基于OTFS的通感一体化感知目标参数估计新算法
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作者单位:

1.南京邮电大学;2.联通物联网有限责任公司

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基金项目:

广东省促进经济发展专项资金项目,面向海洋产业的探测通信一体化立体海洋无线网络系统研究(粤自然资合[2023]24号)


New Target Parameter Estimation Algorithms for Integrated Sensing and Communication Based on OTFS
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Affiliation:

1.Nanjing University of Posts and Telecommunications;2.Unicom Internet of Things Co., Ltd

Fund Project:

the Key Program of Marine Economy Development Special Foundation of the Department of Natural Resources of Guangdong Province(GDNRC[2023]24)

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    摘要:

    在太赫兹频段利用具有叠加导频的OTFS-ISAC车联网系统,能够实现车辆间的高速数据传输,同时进行高精度参数感知。首先,建立并分析了OTFS信号调制模型、通信信号模型和感知信号模型,并在接收端推导了包含角度信息的感知信道新模型。其次,提出了基于均匀网格的MUSIC角度粗估计算法和黄金分割法的MUSIC角度细估计算法。最后,提出了基于最大似然估计准则的信道时延和多普勒频移整数部分参数估计和分数部分参数估计算法。仿真结果表明,所提出的算法能够实现精确的角度、距离、速度等感知参数估计。

    Abstract:

    In the terahertz frequency band, utilizing an OTFS-ISAC vehicular networking system with superimposed pilots can achieve high-speed data transmission between vehicles alongside high-precision parameter sensing. First, the OTFS signal modulation model, communication signal model, and sensing signal model are established and analyzed. At the receiver, a new sensing channel model containing angle information is derived. Subsequently, a coarse angle estimation algorithm based on the uniform grid MUSIC method and a fine angle estimation algorithm based on the golden section MUSIC method are proposed. Finally, a maximum likelihood estimation criterion-based algorithm is proposed for estimating the integer and fractional parts of the channel delay and Doppler shift parameters. Simulation results demonstrate that the proposed algorithms can achieve accurate estimation of sensing parameters such as angle, distance, and velocity.

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  • 收稿日期:2024-09-23
  • 最后修改日期:2024-12-01
  • 录用日期:2025-02-15
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