approaches for distinguishing between human and nonhuman targets: one based on signal processing and the other based on machine learning. We have developed a prototype JRC system using the software-defined radio (SDR) technology. Experimental results are shown to demonstrate the effectiveness of the prototype in detecting range, speed, and vital signs in both human and mobile robot scenarios, as well as in distinguishing between human and non-human targets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_00668 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments Zhang, Xiaojuan Zeng, Yonghong Shin, Francois Chin Po Information Theory We propose an Joint Radar and Communication (JRC) system that utilizes the Orthogonal Time Frequency Space (OTFS) signals. The system features a fast radar sensing algorithm for detecting target range and speed by using the OTFS communication signals, and a self-interference cancellation for enhanced multi-target separation. In addition to target detection, we propose methods for monitoring human vital signs, such as breathing rate and heartbeat. Furthermore, we explore two approaches for distinguishing between human and nonhuman targets: one based on signal processing and the other based on machine learning. We have developed a prototype JRC system using the software-defined radio (SDR) technology. Experimental results are shown to demonstrate the effectiveness of the prototype in detecting range, speed, and vital signs in both human and mobile robot scenarios, as well as in distinguishing between human and non-human targets. |
| title | OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments |
| topic | Information Theory |
| url | https://arxiv.org/abs/2510.00668 |