Radar Sensing via OTFS Signaling

被引:0
|
作者
Kecheng Zhang [1 ]
Zhongjie Li [1 ]
Weijie Yuan [1 ]
Yunlong Cai [2 ]
Feifei Gao [3 ]
机构
[1] Department of Electronic and Electrical Engineering, Southern University of Science and Technology
[2] College of Information Science and Electronic Engineering, Zhejiang University
[3] Department of Automation, Tsinghua University
关键词
D O I
暂无
中图分类号
TN957.52 [数据、图像处理及录取];
学科分类号
080904 ; 0810 ; 081001 ; 081002 ; 081105 ; 0825 ;
摘要
By multiplexing information symbols in the delay-Doppler(DD) domain, orthogonal time frequency space(OTFS) is a promising candidate for future wireless communication in high-mobility scenarios. In addition to the superior communication performance, OTFS is also a natural choice for radar sensing since the primary parameters(range and velocity of targets) in radar signal processing can be inferred directly from the delay and Doppler shifts. Though there are several works on OTFS radar sensing, most of them consider the integer parameter estimation only,while the delay and Doppler shifts are usually fractional in the real world. In this paper, we propose a two-step method to estimate the fractional delay and Doppler shifts. We first perform the two-dimensional(2D) correlation between the received and transmitted DD domain symbols to obtain the integer parts of the parameters. Then a difference-based method is implemented to estimate the fractional parts of delay and Doppler indices. Meanwhile, we implement a target detection method based on a generalized likelihood ratio test since the number of potential targets in the sensing scenario is usually unknown. The simulation results show that the proposed method can obtain the delay and Doppler shifts accurately and get the number of sensing targets with a high detection probability.
引用
收藏
页码:34 / 45
页数:12
相关论文
共 50 条
  • [21] Analysis of Frequency Agile Radar via Compressed Sensing
    Huang, Tianyao
    Liu, Yimin
    Xu, Xingyu
    Eldar, Yonina C.
    Wang, Xiqin
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2018, 66 (23) : 6228 - 6240
  • [22] Robust Doppler radar demodulation via compressed sensing
    Xu, W.
    Gu, C.
    Li, C.
    Sarrafzadeh, M.
    ELECTRONICS LETTERS, 2012, 48 (22) : 1428 - 1429
  • [23] The Estimation Method of Sensing Parameters Based on OTFS
    Tang, Zhiling
    Jiang, Zhou
    Pan, Wanghua
    Zeng, Lizhen
    IEEE ACCESS, 2023, 11 : 66035 - 66049
  • [24] High-Resolution Radar via Compressed Sensing
    Herman, Matthew A.
    Strohmer, Thomas
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (06) : 2275 - 2284
  • [25] Detecting Falls and Vital Signs via Radar Sensing
    Diraco, Giovanni
    Leone, Alessandro
    Siciliano, Pietro
    2017 IEEE SENSORS, 2017, : 1587 - 1589
  • [26] Joint Radar Target Detection and Parameter Estimation with MIMO OTFS
    Gaudio, Lorenzo
    Kobayashi, Mari
    Caire, Giuseppe
    Colavolpe, Giulio
    2020 IEEE RADAR CONFERENCE (RADARCONF20), 2020,
  • [27] Performance Analysis of Joint Radar and Communication using OFDM and OTFS
    Gaudio, Lorenzo
    Kobayashi, Mari
    Bissinger, Bjoern
    Caire, Giuseppe
    2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2019,
  • [28] Near-Field Radar Imaging via Compressive Sensing
    Li, Shiyong
    Zhao, Guoqiang
    Li, Houmin
    Ren, Bailing
    Hu, Weidong
    Liu, Yong
    Yu, Weihua
    Sun, Houjun
    IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2015, 63 (02) : 828 - 833
  • [29] EXAMPLES FOR THE APPLICATION OF RADAR TO REMOTE-SENSING VIA SATELLITE
    SIEBER, A
    ACTA ASTRONAUTICA, 1984, 11 (01) : 15 - 31
  • [30] Posture-Robust Breath Sensing via Imaging Radar
    Zhang, Jinli
    Zhang, Dongheng
    Chen, Jinbo
    Wang, Haoyu
    Wu, Changwei
    Gong, Hanqin
    Han, Shijie
    Chen, Yan
    2023 IEEE INTERNATIONAL CONFERENCES ON INTERNET OF THINGS, ITHINGS IEEE GREEN COMPUTING AND COMMUNICATIONS, GREENCOM IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING, CPSCOM IEEE SMART DATA, SMARTDATA AND IEEE CONGRESS ON CYBERMATICS,CYBERMATICS, 2024, : 219 - 226